ISSN 1945-6123
Journal of
Registry Management
Winter 2011 • Volume 38 • Number 4
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Winter 2011 • Volume 38 • Number 4
Original Articles
Contents
Surveillance of US Deaths Related to Myelodysplastic Syndromes, and the Need
for Linkages with Central Cancer Registries...................................................................183
Anthony P. Polednak, PhD
Using NAPIIA to Improve the Accuracy of Asian Race Codes in Registry Data......190
Mei-Chin Hsieh, MSPH, CTR; Lisa A. Pareti, BS, RHIT, CTR; Vivien W. Chen, PhD
Conforming to Cancer Staging, Prognostic Indicators and National Treatment
Guidelines.............................................................................................................................196
Gwendylen R. Dykstra-Long, RHIA, CTR, CMT
Histological Classification of Liver and Intrahepatic Bile Duct Cancers in
SEER Registries....................................................................................................................201
Sean F. Altekruse, DVM, PhD; Susan S. Devesa, PhD; Lois A. Dickie, CTR; Katherine A.
McGlynn, PhD; David E. Kleiner, MD
Maximizing The Cancer Registry Role and Data Utilization.......................................206
Xuan Barzilay, MBA, CTR
Embedding QR Codes in Tumor Board Presentations, Enhancing Educational
Content for Oncology Information Management........................................................... 209
Richard Siderits, MD; Stacy Yates; Arelis Rodriguez; Tina Lee; Cheryl Rimmer, MD; Mark
Roche, MD, MMI
Features and Other Journal Departments
The Blending of ICD-O-3 with SEER Inquiry (SINQ).................................................... 212
Antonio Bernal, RHIT, CTR
Raising the Bar: It Matters..................................................................................................214
Michele Webb, CTR
Role of CLPs Will Focus on Quality under 2012 Standards..........................................216
Fall 2011 Continuing Education Quiz Answers .............................................................217
Deborah C. Roberson, MSM, CTR; Denise Harrison, BS, CTR
Winter 2011 Continuing Education Quiz......................................................................... 218
Deborah C. Roberson, MSM, CTR; Denise Harrison, BS, CTR
Index......................................................................................................................................220
Call for Papers......................................................................................................................235
Information for Authors.....................................................................................................236
Copyright © 2011
National Cancer
Registrars Association
Journal of Registry Management 2011 Volume 38 Number 4
181
Editors
Vicki Nelson, MPH, RHIT, CTR, Editor-in-Chief
Reda J. Wilson, MPH, RHIT, CTR, Editor Emeritus
Ginger Yarger, Copy Editor
Michael Hechter, Production Editor
Production and Printing
The Goetz Printing Company
Contributing Editors
Faith G. Davis, PhD—Epidemiology
April Fritz, BA, RHIT, CTR—Cancer Registry
Denise Harrison, BS, CTR—CE Credits
Deborah C. Roberson, MSM, CTR—CE Credits
Michele A. Webb, CTR
NCRA 2011–2012 Board of Directors
President: Melanie Rogan, CTR
President Elect/Secretary: Sarah Burton, CTR
Immediate Past President: Susan M. Koering, MEd, RHIA, CTR
Treasurer Senior: Kathy Dunaway, CTR
Treasurer Junior: Terri Richardson, RHIA, CTR
Educational Director: Ellen Kolender, RHIA, CTR
Professional Development Director: Louise Schuman, MA, CTR
Public Relations Director & Liaison to JRM: Amy Walde, MBA,
MHA, CTR
Recruitment/Retention Director: Joyce Ritter, RHIA, CTR
ATP Director—East: Nadine Jenkins, CTR
Indexing
The Journal of Registry Management is indexed in the National
Library of Medicine’s MEDLINE database. Citations from
the articles indexed, the indexing terms (key words), and the
English abstract printed in JRM are included and searchable
using PubMed.
For your convenience, the Journal of Registry Management
is indexed in the 4th issue of each year and on the Web
(under “Resources” at http://www.ncra-usa.org/jrm).
The 4th issue indexes all articles for that particular year.
The Web index is a cumulative index of all JRM articles
ever published.
ATP Director—Midwest: Laurie Hebert, RHIA, CCS, CCS-P, CTR
ATP Director—West: Linda Fine, CTR
182
Journal of Registry Management 2011 Volume 38 Number 4
Original Article
Surveillance of US Deaths Related to
Myelodysplastic Syndromes, and the Need for
Linkages with Central Cancer Registries
Anthony P. Polednak, PhDa
Abstract: Myelodysplastic syndromes (MDS) are a heterogeneous group of tumors with subgroups that differ in prognosis,
including risk of transformation to leukemia and also in survival rate. An analysis was conducted of deaths in US residents
with MDS coded on the death certificate, for surveillance of MDS-related death rates. MDS was coded for 18,304 deaths
in 2005-2006 (age-standardized rate = 2.98 per 100,000 per year) using multiple causes of death vs 9,995 (age-standardized
rate =1.63 per 100,000 per year) using only the underlying cause of death. For deaths with MDS mentioned as other than
the underlying cause, the most common underlying causes were cancers (of which 65% were leukemia) and cardiovascular diseases. Thus, surveillance of MDS-related mortality is unusual in comparison to most types of cancer, in that use of
multiple causes of death is required, as also previously reported for myeloproliferative neoplasms. Use of multiple causes
improves estimation of the burden of MDS-related deaths in the population, which enhances the importance of MDS in
planning cancer research and control efforts. Linkages with cancer registries should be conducted to evaluate the accuracy
of data on MDS as a cause of death on death records, for use in interpreting surveillance data on MDS-related mortality.
Key words: anemia, cancer registries, cancer surveillance, leukemia, multiple causes of death, myelodysplastic syndromes
Introduction
Myelodysplastic syndromes (MDS) are a heterogeneous group of clonal myeloid neoplasms, ranging from
refractory anemia with an indolent course to subgroups
with high risk of rapid progression to acute myeloid
leukemia (AML).1,2 MDS is rarely diagnosed in children
and young adults, and risk increases with rising age and is
diagnosed most commonly in elderly persons.1-3 The 3-year
relative survival rate (RSR), or observed survival compared
to survival expected from mortality rates from all causes in
the general US population (taking into account age, gender
and race), was 45% for MDS patients diagnosed in 20012003 in geographic areas covered by the US National Cancer
Institute’s Surveillance, Epidemiology and End Results
(SEER) program.3 Temporal trends in RSRs were not examined because MDS has been reportable to registries only for
diagnoses since 2001.3
Temporal trends in RSRs can be affected by earlier diagnosis of cancer or changes in the distribution of subgroups
that differ in prognosis, whereas declines in cancer mortality
rates in the US population may suggest real improvement
in cancer control.4 Therefore, trends in both RSRs in cancer
patients and trends in cancer mortality rates in the population should be monitored in evaluating progress in cancer
control for specific cancers. In the Annual Report to the
Nation on the Status of Cancer, declines in mortality rates
(such as the recent finding of the first evidence for lung
cancer women) are regarded as important indicators of
progress in cancer control.5
Optimal surveillance of trends in mortality rates,
however, requires accurate estimation of deaths related to
MDS. Routine mortality statistics on cancer are based on the
underlying cause of death, vs all causes of death mentioned
on death certificates (“multiple causes” or “mentions”). For
most cancer sites/types, the difference between numbers of
deaths based on multiple causes vs underlying cause alone
is small (about 10% for all cancers combined).6-8
A recent study in 3 states (California, Colorado
and Idaho) concluded that, in general, restricting cancer
mortality statistics to underlying cause alone will “not
under report cancer mortality statistics.”8 The proportion of
all cancer deaths that were coded as other than the underlying cause was only 10% for all cancers combined, but was
statistically significantly elevated to 20%-30% for several
sites and 95% for Kaposi sarcoma.8 Thus, analyzing all
causes of death may be justified in routine cancer mortality
statistics for certain types of cancer8; however, MDS was not
included in the analyses.8
For myeloproliferative neoplasms (MPN), however,
the US death rate in 2005-2006 based on multiple causes
was about twice as high as that based on underlying
cause alone.9 Cardiovascular diseases, leukemia and various
chronic diseases which are known to be complications of
MPN were coded as the underlying cause when MPN was
mentioned on the same certificate.9 Complications of MDS
(formerly known as preleukemia) include substantial risk
of progression to leukemia, and leukemia could be coded as
the underlying cause of death on death records.
MDS involves anemia, usually macrocytic (ie, with
enlarged red cells). MDS symptoms or complications,
however, also may include other cytopenias (neutropenia
and/or thrombocytopenia). Neutropenia is associated with
__________
a
Retired. Formerly with the Connecticut Tumor Registry, Connecticut Department of Public Health, Hartford, CT.
Address Correspondence to Anthony P. Polednak, PhD. Email: [email protected].
Journal of Registry Management 2011 Volume 38 Number 4
183
increased risk of infection, and thrombocytopenia is associated with increased risk of bleeding (hemorrhage). If
these cytopenias are severe, clinicians recognize that MDS
patients have high morbidity and mortality from infections
and bleeding.10 These complications also may exacerbate
certain other chronic conditions that may be present in MDS
patients, thus contributing to death,11 and could be coded as
the underlying cause (rather than MDS).
The present study used a national database to evaluate
the utility of multiple causes of death in surveillance of
MDS-related deaths in the United States. The goal is to
improve estimation of the true burden of these deaths in the
US population. This could enhance the utility of mortality
surveillance data in cancer epidemiology, cancer control and
planning for research and treatment resources in an “aging”
population. Also discussed is the potential for cancer registries to contribute to future studies assessing the accuracy of
data on MDS-related death derived from death certificates.
Methods
Identification of US Deaths with MDS Coded Anywhere
on the Death Certificate
Deaths were identified among US residents for 2005200612 with International Classification of Diseases Version
10 (ICD-10) code D46, including D46.0 for refractory anemia
(RA) without sideroblasts; D46.1 or RA with sideroblasts;
D46.3 for RA with excess of blasts; D46.3 for RA with excess
blasts with transformation (RAEB-t); D46.4 for RA unspecified; D46.7 for other MDS; and D46.9 for MDS unspecified.
In ICD-10, MDS is coded under “D” for “neoplasms of
uncertain or unknown behavior,” while in the International
Classification of Diseases for Oncology Version 3 (ICD-O-3)
MDS is coded as malignant behavior.3,13 MDS subgroups
differ in prognosis, due in part to the different proportion of myeloblasts (“blasts”) involved and the presence
of absence of certain cytogenetic features. ICD-10 does
not include the subgroup with isolated deletion of the
long arm of chromosome 5, which is coded as an MDS
subgroup in ICD-O-33,13 and has been associated with better
prognosis and (recently) with a specific drug treatment.1,2
Also, RAEB-t is considered obsolete in ICD-O-3, because
AML is defined as 20%+ marrow blasts in ICD-O-3 and in
the World Health Organization classifications of myeloid
neoplasms.14 ICD-10 does not distinguish “therapy-related”
MDS (t-MDS), while ICD-O-3 has a separate Morphology
code for this subgroup.3,13 T-MDS occurs among patients
who had previously received certain chemotherapy agents
or radiotherapy for selected solid cancers and lymphomas.1,2
The latest file included deaths in 2005 and 2006,12 and a
separate file comprised deaths in 1999-2004; all causes were
coded to ICD-10. The Multiple Cause of Death electronic
data file from the National Center for Health Statistics
(NCHS)12 included up to 20 causes per decedent.
The underlying cause is usually listed on part I of the
US standard death certificate, along with other conditions
in the chain of events believed to have resulted in death.
The most accurate data on the underlying cause of death,
based on complex rules, are those on the NCHS electronic
184
mortality files,15 as used in the present study.12 Part II of
the certificate is for any “other significant conditions” that
contributed to death. Analysis of all conditions reported
on the death certificate is especially important for certain
diseases (such as diabetes mellitus) that may be relatively
infrequently coded as the underlying cause but often
contribute to death.15
The role of each specific condition in causing death
may be extremely difficult to discern, and this is a limitation of using certified causes of death. In addition, the
certifying physician or coroner may not be familiar with the
clinical history of the decedent, including the chronological
sequence of events (dates of diagnoses) and clinical complications of all conditions and their treatments, and may not
have (or take) the time to properly complete the certificate.16
This leads to potential errors in the death certification
process.
Death certificate data are used by central cancer registries, as part of case ascertainment efforts, in the “death
certificate clearance” process that results in the eventual
identification of incident cancers that will be coded as
ascertained by “death certificate only” (DCO).15 All causes
of death, not just the underlying cause, coded on death
certificates should be included in the identification of
deaths involving reportable tumors (including MDS) to be
linked to the central registry database to identify tumors
not already reported to the registry, for use in the registry’s
follow-back efforts.15
Analyses and Statistical Methods
Numbers of deaths and death rates were compared
for MDS coded as any cause (multiple causes) vs MDS as
the underlying cause. Age-specific death rates per 100,000
population per year in 2005-2006 were calculated for MDS
in selected age groups.12 Age-standardized rates (ASR)
were adjusted to the age distribution of the US 2000 standard population, and 95% confidence intervals (CI) were
obtained.12 ASRs were compared by gender, race and
Hispanic ethnicity. Statistical significance (p< .05) of the
difference between 2 rates is indicated by 95% CIs that do
not overlap. For deaths in 2005-2006 combined with MDS
coded as other than the underlying cause, the underlying
cause was examined, to assess whether or not these were
consistent with known complications of MDS and/or its
treatment.
Results
In 2005-2006, age-specific death rates from MDS
increased with rising age (Table 1). ASRs were about
twice as high in males than in females, and higher in
whites than in African Americans/blacks or other groups
(Native American and Asian/Pacific Islander), and in nonHispanics than Hispanics (Table 1).
The ratio of the ASR for MDS based on multiple causes
to the ASR based only on the underlying cause was 1.8. A
similar ratio was evident within most categories defined by
age, gender, racial group (ie, those groups with substantial
numbers of deaths), Hispanic ethnicity, and calendar year
(2005 and 2006). Noteworthy was the high proportion (91%)
Journal of Registry Management 2011 Volume 38 Number 4
Table 1. Deaths from Myelodysplastic Syndromes (MDS)a Based on Any Cause of Death (Multiple Causes)b vs Only
the Underlying Cause on Death Certificates of all US-resident Deaths in 2005 and 2006: Age-Specific Rates and Age
Standardized Rates (ASR) per 100,000 per Year
Underlying Cause (UC) Only
No.
Age at death
Multiple Causes (MC)b
Rate (95% CI)
Ratio of Rates
No.
Rate (95% CI)
(MC/UC)
Age-Specific Death Rates for MDS
0-14
12
0.01 (0.01-0.02)
31
0.03 (0.02-0.04)
2.6c
15-24
16
0.02 (0.01-0.03)
31
0.04 (0.03-0.05)
1.9c
25-34
15
0.02 (0.01-0.03)
31
0.04 (0.03-0.06)
2.0c
35-44
55
0.06 (0.05-0.08)
98
0.11 (0.09-0.14)
1.8
45-54
214
0.25 (0.22-0.28)
389
0.45 (0.41-0.50)
1.8
55-64
558
0.90 (0.83-0.98)
1,144
1.85 (1.74-1.95)
2.1
65-74
1,671
4.45 (4.24-4.66)
3,226
8.59 (8.29-8.89)
1.9
75-84
3,950
15.13 (14.66-15.61)
7,280
27.89 (27.25-28.53)
1.8
85+
3,504
33.72 (32.60-34.83)
6,074
58.45 (56.98-59.91)
1.7
Total, ASR
9,995
1.63 (1.59-1.66)
18,304
2.98 (2.94-3.02)
1.8
ASRs for MDS, by Sociodemographic Groups and Calendar Year
Gender
Male
5,611
2.35 (2.28-2.41)
10,460
4.37 (4.28-4.45)
1.9
Female
4,384
1.15 (1.12-1.19)
7,844
2.09 (2.04-2.13)
1.8
Native American
37
1.06 (0.74-1.48)
56
1.61 (1.21-2.11)
1.5
Asian/Pacific Isl.
178
0.95 (0.81-1.09)
330
1.77 (1.58-1.97)
1.9
Black/AA
509
0.99 (0.91-1.08)
919
1.78 (1.66-1.90)
1.8
9,271
1.71 (1.67-1.74)
16,999
3.14 (3.09-3.19)
1.8
340
0.89 (0.79-0.99)
599
1.59 (1.46-1.72)
1.8
9,647
1.67 (1.63-1.70)
17,688
3.07 (3.02-3.11)
1.8
4,813
1.58 (1.53-1.62)
8,953
2.94 (2.88-3.00)
1.9
5,182
1.67 (1.63-1.72)
9,351
3.02 (2.96-3.08)
1.8
1.8
Race-ethnicity
White
Hispanic
d
Not Hispanic
Year
2005
2006
ASRs for MDS by Subgroup of MDS
RA, unspecified
MDS, unspecified
e
233
0.04 (0.03-0.04)
405
0.07 (0.06-0.07)
9,708
1.58 (1.55-1.61)
17,807
2.90 (2.86-2.94)
1.8
International Classification of Diseases Version 10 (ICD-10) code D46. Numbers are for 2005-06 combined; death rates are per year.
“Multiple causes” includes the underlying cause and as many as 20 additional causes from the death certificate as coded in the database used.12
c
Ratio based on rate rounded to 3 decimals.
d
“Race” and Hispanic ethnicity are separate items; Hispanics can be of any “race.” Hispanic ethnicity was not stated for a small number of deaths
(not tabulated).
e
Other specific MDS subgroups were rarely coded (data not tabulated).
CI: Confidence interval (95%).
RA: Refractory anemia.
a
12
b
of deaths at age 65 years or older, for MDS as underlying
cause (9,125/9,995) or as any cause (16,580/18,304). MDS
subgroup was coded as unspecified for 97% of deaths for
MDS as underlying cause or as any cause (Table 1).
For MDS as underlying cause the ASR increased
slightly from 2005 to 2006 (Table 1), but the overall change
was small from 1999 (1.63 per 100,000, 95% CI=1.59-1.68,
data not tabulated) to 2006 (1.67, 95% CI=1.63-1.72, Table
Journal of Registry Management 2011 Volume 38 Number 4
1). For MDS coded as any cause, the ASR increased slightly
from 1999 (2.89 per 100,000, 95% CI=2.82-2.95, data not
tabulated) to 2006 (3.02, 95% CI= 2.96-3.08, Table 1); the two
95% CIs did not overlap.
For the 8,309 deaths in 2005-2006 coded with MDS as
other than the underlying cause, the most common underlying cause was a malignant neoplasm (3,899 or 46.9%), of
which 2,541 (or 65.2% of 3,899) were leukemia, including
185
Table 2. Underlying Cause of Death Coded Among Deaths with Myelodysplastic Syndromes (MDS) (ICD-10 D46) Coded
as Other than the Underlying Cause of Death on Death Certificates for US Residents in 2005-2006 Combined, and AgeStandardize Rate (ASR) per 100,000 per Year
Underlying cause (ICD-10 code or codes)
No.
%a
ASR (95% CI)
Malignant Neoplasms (C00-97)
3,899
46.93
0.64 (0.62-0.66)
Leukemia (C91-95)
(2,541)
(30.58)
0.42 (0.40-0.44)
Acute myeloid (C92.0)
(1,482)
(17.84)
0.25 (0.23-0.26)
Acute, unspecified type (C95.0)
(523)
(6.29)
0.09 (0.08-0.09)
Leukemia unspecified type
(258)
(3.11)
0.04 (0.04-0.05)
Non-Hodgkin lymphoma (C85.9)
(230)
(2.77)
0.04 (0.03-0.04)
Multiple myeloma (C90.0)
(112)
(1.35)
0.02 (0.02-0.02)
Cardiovascular system (I00-99)
2,172
26.14
0.35 (0.33-0.36)
Ischemic heart diseases (I20-25)
(1,120)
(13.48)
0.18 (0.17-0.19)
Other forms of heart disease (I30-510)
(561)
(6.39)
0.09 (0.08-0.10)
Cerebrovascular diseases (I60-69)
(234)
(2.82)
0.04 (0.03-0.04)
Cerebral hemorrhage (I60-62, I69.1-2)
(58)
(0.70)
0.01 (0.01-0.01)
Respiratory (J00-98)
577
6.94
0.09 (0.09-0.11)
Chronic lower respiratory (J40-47)
(372)
(4.48)
0.06 (0.06-0.07)
Digestive system (K00-92)
301
3.62
0.05 (0.04-0.05)
Liver (K70-76)
(113)
(1.36)
0.02 (0.02-0.02)
Infectious, parasitic (A00-B99)
251
3.02
0.04 (0.04-0.05)
Genitourinary (N00-98)
211
2.54
0.03 (0.03-0.04)
Renal failure (N17-19) (134)
(1.61)
0.02 (0.02-0.03)
Blood, blood-forming (D50-89) 161
1.94
0.03 (0.02-0.03)
Anemia, thrombocytopenia, hemorrhagic conditions (D60-64, D69)
(110)
(1.32)
0.12 (0.02-0.02)
Nervous system (G00-98)
156
1.88
0.02 (0.02-0.03)
External causes (Y01-89)
154
1.85
0.03 (0.02-0.03)
Diabetes mellitus (E10-14)
130
1.56
0.02 (0.02-0.02)
8,309
100
1.36 (1.33-1.39)
Total
b
The proportion of all 8,309 deaths. Proportions in parentheses are subgroups of a larger category of cause of death.
The specific causes listed in this table accounted for 8,012 (96.4%) of the 8,309 deaths for the 2 years (2005-2006); the figure of 96.4% is the sum
of the proportions not shown in parentheses in this table. The total of 8,309 deaths is the number of deaths with MDS coded as any cause (18,304)
minus the number (9,995) with MDS coded as underlying cause (ie, as shown in Table 1). ASRs and confidence intervals were rounded to 2 decimals.
a
b
1,482 from AML (Table 2). However, a large proportion of
leukemias were coded as unspecified type (Table 2) and
could actually include additional cases of AML.
Other common underlying causes were cardiovascular diseases, chronic lower respiratory diseases, digestive
(including liver) diseases, infectious diseases, genitourinary
system (including renal failure), and diseases of blood and
blood-forming tissues (Table 2). Blood diseases include
anemias and hemorrhage (Table 2), which are well-known
clinical features of MDS. Cerebral hemorrhage would be
included in the subcategory of cerebrovascular diseases
under the larger category of CVD in ICD-10 (Table 2).
186
Discussion
Underestimation of MDS-Related Deaths in Routine
Cancer Mortality Statistics
The increasing rate of MDS-related death rates with
rising age, and higher ASRs in males vs females, in whites
vs blacks and other racial groups, and in non-Hispanics vs
Hispanics (Table 1), are consistent with incidence data on
MDS.3,13 However, using multiple causes of death results
in much higher ASRs than those based only on the underlying cause, indicating the need to use multiple causes in
assessing the burden of MDS-related deaths in the US population. The ASR for MDS-related deaths based on multiple
Journal of Registry Management 2011 Volume 38 Number 4
causes in the United States was about 3.0 per 100,000 per
year in 2005 and 2006 (Table 1), compared to an estimated
US incidence rate (ASR) of 4.4 per 100,000 per year for 20032007 based on SEER data.3,13
The 1.8 ratio of ASRs based on multiple causes/underlying cause (Table 1) is close to the ratio of 2.0 reported for
MPN mortality (ie, 3,226 deaths in 2005-2006, ASR=1.04 per
100,000 per year, with MPN as any cause, vs 1,645 deaths in
2005-2006, ASR= 0.53, for MPN using only the underlying
cause),9 although larger numbers of deaths and higher ASRs
were involved for MDS than for MPN. In contrast, using the
NCHS Multiple Cause files for 2005-200612 for deaths from
neoplasms combined (ICD-10 codes C00-D48), the ratio of
the ASRs based on multiple causes/underlying cause was
only 1.11 (ie, 206.9/186.8 per 100,000 per year).
Underlying Cause of Death among Deaths with MDS
Coded Elsewhere on the Certificate
Among decedents with MDS coded as other than the
underlying cause, cancers (especially leukemia) were the
most common underlying cause (Table 2). Leukemias that
have arisen by transformation of MDS, as indicated by an
elevated proportion of myoblasts (blast cells) in the bone
marrow, apparently have been coded as the underlying
cause on death certificates that also mention MDS. The
risk of transformation of MDS to leukemia varies by MDS
subgroups, but leukemia (AML) in these patients would
not have arisen without the antecedent condition of MDS.
Therefore, it is important to ascertain these MDS-related
deaths by using multiple causes of death, as also for AML
related to progression (evolution) of a previously diagnosed
MPN.
The majority of MDS cases are classified by clinicians as “de novo” (or “primary”) MDS, but 15%-25%
(depending on the definition and sample size used in the
studies) are therapy-related (t-MDS) or “secondary” MDS
and are associated with a relatively poor prognosis.1,10,17
Chemotherapy (especially with alkylating agents or topoisomerase inhibitors) and radiotherapy for a previous solid
cancer (including breast and lung) or lymphoma have been
associated with elevated risks of MDS (and also AML).1,10,17
Solid cancers or lymphomas may have been certified as the
underlying cause (Table 2) and MDS mentioned elsewhere
on the death certificate.
Among MDS patients in high-risk subgroups, the
cumulative probability of death from leukemia increases
over time after diagnosis to exceed non-leukemic causes,
which include cardiac failure, infection, hemorrhage and
hepatic cirrhosis.18 “High-risk” refers to relatively high
risk for transformation to leukemia and/or lower survival,
based on pathological and cytogenetic features. Death
records cannot be used to identify high-risk subgroups of
MDS, because almost all MDS deaths were coded as unspecified subgroup rather than to a specific MDS subgroup
(Table 1). This suggests lack of clinical information relevant
to MDS subgroups, and/or lack of awareness or interest in
MDS subgroups, among certifiers.
Symptomatic anemia contributes to death (especially
from cardiovascular diseases) in MDS patient as well as
Journal of Registry Management 2011 Volume 38 Number 4
the general population,18 and MDS may exacerbate other
pre-existing chronic diseases (eg, chronic lung diseases).11
Certain chronic diseases were coded as underlying cause
on death records with MDS mentioned (Table 2). These
conditions are also common among all deaths in the United
States, so that the possible role of MDS in contributing to
these deaths (in Table 2) cannot be determined solely from
death records with mention of MDS. However, analysis of
Medicare files for elderly persons newly diagnosed with
MDS in 2003 showed elevated age-adjusted rates of certain
clinical complications within 3 years after MDS diagnosis,
compared with rates in the general Medicare population.19
In addition to the development of myeloid leukemia in 9.6%,
risks for cardiac events, diabetes, dyspnea, hepatic diseases
and infections were significantly elevated for patients with
MDS compared with the general Medicare population.19
Additional studies are needed of other complications
among MDS patients vs other Medicare enrollees. Certain
drugs used to treat iron overload, after red blood cell transfusions in MDS patients, have an uncertain role in acute
renal and hepatic failure, gastrointestinal bleeding and
other complications that could contribute to death.20 Such
complications could conceivably be written anywhere on
the death certificate.
Infectious diseases have been reported as an immediate
cause of death in clinical studies (not using ICD-10 coding
rules) of MDS patients.21 Coding of infectious diseases as the
underlying cause on death certificates with MDS mentioned
(Table 2) may represent exacerbation of infections by MDS,
or the inability of certifiers to identify infections related to
complications of MDS (eg, neutropenia) or its treatment (eg,
blood transfusions). Further understanding of the potential
role of MDS in contributing to the causes of death listed
in Table 2 would require review of medical records and
contacting certifying physicians.
The Need for Continued Surveillance of MDS-Related
Mortality in the US Population
There was no decline in the ASR for all MDS-related
deaths in the US population from 2005 to 2006 (Table 1)
or from 1999 to 2006. US mortality data, however, include
some patients diagnosed and treated in the distant past.
Since May 2004, 3 drugs have been approved by the
Food and Drug Administration (FDA) specifically for use
in MDS patients, although the survival benefits require
further study. Azacitidine and decitabine are demethylating agents, while lenalidomide is an immune-modulating
agent and an analogue of thalidomide; lenalidomide may
be beneficial for patients in the 5q deletion subgroup of
MDS.1,2,22 Previously, therapy (eg, red blood cell or platelet
transfusions and erythropoiesis-stimulating agents) had
been largely supportive, or has involved use of cytotoxic
drugs (as also used for AML) or hematopoietic stem cell
transplants for younger patients with suitable donors.1,2,22
According to surveys in 2005-2007 of samples of US physicians treating MDS patients, small proportions of recently
diagnosed MDS patients had received any of these 3 newer
drugs (highest for azacitidine, at 16%),22 but additional
studies are needed on patterns of care.
187
Continued surveillance of MDS-related deaths is the
US population is needed. Data on US mortality rates (underlying cause only) and on survival rates of patients in SEER
registries, routinely reported by cancer site or type, have not
included MDS , because MDS (reportable only since 2001)
has been excluded from other analyses of cancer trends.13 A
special report on survival (RSRs) of patients diagnosed with
MDS, along with MPN and other hematopoietic cancers, in
SEER and other US cancer registries3 needs to be updated.
Analyses of trends in MDS-related mortality rates in
the population is especially important, because trends in
RSR can be misleading if there were also a trend toward
earlier diagnosis (as shown for other cancers)4 or toward
greater proportion of patients with better prognosis at
diagnosis. For MDS, trends in the distribution of subgroups
that differ in prognosis are difficult to study because of the
large proportions (>50%) of MDS cases coded as unspecified
subgroup in cancer registries.3,13,23,24
The Potential Contribution of Central Cancer Registries
in Assessing the Accuracy of Cancer Mortality Statistics
for MDS-Related Deaths
The accuracy of death-certificate data on MDS is
uncertain. In a project linking death records and cancer
registry databases for 3 states (California, Colorado and
Idaho), the numerator of the concordance rate for cancer site
was the number of persons for whom the cancer site group
(of 79 groups examined) in the registry matched that for the
underlying cause coded on the linked death certificate.25
Confirmation rates were calculated among persons who
died of cancer in 2002-2004 and had been diagnosed with
cancer in 1993-2004, while detection rates were estimated
among persons diagnosed with cancer in 1993-1995 who
died in 1993-2004 with cancer listed anywhere on the death
certificate.25 These rates were almost 90% for leukemia (and
75% for the subgroup of AML), but MDS was not included,
and the study was limited to underlying cause.25 The
substantial numbers of DCO cases, due to lack of followback of potential DCO cases, and patients with multiple
primary cancers were excluded.25
Similar studies should be feasible for MDS, for diagnoses since 2001. Multiple causes of death on death records
should be examined, and patients with multiple primary
cancers coded in the cancer registry should be included.
Patients with MDS recorded in a cancer registry may not
have MDS coded on their death record because the certifier was unaware that leukemia was preceded by MDS, or
that treatment for a solid cancer or lymphoma had been
followed by MDS (which contributed to death).
Many central cancer registries already have periodically linked their databases with death-record files (for
selected calendar years) that include multiple causes of
death, as part of the registry’s “death clearance” process.15
Also, the Data Management System being adopted by
SEER registries26 includes data items (ICD-10 codes) for
multiple causes of death for each patient in the registry.
Thus, although only the underlying cause of death has been
included in the NAACCR record format,15 multiple causes
should be available in the databases of some individual
188
registries for collaborative studies.
Potential Limitations of MDS Data in Central Cancer
Registries
Although coding of cancer site or type is likely to be
much more accurate and specific in cancer registries, which
use hospital records and pathology reports, than in death
records, registry data on MDS may be incomplete due to
under-ascertainment of diagnosed MDS by central cancer
registries3 and the existence of undiagnosed MDS patients
in the population.
In a study in western Washington State, the ASR for
MDS in 2005-2006 based on data in the SEER registry was
close to the ASR estimated for the population of a local
health-care plan based that included a review of medical
charts of patients with ICD-9 code 238.7 (ie, neoplasm of
uncertain behavior in other lymphatic and hematopoietic
tissue) in the plan’s database.27 The findings suggested
nearly complete reporting of probable or definite MDS cases
to the SEER registry.27 Also identified, however, were symptomatic “possible” MDS cases, defined as patients with an
ICD-9 code 238.7 and a medical chart mentioning suspected
MDS that was never definitively ruled out.27 In the event
(albeit unlikely) that all of these cases were MDS, the
incidence of MDS would have increased by 46%.27 Similar
studies are needed in other geographic areas, and should
also include linkage to death records.
Bone-marrow (aspirate and/or biopsy) tests for elderly
patients with suspected MDS27 or with unexplained anemia
(which may contribute to death)28 may be limited because
definitive diagnosis would not have affected treatment
decisions.27 The recent approval of new drugs for MDS,
however, offers promise for improved survival and the use
of potentially curative allogeneic hematopoietic stem-cell
transplants for elderly MDS patients may be increasing.29
Clinicians have suggested that the lack of diagnostic testing
for MDS in patients with unexplained cytopenias and/
or macrocytosis may deprive some patients of access to
effective treatments for MDS.30 These developments may
encourage more diagnostic testing (including cytogenetics
of bone-marrow cells) useful in the differential diagnosis of
MDS,14 resulting in increased detection of MDS.
Conclusion
Using multiple causes of death on records in cancer
mortality surveillance is necessary to estimate the true
burden of deaths related to MDS, in view of the large
numbers of deaths with MDS coded as other than the
underlying cause that is used in routine mortality statistics.
Thus, MDS should be included with a small group of other
cancers that includes MPN. It is important to include the
minority of MDS-related deaths that involve “treatmentrelated” MDS. Resources must be planned for dealing with
MDS in the growing numbers of long-term survivors who
have been treated with chemotherapy and/or radiotherapy
for certain common solid tumors and lymphomas.
In assessing the accuracy of surveillance of routine
mortality data from MDS, along with MPN, cancer registries can contribute through linkages of their databases with
Journal of Registry Management 2011 Volume 38 Number 4
death records for the population covered by the registries,
as already shown for other cancers.8,25
With anticipated future increases in numbers of
cancers in an “aging” population,5 accurate estimates of
MDS-related morbidity and mortality in the US population
are needed in order to avoid underestimating the importance of MDS, in prioritizing or planning for research on
cancer causes and treatment (including clinical trials) and
in estimating the costs to society for treatment of MDS.19,31,32
References
1. Sekeres MA. The epidemiology of myelodysplastic syndromes. Hematol
Oncol Clin N Am. 2010;24:287-294.
2. Kantarjian H, O’Brien S, Cortes J, et al. Therapeutic advances in
leukemia and myelodysplastic syndrome over the past 40 years. Cancer.
2008;113(7 suppl):1933-1952.
3. Rollison DE, Howlader N, Smith MT, et al. Epidemiology of myelodysplastic syndromes and chronic myeloproliferative disorders in the
United States, 2001-2004, using data from the NAACCR and SEER
programs. Blood. 2008;112:45-52.
4. Welch HG, Schwartz LM, Woloshin S. Are increasing 5-year survival
rates evidence of success against cancer? JAMA. 2000;283:2975-2978.
5. Kohler BA, Ward E, McCarthy BJ, et al. Annual report to the nation on
the status of cancer, 1975-2007, featuring tumors of the brain and other
nervous system. J Natl Cancer Inst. 2011;103:1-23.
6. Steenland K, Nowlin S, Ryan B, Adams S. Use of multiple-cause
mortality data in epidemiologic analyses: US rate and proportion files
developed by the National Institute for Occupational Safety and Health
and the National Cancer Institute. Am J Epidemiol. 1992;136:855-862.
7. Goldacre MJ, Duncan ME, Cook-Mozaffari P, Griffith M. Trend in
mortality for cancers, comparing multiple- and underlying-cause rates,
in an English population 1979-1999. Br J Cancer. 2004;90:1019-1021.
8. Fink AK, German RR, Heron M, et al. Impact of using multiple
causes of death codes to compute site-specific, death certificate-based
cancer mortality statistics in the United States. Cancer Epidemiol.
2012;36:22-28.
9. Polednak AP. U.S. death rates from myeloproliferative neoplasms, and
implications for cancer surveillance. J Registry Manage. 2011;38:87-92.
10.Liesveld JL, Lichman MA. Chapter 88. Myelodysplastic syndromes. In
Lichtman MA, Kipps TJ, Seligsohn U, et al. Williams Hematology, 8e.
McGraw Hill, 2010.
11.Wang R, Gross CP, Halene S, Ma X. Comorbidities and survival in a large
cohort of patients with newly diagnosed myelodysplastic syndromes.
Leuk Res. 2009;33:1594-1598.
12.Centers for Disease Control and Prevention. National Center for Health
Statistics. Multiple cause of death file 2005-2006. CDC WONDER
on-line database, compiled from multiple cause of death file 2005-2006
Series 20 No. 2L, 2009. Available at: http://wonder.cdc.gov/mcd-icd10.
html.
13.Howlader N, Noone AK, Krapcho M, et al, eds. SEER Cancer Statistics
Review, 1975-2008. National Cancer Institute, Bethesda MD. Based on
the November 2010 SEER data submission posted to the SEER website,
2011. Available at: http://seer.cancer.gov/csr/1975_2008.
14.Vardiman JW, Thiele J, Arber DA, et al. The 2008 revision of the World
Health Organization (WHO) classification of myeloid neoplasms
and acute leukemia: Rationale and important changes. Blood.
2009;114:937-951.
Journal of Registry Management 2011 Volume 38 Number 4
15.North American Association of Central Cancer Registries (NAACCR).
NAACCR death clearance best practices working group, editors. Death
clearance manual. Springfield, IL: NAACCR; 2009.
16.Remington PL, Goodman RA. Chronic disease surveillance. Chapter
3, in Brownson RC, Remington PL, Davis JR, eds. Chronic Disease
Epidemiology and Control. Washington D, American Public Health
Association. 1998;55-76.
17.DeRoos AJ, Deeg HJ, Davis S. A population-based study of survival
in patients with secondary myelodysplastic syndromes (MDS): Impact
of type and treatment of primary cancers. Cancer Causes Control.
2007;18:1199-1208.
18.Della Porta MG, Malcovati L. Clinical relevance of extra-hematologic
comorbidity in the management of patients with myelodysplastic
syndrome. Haematologica. 2009;94:602-606.
19.Goldberg SL, Chen E, Corral M, et al. Incidence and clinical complications of myelodysplastic syndromes among United States Medicare
beneficiaries. J Clin Oncol. 2010;2847-2852.
20.Greenberg PL, Attar E, Bennett JM, et al. Myelodysplastic syndromes.
Clinical practice guidelines in oncology. J Natl Compr Cancer Netw.
2011;9:30-56.
21.Dayyani F, Conley AP, Strom SS, et al. Cause of death in patients with
lower-risk myelodysplastic syndrome. Cancer. 2010;116:2174-2179.
22.Sekeres MA, Schoonen M, Kanatarjian H, et al. Characteristics of US
patients with myelodysplastic syndromes: Results of six cross-sectional
physician surveys. J Natl Cancer Inst. 2008;100:1542-1551.
23.Ma X, Does M, Raza A, Mayne ST. Myelodysplastic syndromes: Incidence
and survival in the United States. Cancer. 2007;109:1536-1542.
24.Komrokji RS, Matacia-Murphy GM, Al Ali NH, et al. Outcome of patients
with myelodysplastic syndromes in the Veterans Administration population. Leuk Res. 2010;34:59-62.
25.German RR, Fink AK, Heron M, et al. The accuracy of cancer mortality
statistics based on death certificates in the United States. Cancer
Epidemiol. 2011;35:126-131.
26.National Cancer Institute. Surveillance, Epidemiology, and End Results
(SEER) Program. SEER data management system. SEER*DMS user manual
and tutorials. Available at: http://seer.cancer.gov/seerdms.
27.DeRoos AJ, Deeg HJ, Ornstad L, et al. Incidence of myelodysplastic
syndromes within a nonprofit healthcare system in western Washington
state, 2005-2006. Am J Hematol. 2010;765-770.
28.Guralnick JM, Eisenstaedt RS, Ferrucci L, Klein HG, Woodman RC.
Prevalence of anemia in persons 65 years and older in the United
States: Evidence for a high rate of unexplained anemia. Blood.
2004;104:2263-2268.
29.Kelsey JH. The role of allogeneic-cell transplantation in leukemia. N Engl
J Med. 2010;363:2158-2159.
30.Rauw J, Wells RA, Reis M, Zhang L, Buckstein R. Validation of a
scoring system to establish the probability of myelodysplastic syndrome
in patient with unexplained cytopenias or macrocytosis. Leuk Res.
2011;35:1335-1338.
31.Greenberg PL, Coster LE, Ferro SA, Lyman GH. The costs of drugs used to
treat myelodysplastic syndromes following the National Comprehensive
Cancer Network guidelines. J Natl Compr Canc Netw. 2008;6:942-953.
32.Tefferi A. Myelodysplastic syndromes – Many new drugs, little therapeutic progress. Mayo Clin Proc. 2010;85:1042-1045.
189
Original Article
Using NAPIIA to Improve the Accuracy of
Asian Race Codes in Registry Data
Mei-Chin Hsieh MSPH, CTRa; Lisa A. Pareti, BS, RHIT, CTRb; Vivien W. Chen, PhDa
Abstract: Background: Misclassification of race/ethnicity, particularly for Asians and American Indians, has been an issue
existing in cancer registry data for years. Over the past 10 years, the Asian population has increased noticeably in both
the US and in Louisiana. Therefore, accurate recording of Asian races/ethnicities in cancer registry databases has become
essential for disparity research. The objectives of this study were to demonstrate that using the North American Association
of Central Cancer Registries (NAACCR) Asian/Pacific Islander Identification Algorithm (NAPIIA) could improve the
coding accuracy of Asian ethnicities and to identify sources for manually verifying race/ethnicity. Methods: We selected
cases diagnosed in years 1995 to 2008 with first race (NAACCR item 160) coded to any Asians, other race, unknown race,
or non-Asian race with birthplace in an Asian country. We then converted these races to Asian, Not Otherwise Specified
(Asian NOS) race code 96 and applied NAPIIA on the records. The resultant Asian races/ethnicities assigned by NAPIIA
were then compared to the original race. When the NAPIIA-assigned Asian codes were different from the original race,
the cases were manually reviewed. Kappa statistic test was used to measure the interobserver agreement; sensitivity and
positive predictive value (PPV) were used to assess the degree of discrepancy for each Asian racial/ethnic subgroup separately. Results: Of 2,147 cases run through the NAPIIA, 22.3% (479) were identified with coding discrepancies. Overall, the
agreement on Asian subgroups between the original and NAPIIA-assigned was almost perfect (Kappa = 0.8682). When
NAPIIA-assigned race and manually reviewed race were compared, the Vietnamese subgroup had the highest consistent
rate (95%). Of the 237 cases where the original race was coded to Asian NOS, 93.7% were verified as having a more specific
race/ethnicity. Slightly over 98% of deceased patients found in Louisiana online death certificate database had specific
race/ethnicity information. Conclusions: NAPIIA is an excellent tool to assist cancer registries in improving the coding accuracy of Asian subgroups and enhancing the data quality by reducing cases with Asian NOS and unknown race.
The death certificate is a great source for identifying and/or verifying race/ethnicity based on several factors including
patient’s race code and place of birth as well as the parent’s names and place of birth.
Key words: Asians, race, ethnicity, misclassification, data quality
Introduction
The Asian population (Asian alone only) has increased
43.3% between 2000 and 2010 (10.2 million [3.6%] to 14.7
million [4.8%]) in United States and has increased 28.1%
in Louisiana.1,2 According to the US Census 2000, the top
3 Asian subgroups in the US are Chinese, Filipino and
Asian Indian.3 In Louisiana, the distribution of the Asian
subgroups differs with the US; 44.5% of the Asian population was Vietnamese, followed by Asian Indian (15.1%) and
Chinese (13.6%).4
Although Asians have lower incidence rates from all
cancers combined than whites and blacks for both males
and female, Asians have highest incidence rates for certain
cancers such as stomach and liver cancers.5 Among Asian
ethnicities, Koreans had the highest incidence and mortality
rates from stomach cancer while Vietnamese had the
highest incidence and mortality rates from liver cancer.6,7
Study comparing self-reported race/ethnicity with race/
ethnicity recorded in cancer registry data revealed that
Asian subgroups had a higher misclassification of race
than whites and blacks, particularly for Vietnamese.8 Issues
related to the misclassification of Asian subgroups in central
cancer registries, such as miscoding or code transposition,
was described in Boscoe’s study.9
With the increasing Asian population in both the US
and Louisiana, the recording accuracy of Asian race ethnicity
codes by registries has become more essential for research
on cancer disparities. Such need has led the North American
Association of Central Cancer Registries (NAACCR) to form
the Race and Ethnicity Work Group. The Work Group developed an Asian/Pacific Islander Identification Algorithm
(NAPIIA)10 to classify cases directly or indirectly as Asian/
Pacific Islander for analysis purposes. The specific aims of
our study were: (1) to study the utility of this algorithm in
improving the coding accuracy of Asian race/ethnicity in
the Louisiana cancer registry data as well as reducing Asian
__________
Louisiana Tumor Registry and Epidemiology Program, School of Public Health, Louisiana State University Health Sciences Center. bLouisiana Tumor Registry,
School of Public Health, Louisiana State University Health Sciences Center.
a
Address correspondence to Mei-Chin Hsieh, MSPH, CTR, Louisiana Tumor Registry, School of Public Health, Louisiana State University Health Sciences
Center—New Orleans, 2020 Gravier St., Third Floor, New Orleans, LA 70112. Telephone: (504) 568-5850. Fax: (504) 568-5800. Email: [email protected].
Acknowledgement: The authors would like to thank Louisiana’s hospital, regional, and central registrars for their diligence in quality cancer data collection.
This work was supported in part by LSU Health Sciences Center—New Orleans, the Centers for Disease Control and Prevention under cooperative agreement
number 5U58DP000769, and the National Cancer Institute‘s contract number N01-PC-2010-00030.
190
Journal of Registry Management 2011 Volume 38 Number 4
Table 1. Race Consistency Comparison after Applied NAPIIA on Original Race/Ethnicity, and Agreement on Original
Asian Race/Ethnicities (Reference Standard) vs NAPIIA-assigned Asian Race/Ethnicity (1,093 cases) Using Sensitivity and
Positive Predictive Value (PPV), Louisiana 1995-2008
Consistent Race Code
Different Race Codes
Keep as Original Race†
Count
%
Count
%
Count
%
Total
Sensitivity
(95% CI‡)
Positive Predictive
Value (95% CI‡)
White§
NA
NA
63
93
5
7
68
~
~
Black
NA
NA
4
100
0
0
4
~
~
Chinese
106
69
16
10
31
20
153
89.5 (83.6-93.9)
86.7 (80.4-91.6)
Japanese
53
67
10
13
16
20
79
87.3 (78.0-93.8)
89.6 (80.6-95.4)
Filipino
63
70
2
2
25
28
90
97.8 (92.2-99.7)
80.7 (72.1-87.7)
Korean
30
71
6
14
6
14
42
85.7 (71.5-94.6)
78.3 (63.6-89.1)
Vietnamese
403
90
21
5
23
5
447
95.3 (92.9-97.1)
91.2 (88.3-93.6)
Asian Indian
96
40
47
20
97
40
240
80.4 (74.8-85.2)
98.0 (94.8-99.4)
Other Asians#
5
12
6
14
31
74
42
85.7 (71.5-94.6)
92.3 (79.1-98.4)
Asian NOS*
NA
NA
237
70
104
30
341
~
~
Unknown
NA
NA
67
10
574
90
641
~
~
Original
Race/Ethnicity
§
†The original race was kept in the NAPIIA-assigned race field when it could not be assigned by NAPIIA.
‡95% CI = 95% confidence interval.
§Non-Asian race/ethnicity with birthplace in Asian country.
~ Sensitivity and PPV were not conducted.
# Other Asians include Laotian, Hmong, Kampuchean, and Thai.
*Asian NOS=Asian, Not Otherwise Specified.
NOS and unknown race rates, and (2) to identify alternate
data sources to be used for the verification of race/ethnicity
codes.
Data and Methods
Cancer cases diagnosed in years 1995 to 2008 with
the first race (NAACCR item 160)11 coded to any Asians,
other race, unknown race, or non-Asian race with birthplace in Asian country were obtained from the Louisiana
Tumor Registry (LTR), a statewide population-based cancer
registry since 1988 and a registry of the National Cancer
Institute’s Surveillance, Epidemiology and End Results (NCI
SEER) Program and the Centers for Disease Control and
Prevention’s (CDC) National Program of Cancer Registries
(NPCR). As such, the LTR have consistently met the data
quality standards of these funding agencies. In addition,
the LTR data have met the high-quality data requirements
of NAACCR and have been certified every year since 1999
as well as being included in numerous cancer data files and
monographs.
For patients with multiple primaries, only 1 primary
was selected for this analysis. All race codes mentioned
Journal of Registry Management 2011 Volume 38 Number 4
above were converted to code 96, Asian, Not Otherwise
Specified (Asian NOS), and NAPIIA version 1.2.110 was
applied to the records to reassign race/ethnicity (the
SAS code of the conversion is available online at http://
www.naaccr.org/Research/DataAnalysisTools.aspx). The
NAPIIA (version 1.2.1)10 includes 2 components, direct
identification and indirect identification. Race codes not
equal to 96 (Asian, NOS) and 97 (Pacific Islander, NOS)
will be directly coded to the original race; otherwise,
the indirect identification will be applied. The indirect
identification algorithm is based first on birthplace, then
surname (except for female where maiden name takes
precedence) and lastly first name. The name lists used in
the indirect identification were obtained from 3 different
sources: the US Census,12 Lauderdale-Kestenbaum list,13 and
listings provided by 7 registries participated in the development of the NAPIIA algorithm. Patients with birthplace in
either Central and South America, Spain or Asian countries (specifically Maldives, Nepal, Bhutan, Bangladesh,
Sri Lanka, Myanmar/Burma, Malaysia, Singapore, Brunei,
Indonesia, Tibet, and Mongolia) were excluded from indirect identification for Asian race/ethnicity.10
191
Figure 1. Comparison of Manually Reviewed Race/Ethnicity
and NAPIIA-Assigned Race/Ethnicity Among 479 Reviewed
Cases, Louisiana 1995-2008
Figure 2. Percent Change of Asian Race/Ethnicity Subgroups
and Unknown Race after Review of 479 Cases with
Inconsistent Races, Louisiana 1995-2008
NAPIIA Assigned Asian Ethnicity (Count)
#Other Asians include Laotian, Hmong, Kampuchean, and Thai.
#
% Change
50.0
#Other Asians include Laotian, Hmong, Kampuchean, and Thai.
Table 2. Frequency Distributions of Original Race/Ethnicity by Manually Reviewed Race/Ethnicity among 479 Reviewed
Cases, Louisiana 1995-2008
White
Black
American
Indian
Chinese
Japanese
Filipino
Korean
Asian Indian/
Pakistani
Vietnamese
Other Asians#
Asian NOS*
Unknown
Total
Reviewed Race/Ethnicity
White
22
0
0
5
3
11
1
12
7
2
0
0
63
Black
0
3
0
0
0
1
0
0
0
0
0
0
4
Chinese
2
0
0
1
3
1
1
1
7
0
0
0
16
Japanese
0
0
0
1
2
0
1
1
4
0
1
0
10
Filipino
0
0
0
0
0
0
0
0
1
0
1
0
2
Korean
0
0
0
0
1
0
0
1
2
2
0
0
6
Asian Indian/ Pakistani
4
3
1
3
2
3
1
2
24
0
5
1
47
Vietnamese
10
0
0
5
0
0
4
0
7
1
1
1
21
Other Asians#
1
1
0
1
0
0
0
0
0
2
1
0
6
Asian, NOS
7
2
0
53
20
10
19
15
93
3
15
0
237
Unknown
43
8
0
4
1
1
0
7
0
0
0
3
67
Total
81
15
1
73
32
27
27
39
145
10
24
5
479
Original Race/Ethnicity
#Other Asians include Laotian, Hmong, Kampuchean, and Thai.
*Asian NOS= Asian, Not Otherwise Specified.
The new Asian race/ethnicity codes assigned by
NAPIIA were then compared to the original race codes;
discrepant cases were manually reviewed. This also included
unknown race which was assigned to a more specific Asian
race/ethnicity by NAPIIA. Because of very low case counts
for Laotian, Hmong, Kampuchean, and Thai, these Asian
ethnicities were aggregated into 1 group when presenting
the results. This study did not involve direct patient contact
and was IRB exempt.
192
Data sources utilized for manual review included
abstract text in the LTR database, online medical records,
death certificate database, and Voter Registration via
LexisNexis Accurint. As part of the LTR’s data quality
standards, we required all registry abstracts to include
race/ethnicity text to substantiate all codes including race/
ethnicity fields. In addition, electronic medical records for
Louisiana’s public hospitals and online death certificates
for Louisiana residents were accessible to the LTR staff. We
Journal of Registry Management 2011 Volume 38 Number 4
also utilized information from Voter Registration through
LexisNexis Accurint, a commercial vendor, on a fee basis.
Supporting evidence for verifying race included race documented on these data sources, birthplace, ethnicity and/
or birthplace and last name of the patients’ parents (both
mother and father) as documented on their death certificate.
If either one of the parents indicated a specific Asian race/
ethnicity the corresponding race was coded. The priorities
for coding multiracial patients followed the coding rules
documented in the SEER Program Coding and Staging Manual
2010.14 If a patient’s parents had different Asian races, the
mother’s race was used to code the first race and the father’s
race was used to code the second race. For patients whose
race could not be identified through research sources, the
original race coded on abstract was kept.
We used Kappa statistic test to measure the interobserver agreement15,16 between original Asian race/ethnicity
and NAPIIA-assigned Asian race/ethnicity on cases with
specific Asian race/ethnicity coded in the original race
field. The strength of agreement was based on the range of
Kappa values categorizing into: almost perfect (0.81-1.00),
substantial (0.61-0.80), moderate (0.41-0.60), fair (0.21-.040),
slight (0.00-0.20), and poor agreement (<0.00).17 In addition, sensitivity and positive predictive value (PPV) based
on original Asian race/ethnicity (as the reference standard) verses NAPIIA-assigned Asian race/ethnicity were
computed separately to assess the degree of discrepancy for
each Asian racial/ethnic subgroup. All data analyses were
performed using SAS statistical software version 9.2 (SAS
Institute, Inc., Cary, North Carolina).
Results
We identified 2,147 eligible cases diagnosed between
1995 and 2008 from the LTR database; there were 1,093
(50.9%) cases with specific Asian race/ethnicity, 341 (15.9%)
cases with Asian NOS, 641 (29.9%) unknown race cases, and
72 (3.4%) non-Asian patients with birthplace in an Asian
country (Table 1). After NAPIIA was applied, 479 (22.3%)
cases were identified with racial discrepancies between
the original races/ethnicities and NAPIIA-assigned races/
ethnicities; the majority (49.5%) was originally coded to
Asian NOS.
Comparison of Original Asian Race/Ethnicity with
NAPIIA-assigned Asian Race/Ethnicity on cases with
Specific Asian Race/Ethnicity (N=1,093)
Overall, the agreement test between the original Asian
race/ethnicity and NAPIIA-assigned Asian race/ethnicity
was almost perfect (Kappa = 0.8682). Among Asian racial/
ethnic subgroups, Chinese and Japanese had comparable
sensitivity and PPV, about 87% to 89% (Table 1). Vietnamese
had very high percentage in both sensitivity and PPV.
Patient originally coded as Vietnamese in the LTR database
95% would likely be coded as a Vietnamese by NAPIIA and
a patient assigned as a Vietnamese by NAPIIA had 91%
chance coded to Vietnamese in original race code. Filipino
had very high sensitivity (97.8%), but lower PPV (80.7%),
whereas Asian Indian had sensitivity much lower than PPV
(80.4% and 98.0%, respectively).
Journal of Registry Management 2011 Volume 38 Number 4
Figure 3. Proportions of Specific Race/Ethnicity
Information Obtained from Different Sources Among 479
Reviewed Cases, Louisiana 1995-2008
Abstract
text (479)
Online
Medical
Records (48)
Voter
Registration
(162)
Online Death
Certificate
(182)
Race/Ethnicity Comparison of Manually Reviewed with
NAPIIA-assigned and Original Code among Cases with
Inconsistent Race Codes (N=479)
When the 479 cases with inconsistent race codes
(NAPII-assigned and original codes) were reviewed, 333
(69.5%) were determined to be the same race code as the
NAPIIA-assigned code. Vietnamese had the highest consistency; 95% of Vietnamese assigned by NAPIIA remained as
Vietnamese (Figure 1). Filipino had the lowest consistent
rate between NAPIIA-assigned and manually reviewed
race/ethnicity; among 98 NAPIIA-assigned Filipinos, 51
patients were actually white (52.0%).
When the original race/ethnicity and manually
reviewed race/ethnicity were compared, 41 out of 63
(65.0%) originally coded white were Asian; 10 out of 21
(47.6%) originally coded Vietnamese were white; and 24 out
of 47 (51.1%) Asian Indians were Vietnamese (Table 2). We
verified 222 cases (93.7%) from 237 Asian NOS and 64 cases
(95.5%) from 67 unknown races with a more specific race/
ethnicity.
Percent of Changes for Asian Racial/Ethnic Group and
Unknown Race
After manually reviewing the inconsistent race/
ethnicity cases, there is an increase in number for most of
the Asian racial/ethnic subgroups except for Asian Indian.
Korean had the highest increase (50%) followed by Chinese
(37%) and Filipino (32%) (Figure 2). The Asian NOS rate
was reduced by almost two thirds and unknown race was
reduced about 10%.
Sources for Verifying Race/Ethnicity:
Figure 3 shows the proportions of race information
obtained from different sources among the 479 manually
reviewed cases. Over three quarters of the reviewed cases
lacked documented race information within the abstract
text. Only 48 cases were found using online medical records;
among those only 11 cases (23%) had a specific race identified. About 43% of cases found in the voter registration
had a specific race. For most of the deceased cases found in
193
Louisiana’s online death certificate database, we were able
to identify specific race/ethnicity.
Discussion
Using these data sources we were able to verify 450 cases
with correct race. About 10% of unknown race and 65% of
Asian NOS were coded to a more specific race among cases
diagnosed from 1995 and 2008. NAPIIA was able to more
accurately identify Vietnamese race group as compared
with other Asian racial/ethnic groups. In contrast, Filipino
race code had the least improved accuracy among all race
groups, because of their Spanish last name. Previous study
self-reported ethnicity and ethnicity recorded in a Health
Maintenance Organization (HMO) found Filipinos were
mostly likely to be classified as non-Asian.18 Similar with
Boscoe’s finding,9 we found that miscoding was one of the
main reasons for misclassifying race; other reasons included
code transposition and coding multiple races incorrectly.
Although miscoding was evident across all race/ethnicities, it was most prevalent in the Asian subgroups between
Asian Indian/Pakistani and Vietnamese. Before NAACCR
version 1211 was released, there was only one code, 09, used
to code Asian Indian/Pakistani. Since Vietnamese (race
code: 10) and Asian Indian are the top 2 Asian subgroups in
Louisiana, this may result in higher miscoding rates among
these 2 groups. Race code transposition was also observed
between whites (race code: 01) and Vietnamese (race code:
10). About 50% of reviewed Vietnamese were actually
white. Patient with multiple races was another factor that
caused incorrect race coding, especially in the first race
field. This was likely caused by not following the SEER race
coding guidelines.14
The reasons for misclassifying race/ethnicities or
coding Asian to Not Otherwise Specified (NOS) described
above were mainly caused by manual coding errors, limited
racial/ethnic coding options and/or limited race information in the medical record preventing more specific
Asian ethnicity coding. The accuracy of self-reported race/
ethnicity was another reason that caused misclassification.8,19
A previous study using Veterans Affairs (VA) administrative
files found that patients who were less educated, nonsolitary living, younger, having sufficient food, and using
more inpatient VA healthcare services tended to have better
agreement on race/ethnicity between administrative data
and the patients’ self-reported race data.19
Most of the sources used to verify race in our study do
not provide specific Asian subgroup information. Except
for white, black, and/or Hispanic, most of the Asian races
are aggregated to Asian Not Otherwise Specified or Asian/
Pacific Islander only. Louisiana’s online death certificate
database is the best source for identifying and verifying
race/ethnicity, it not only provides a specific race group
for the deceased, but also provides birthplace information
for both the deceased and the deceased’s parents, as well
as the parents’ first and last names. Although the death
certificate is a great source, it only applies to deceased cases
and therefore can introduce bias when comparing incidence
and mortality rates among specific race/ethnic groups. For
example, if incident cases are coded to Asian, NOS while
194
deceased cases are coded to more specific Asian codes, it
may lead to a higher mortality rate for the specific Asian
subgroups.
The original medical record remains the most important source of race/ethnicity. Usually the race/ethnicity
is documented and/or described in an admission Face
Sheet/Registration Form, and/or the History and Physical
(H&P) section of the medical record. Consultation notes
including Medical and Radiation oncology notes as well as
the Discharge Summary may also contain race/ethnicity
descriptions. While the Face Sheet/Registration Form
contains mainly self-reported race data, the other medical
records rely on the physician’s description of race/ethnicity.
With the increased need of Asian race/ethnicity for cancer
disparity research, more specific race /ethnicity descriptions in the medical record can decrease the Asian NOS rate.
Abstractors also need to carefully read through the patient’s
records to find race information when documented and
be trained to properly code specific race/ethnicity on the
cancer abstract based on SEER race coding rules.14
To decrease the race/ethnicity misclassification rate
from routine data collection, hospital and field abstractors
need to: (1) double check race codes to make sure they code
what they intend; (2) document the race information in
the text field, preferably in physical exam (PE) text, if race
is known; (3) correctly spell patient’s last and first names
as well as maiden name if female; (4) document and code
patient’s birthplace if known. Central Registries need to:
(1) make sure the corresponding NAACCR race code is
coded if race information is obtained from death certificate
or other sources; (2) collect birthplace information when
available which can improve the NAPIIA’s performance;
(3) follow SEER race coding rules14 to code the priority
of multiple races and priority order of multiple sources.
When race is reported differently by 2 or more sources then
self-declared race identification has priority over documentation in medical record and death certificate.14 The LTR has
adopted these recommendations in our registry operations.
In summary, we found that NAPIIA is an excellent
tool to assist central registries in improving the coding
accuracy of Asian subgroups, particularly for identifying
specific Asian ethnicities among those races originally
coded to Asian NOS. NAPIIA could also be applied to race
codes other than Asians to enhance registry data quality.
As a result of these findings, the Louisiana Tumor Registry
implements this methodology into its routine data quality
procedure to ensure Asian races are coded correctly. Any
discrepancies identified between NAPIIA-assigned and
original race codes are required to manually review as well
as any incoming cases with multiple races.
References
1. Humes KR, Jones NA, Ramirez RR. Overview of race and Hispanic
Origin: 2010. Census 2010 Briefs, C2010BR. Washington, DC: US
Census Bureau; March 2011.
2. 2010 Census Data. Available at: http://2010.census.gov/2010census/
data/index.php. Accessed April 11, 2011.
3. Reeves TJ, Bennett CE. We the people: Asians in the United States.
Census 2000 Special Reports, CENSR-17. Washington, DC: US Census
Bureau; December 2004.
Journal of Registry Management 2011 Volume 38 Number 4
4. LA Census 2000 profile. Available at: http://www.census.gov/
prod/2002pubs/c2kprof00-la.pdf. Accessed April 11, 2011.
5. Miller BA, Kolonel LN, Bernstein L, et al. (eds). Racial/ethnic patterns of
cancer in the United States 1988-1992, National Cancer Institute. NIH
Pub. No. 96-4104. Bethesda, MD; 1996.
6. Kwong SL, Chen MS Jr, Snipes KP, et al. Asian subgroups and cancer
incidence and mortality rates in California. Cancer. 2005;104(12 Suppl):
2975-2981.
7. McCracken M, Olsen M, Chen MS, et al. Cancer incidence, mortality,
and associated risk factors among Asian Americans of Chinese, Filipino,
Vietnamese, Korean, and Japanese ethnicities. CA Cancer J Clin.
2007;57(4):190-205.
8. Gomez SL, Glaser SL. Misclassification of race/ethnicity in a populationbased cancer registry (United States). Cancer Causes and Control.
2006;17:771-781.
9. Boscoe FP. Issues with the coding of Asian race in Central Cancer
Registries. J Registry Manage. 2008;34(4):135-139.
10.NAACCR Race and Ethnicity Work Group. NAACCR Asian Pacific
Islander Identification Algorithm [NAPIIA v1.2.1]. Springfield, IL: North
American Association of Central Cancer Registries, September 2010.
Available at: http://www.naaccr.org/LinkClick.aspx?fileticket=3HnBhl
mhkBs%3d&tabid=92&mid=432.
11.Thornton M, O‘Connor L, eds. Standards for Cancer Registries Volume
II: Data Standards and Data Dictionary, Record Layout Version 12, 14th
Journal of Registry Management 2011 Volume 38 Number 4
ed. Springfield, IL.: North American Association of Central Cancer
Registries, February 2009, rev. August 2009.
12.Falkenstein MR. The Asian and Pacific Islander surname list as developed
from Census 2000. In Joint Statistical Meeting, New York, 2002.
13.Lauderdale DS, Kestenbaum B. Asian American ethnic identification by
surname. Population Research and Policy Review. 2000;19:283-300.
14.Adamo MB, Johnson CH, Ruhl JL, Dickie LA, eds. 2010 SEER Program
Coding and Staging Manual. National Cancer Institute, NIH Publication
number 10-5581, Bethesda, MD.
15.Cohen J. A coefficient of agreement for nominal scales. Edu Psychol
Meas. 1960;20:37-46.
16.Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa
statistic. Fam Med. 2005;37(5):360-363
17.Landis JR, Koch GG. The measurement of observer agreement for
categorical data. Biometrics. 1977;33:159-174.
18.Gomez SL, Kelsey JL, Glaser SL, et al. Inconsistencies between selfreported ethnicity and ethnicity recorded in a Health Maintenance
Organization. Ann Epidemiol. 2005;15:71-79.
19.Kressin NR, Chang B, Hendricks A, et al. Agreement between administrative data and patients’ self-reports of race/ethnicity. Am J Public Health.
2003;93(10):1734-1739.Surveillance Epidemiology and End Results
Program. 2007 SEER Program Coding and Staging Manual (SPCSM) with
2008 revisions. Rockville, MD: National Cancer Institute; 2007.
195
Original Article
Conforming to Cancer Staging, Prognostic
Indicators and National Treatment Guidelines
Gwendylen R. Dykstra-Long, RHIA, CTR, CMTa
Abstract: Clinical cancer staging and prognostic indicators guide treatment planning, and as such the American College
of Surgeons Commission on Cancer Commission on Cancer (ACoS CoC) and the American Joint Committee on Cancer
(AJCC) have recognized this as quality patient care. Overton Brooks Veterans Administration (OBVAMC) developed an
organizational policy and procedure, flow algorithms, treatment plan templates, and education strategies in order to conform to this quality care approach. The purpose of this article is to share this systematic approach that is able to support
clinical and working cancer stage and prognostic indicators which have been recognized by national standard setting
organizations as quality patient care.
Key words: cancer staging, prognostic indicators, national treatment guidelines
Introduction
Cancer staging is a shorthand method of writing the
extent of cancer and therefore helps determine appropriate treatment for a particular stage of disease, including
appropriateness for clinical trials. In addition, the stage of
a cancer helps determine a patient’s prognosis. As cancer
staging plays an important role in fighting cancer, it is the
managing physician’s responsibility to stage and document
each newly diagnosed cancer case in a timely, complete,
and accurate fashion.1 However, documentation seems to
be the most common barrier in cancer care due to requirements for documentation having changed so much over the
last several years. What contributes to the documentation
issue? Physicians have many priorities such as patient care,
committee work, call coverage, management, and practice
administration to tend with. Too many priorities and not
enough training in charting contribute to the documentation deficiencies.2
Recently, the AJCC reviewed prognostic indicators for
incorporation into the Tumor, Node, and Metastasis (TNM)
staging guidelines. For example, molecular markers are
used in colorectal carcinoma to identify microsatellite instability (MSI) and vascular endothelial growth factor (VEGF)
expression. Staging and assessment of molecular prognostic
indicators are important in identifying treatment modalities3. Recognizing the importance of prognostic indicators,
the AJCC followed through with revisions to incorporate
into the seventh edition staging schemes to include certain
site-specific prognostic indicators which became effective
for cancer cases diagnosed as of 2010. For instance, prostate
cancer includes the Gleason Score and prostate specific
antigen (PSA) into its staging scheme to determine the
stage group. In addition to the AJCC prognostic indicators
there is the Eastern Cooperative Oncology Group (ECOG)
Functional Performance Status (FPS). The FPS is an important prognostic indicator collected by Veterans Health
Administrations (VHA) nationally to assess how a patient’s
Figure 1. Flow Algorithm for Quality Assessment of Cancer
Stage, Prognostic Indicators, and National Treatment
Guideline
Casefinding by
tumor registrar
Eligible cancer cases are
entered into the registry
software program
suspense folder
Cancer program manager
reviews accessioned cases
for clinical cancer staging
eligibility
Cancer Program Manager
assigns staging form for
managing physician to
complete clinical staging in
electronic medical record
Clinical cancer staging, prognostic
indicator (ECOG FPS), & national
treatment guideline documented
via tumor board, treatment
plan/management, or op note?
Physician documents
clinical staging?
Physician documents
prognostic indicator
(ECOG FPS)?
Physician documents
treatment guideline used
in treatment planning.
i.e., NCCN, AUA, other?
disease affects daily living abilities, appropriate treatment and prognosis. Finally, cancer staging and prognostic
indicators guide treatment planning from evidence-based
national guidelines such as the National Comprehensive
__________
Cancer Program Manager, Overton Brooks Veterans Administration Medical Center (OBVAMC).
a
Address correspondence to Gwendylen R. Dykstra-Long, RHIA, CTR, CMT. Email: [email protected].
196
Journal of Registry Management 2011 Volume 38 Number 4
Figure 2:Figure
Computerized
Patient Patient
RecordRecord
SystemSystem
(CPRS)(CPRS)
Medical
Oncology
Treatment
Plan Template
Example
2: Computerized
Medical
Oncology
Treatment
Plan Template
Example
Diagnosis: NSCLC = Adenocarcinoma
Stage: c
T2 a
N2
M1 a
GX
Group Stage: IV
ECOG FPS: 2 Some bed time, but needs to be in bed <50% of normal day
Is patient considered incurable? Yes, patient is considered incurable due to:
Advanced/Extensive/Metastatic disease, Available treatment does not cure the disease
Was Hospice/Best Supportive Care/End of life care discussed with the patient? Yes
Was Hospice Care offered to the patient? Yes
Was Code Status discussed? Yes
The patient codes status is: No Code
If patient is NO CODE, did you generate a social work consult for Advance Directive? Not Applicable (explain)
Pt is working on it with wife.
Discussed at length the nature of patient's disease, goal(s) of therapy and options of therapies. I also
discussed the logistics and side-effects of the chemotherapeutic agents used in this case as well as the
realistic expectation(s) of such therapy.
Patient is inclined/decided to pursue: Active therapy based on guidelines of NCCN FDA
Chemotherapy alone which consists of: The standard regimen of Carbo/ALIMTA every 21 days for a total of 6
cycles.
Cancer Institute (NCCN).4 So, why are there all of these
changes? We learn more and more as cancer is continually
investigated which in turn demands an increased need for
change and standardization.5 The purpose of this article
is to share OBVAMC’s methodology to quality patient
care through use of organizational policy and procedure,
flow algorithms, treatment plan templates, and education
strategies to support clinical and working cancer staging
and prognostic indicators which have been recognized by
national standard setting organizations.
Methods
To facilitate timely, accurate, and complete documentation by the managing physician, a quality improvement
process referred to as Plan, Do, Study, Act (PDSA) was
implemented by OBVAMC. To meet OBVAMC needs,
use and maintenance of an organizational cancer staging
policy and procedure was adapted from the ACoS CoC best
practice repository.6 The best practice policy and procedure
outlines: (1) purpose, policy, and procedure for assigning the
electronic AJCC staging, (2) standardized locations of the
electronic health record (EHR) to complete AJCC staging,
(3) prognostic indicators and evidence-based national treatment guidelines, (4) definitions of clinical and working
stage and the managing physician, (5) accuracy rate, resolutions and discrepancies, and (6) quality assurance.
In addition to our policy and procedure, a flow algorithm of the documentation review process was composed
(Figure 1). OBVAMC accessions 500 cases per year on
average and is staffed with a full-time cancer program
manager, tumor registrar and part-time follow-up clerk.
OBVAMC’s process for a quality assessment “snap-shot”
Journal of Registry Management 2011 Volume 38 Number 4
begins with the tumor registrar who performs case finding
on a one-month retrospective timeline. For instance, if this
is June 1, then case finding from the previous month of May
is reviewed to determine which cases are appropriate to be
accessioned into the registry database. On a monthly basis
the cancer program manager will pull a canned report of
the cases accessioned by the registrar. Each case is reviewed
in the EHR for the managing physician’s documentation
of the cancer stage, prognostic indicator of ECOG FPS and
the evidence-based standard setter organization used in the
treatment planning, ie, NCCN. If there is no documentation
of those attributes in the EHR via a tumor board, treatment plan/management or op note, then a staging form
is assigned for completion. The findings of the physician’s
documentation or lack of it is then recorded in the cancer
abstract.
OBVAMC created new and revised current documentation templates in our EHR to capture the required
attributes of AJCC staging, prognostic indicators and treatment guidelines. Since the CoC has relaxed its stance on
staging forms in the medical record, and recognizing that
not all of our managing physicians prefer to use a cancer
staging form, it was discussed with our Chief of Oncology
(Cancer Liaison Physician) about creating a new treatment
plan documentation template for the medical oncology
service, and as such, he created a remarkable EHR treatment
plan template (Figure 2). Stemming from this concept, our
EHR staging form, tumor board and radiation oncology
treatment management templates were revised to include
the required attributes. Finally, it was noted that on occasion for certain cancer sites such as colorectal, that the
intra-operative information can be incorporated into the
197
Figure 3: Flow Algorithm for AJCC Staging of Primary Tumor
for Colorectum
Is there evidence of a
primary tumor of
colorectal origin?
Is a primary tumor of
colorectal origin
suspected although
there is no evidence?
Is there evidence that the
primary tumor directly
involves other organs or
structures?
Is there evidence that the
primary tumor involves the
surface of the visceral
peritoneum by direct
extension through serosa?
Is there evidence that the
primary tumor extends to
the muscularis propria to
involve the
pericolorectal tissues?
Is there evidence that
the primary tumor
involves the muscularis
propria?
Is there evidence that
the primary tumor
involves the submucosa?
nodes and metastasis for our top sites of prostate, lung, and
colorectal (Figures 3 and 4). In addition, email notifications
and interactive question and answer email competitions for
gift certificates were utilized as learning incentives. ACoS
CoC Webinars, postings of resource materials to our intranet
site Hot Topics and our cancer program Web page, poster
board displays throughout the organization as well as
networking with our regional VHAs were are also utilized.
An Excel program functions as our monitoring and
reporting tool to evaluate the effectiveness of our cancer
staging policy and procedure, flow algorithm(s), treatment plan templates and educational strategies. From our
OncoTrax software, an ad hoc report is generated with the
following case criteria: (1) analytic, (2) invasive histology,
(3) diagnostic confirmation by histopathology, and (4)
applicable to AJCC stage excluding skins and reportable
by agreement cases. The managing physician, physician’s
stage, registrar’s stage, ECOG FPS and the treatment guideline standard setter organization is exported from the cancer
abstract into Excel for preliminary concordance rates to be
calculated.
Cases not concordant are subtracted from concordant
cases and then the percentage is calculated by dividing
non-concordant cases by concordant cases. For ongoing
comparison of the results, the percentage is then graphed
in Excel as a stacked bar chart for the months of January
through December. The graph as well as a summary report
to the Medical Executive Committee (MEC) is presented
on a quarterly basis to address the current annual analytic
caseload, number of cases applicable to AJCC staging,
number of cases applicable which were staged and accuracy
which is determined by comparing the physician’s stage
to the registrar’s stage. Finally, our 10% physician reviews
are then randomly selected from the MEC ad hoc report to
determine if the diagnostic evaluation and treatment plan is
in actual concordance and appropriate to the documented
stage and prognostic indicator(s). The results of the 10%
physician review are reported to the cancer committee
meeting on a quarterly basis.
Results
Does path report state in
situ, intraepithelial or
invasion of lamina propria
(intramucosal)??
clinical staging. With that being the case, our operative note
template was also revised to include the required attributes.
OBVAMC incorporated several ongoing educational
strategies for our managing physicians. The strategies
consist of speaking at staff meetings and orientations and
providing on-the-go educational materials such as laminated flow algorithms for the staging of the primary tumor,
198
OBVAMC’s results were gathered for 9 months, during
the time frame of January through September 2011. New
staff physicians (n=4) in surgery, medical oncology and
radiation oncology were provided a cancer program orientation with overview of the cancer staging policy and
procedure. Although the registry quality assessment flow
algorithm identified cases (n=11) that needed staging prior
to planned systemic and/or radiation therapy, cases were
also identified where the managing physician had initiated
and completed their own treatment plan templates (n=34).
Various staff meetings and orientations were organized and
attended where cancer staging was discussed (n=18). There
were cases identified (colorectal n=5, lung n=6 and prostate n=15) where the educational flow algorithms for the
primary tumor were utilized as the managing physician’s
clinical and or pathologic T did not compare to the registrars. Findings for NX from January through September
2011 revealed n=6 compared to the previous 9 months of
Journal of Registry Management 2011 Volume 38 Number 4
Figure 4: Flow Algorithm of Regional Nodes and Distant
Metastasis for all Applicable Sites to AJCC Staging
Is there clinical or
histologic EVIDENCE
of nodal or distant
mets via H&P, PE, or
other?
Were there any
imaging studies
performed to evaluate
nodal or distant mets?
Was standard treatment
offered for clinically
localized cancer?
April through December 2010 where n=11. There was no
difference in MX during this same time period where n=0.
Webinars shared with our physicians, nurses, and other
allied healthcare included the following: Debunking Urban
Legends in Cancer Staging; Monitoring Clinical Stage; and
Introducing the Next Generation of Prostate Cancer Staging
AJCC 7th Ed.
In our reporting to the MEC, the overall concordance
rates for 2010 revealed AJCC stage at 99%, prognostic
indicators at 69%, and national treatment guideline at 58%.
AJCC cancer stage consistently remained well above our
90% benchmark from January through September 2011.
In January 2011 concordance rates improved drastically
with prognostic indicator at 84%, and national treatment
guideline at 87%. We saw an increase in concordance for
prognostic indicators and national treatment guideline
above our 90% benchmark in May 2011. Our latest calculation of concordance rates was in September 2011 which
revealed prognostic indicators at 97% and national treatment guideline at 95%. Finally, the randomly selected
cases from the 2011 MEC reports that were used for our
10% physician review revealed cancer staging, prognostic
indicators, national treatment guideline and accuracy to be
100% for the March, June, and September 2011 quarterly
cancer committee reporting.
Discussion
Besides the fact that OBVAMC is an approved cancer
program which provides quality patient care and incorporates recommendations of the National Cancer Strategy,
Under Secretary for Health’s Information Letter on Cancer
Staging, there are other reasons the need for improvement
Journal of Registry Management 2011 Volume 38 Number 4
in concordance rates were addressed.7 Funding has recently
been noted to play a tremendous role, as a recent audit
of our stage IV cancers for fiscal year (FY) 2011 was to
determine if patients were appropriately classified to the
Metastatic Cancer Patient Class. Our funding is based on
a capitated model and the audit helped justify additional
funding for several of our future FY budgets.
Finally, as new staff rotates in and out there is the
tremendous need for ongoing education. It is imperative we
keep ongoing education to all of our providers. Education
can be provided with minimal or zero cost through various
staff meetings and orientations, on-the-go educational
materials, email, ACoS CoC webinars, intranet postings of
resource materials, and poster boards. In addition, OBVAMC
also educates through networking. Our Veterans Health
Administrations are organized into regions called Veterans
Integrated Systems Networks (VISN) 1-23. Our facility falls
into VISN 16 the South Central Veterans Administration
Health Care Network (SCVAHCN). SCVAHCN includes
Alexandria, Louisiana; Biloxi, Mississippi; Fayetteville,
Arkansas; Houston, Texas; Jackson, Mississippi; Little Rock,
Arkansas; Muskogee, Oklahoma; NOLA; OKC and our
facility, OBVAMC, located in Shreveport, Louisiana. Our
VISN 16 SCVAHCN office is staffed with a Cancer Program
Manager and Cancer Program Analyst who coordinates and
holds biweekly cancer registrar and monthly cancer care
committee teleconferences. These teleconferences include
key stakeholders throughout our VISN 16 facilities. We also
hold a yearly VISN 16 cancer care symposium where our
stakeholders gather to discuss cancer care. Our goal is to
share ideas and create new or streamline current processes
in our approved cancer programs in order to provide the
best possible care for our patients.
There were several strengths in the findings of
OBVAMC’s study. The policy and procedure was beneficial
in communicating our organizational expectations and
therefore lessened the missed opportunities for quality
documentation. Use of the tumor registry QA flow algorithm has contributed to timeliness and completeness by
identifying cases, which otherwise would have been missed,
that were in need of staging prior to planned systemic
and/or radiation therapy. Treatment plan templates also
impact timeliness and completeness in a positive way
due to the managing physician most often initiating and
completing the note before systemic and/or radiation
treatment has begun, as well as before the registry QA had
begun for calculation of preliminary concordance rates.
Various staff meetings have allowed for the opportunity of
one-on-one question and answer sessions to clarify expectations regarding timeliness, accuracy, and completeness of
cancer staging, prognostic indicators and treatment guidelines. Interactive email competitions, ACoS CoC Webinars,
intranet postings of resource materials on our Hot Topics
and cancer program webpage, as well as poster boards
support our yearly clinical educational activity for standard
1.10. The poster boards are placed strategically in high
traffic areas for communication to those who may not have
had the opportunity to be informed via other educational
methods as mentioned earlier. The webinars are funded by
199
our VISN 16 and have been found extremely useful for our
networking to keep our regional VHAs abreast of cancer
staging standards. Finally, the primary site flow algorithms
proved useful in reassessment of the clinical and/or pathologic T for those cases found with discrepancy and need for
resolution.
OBVAMC also identified a weakness of the study.
Without complete staging, a stage group usually cannot be
assigned which affects analysis such as survival by stage,
and as such a flow algorithm for regional nodes and distant
metastasis was provided to guide cancer staging to avoid
abusing NX and elimination of MX. Although the numbers
reported for NX and MX were extremely low, it is unclear at
this time how much of a role the flowchart actually played.
It is difficult to identify whether the numbers are due to an
alternate or a mix of other educational methods provided
where NX and MX is discussed.
It appears that OBVAMC’s findings can be generalized
to another study that has looked at documentation improvement which was discussed in the ACoS CoC webinar
Monitoring Clinical Stage to Improve Care. In comparison,
both studies focused on patient care by developing a
process to monitor physician use of stage, prognostic indicators and treatment guidelines through use of a PDSA. Both
implementation processes consisted of education, acceptable locations for staging, use of nationally recognized
standards, and initiating and reporting the findings to the
cancer committee with a goal to improve compliance rates.
In addition, both studies established which primary sites
would be reviewed for staging and the treatment process, as
well as set rates of accuracy and concordance to be reported
to the cancer committee. Finally, both studies selected standardized locations for staging and utilized a monitoring grid
or tool with the attributes of primary site, physician, stage,
accuracy, and treatment. In contrast, OBVAMC’s implementation process included use of an organizational policy
and procedure; flow process algorithms and treatment plan
templates, as well as continues to utilize the staging form as
a standardized location. Also, in addition to reporting to the
cancer committee, OBVAMC reports concordance rates to
the MEC for all sites applicable to AJCC staging in a lump
sum total, while the other study reported concordance rates
broken out by specific site of lung, hematologic, rectum and
esophagus.
There were several limitations in OBVAMC’s study.
There was no method in place to monitor the usefulness
of regional node and distant metastasis flowchart. To gain
some feedback, it might be of benefit to provide a survey
to the managing physician’s regarding which method(s) of
education and resource materials they prefer to utilize to
aid in complete and accurate staging. The study was also
limited due to the choice of sites selected for QA. Our focus
was on cases applicable to AJCC staging, however hematologic malignancies are one of our top sites and therefore
it would have been appropriate to include them in our
monitoring and reporting process as the other study did.
AJCC staging is not applicable to hematologic malignancies,
however the Rai staging for chronic lymphocytic leukemia
and Durie-Salmon for myeloma along with prognostic
200
indicators are beneficial to treatment planning as well.
Another limitation is that there are not enough published
studies on the subject to further compare or contrast at this
time. Considering the weaknesses identified and limitations
of the study, OBVAMC has adapted very well over this short
period of time to become concordant in timeliness, accuracy,
and completeness of the cancer staging, prognostic indicator and treatment guideline documentation.
References
1. American Joint Committee on Cancer. Purposes and Principles of Cancer
Staging. AJCC Cancer Staging Handbook. 7th ed. Chicago, IL: Springer,
2010:3-11.
2. The Advisory Board Company. Oncology Round Table: The New
Quality Mandate. Building a Quality-Centric Service Line to Elevate
Program Performance. Washington, DC. The Advisory Board Company,
2008:63-67.
3. Green F, Sobin L. The Staging of Cancer: A Retrospective and Prospective
Appraisal. CA A Cancer Journal for Clinicians. 2008;58:180-190.
4. NCCN Clinical Practice Guidelines in Oncology. Available at: http://
www.nccn.org/professionals/physician_gls/f_guidelines.asp. Accessed
August 1, 2011.
5. Hurlbut A. Change management: A Must-Have for 2010 Implementation.
J Registry Manage. 2009:36;147-152.
6. American College of Surgeons Commission on Cancer. Assessment of
Evaluation of Treatment Planning. Cancer program Standards 2012:
Ensuring Patient-Centered Care. Chicago, IL: American College of
Surgeons. 2011: 88-89.
7. U.S. Department of State. Under Secretary for Health’s Information
Letter, Cancer Staging IL10-2010-010. Washington, DC. Department of
Veterans Affairs Health Administration. June 2010.
Journal of Registry Management 2011 Volume 38 Number 4
Original Article
Histological Classification of Liver and Intrahepatic
Bile Duct Cancers in SEER Registries
Sean F. Altekruse, DVM, PhDa; Susan S. Devesa, PhDb; Lois A. Dickie, CTRa; Katherine A. McGlynn, PhDb;
David E. Kleiner, MDc
Abstract: Clear definitions of histological groups are essential for studies of liver and intrahepatic bile duct cancers. Thus,
we developed a classification system based on abstracted information on histologies of liver and intrahepatic bile duct
cancers diagnosed during 1978-2007 within all Surveillance, Epidemiology, and End Results (SEER) registries. Of 61,990
reported primary liver and intrahepatic bile duct cancers, 108 distinct ICD-O histology codes were identified. During the 5
recent years of diagnosis, 2003-2007, the leading histological groups were hepatocellular carcinoma (75%) and cholangiocarcinoma (12%). The remaining categories were other specified (3%) and poorly specified carcinomas (3%), hepatoblastomas (1%), sarcomas (1%), embryonal sarcomas (0.1%), other specified malignancies (0.05%), and poorly specified malignancies (5%). During 2003-2007, only 68% of diagnoses were microscopically confirmed. Factors contributing to incomplete
histological classification may include reluctance to obtain diagnostic specimens from late stage cases and administration
of therapy in lieu of histological confirmation after positive diagnostic imaging. Conclusion: The proposed histological
classification in this report may facilitate studies of primary liver cancers. This is of value because the inconsistent characterization of some cancers, particularly cholangiocarcinomas, may affect interpretation of incidence trends. Incomplete
histological characterization of hepatocellular carcinomas was noted in this report. It is likely to be explained by guidelines
affirming the use of non-invasive diagnostic and treatment procedures for this cancer.
Key words: hepatocellular carcinoma, cholangiocarcinoma, microscopic confirmation, trends
Introduction
Defining histological groups of cancers is essential
for surveillance and clinical research. For the first several
years of the Surveillance, Epidemiology, and End Result
(SEER) program, the Manual of Tumor Nomenclature
and Coding (MONTAC) 1968 edition was used to code
anatomic site and histologic type.1 The morphology code
consisted of 3 digits, with a fourth digit designating the
degree of malignancy or behavior. SEER started using the
International Classification of Diseases for Oncology (ICDO), published in 1976 for cases diagnosed during 1977.2 The
morphology coding was expanded to 4 digits, with many
new codes added and the fifth digit was used to designate
the behavior. As an example, the MONTAC code 8163 was
expanded to 2 codes, cholangiocarcinoma (8160) and bile
duct cystadenocarcinoma (8161). The 1990 revision, ICD-O2,3 added a code for Klatskin tumor (8162/3) with a site of
C22.1=intrahepatic bile duct suggested. In 2000, ICD-O-3
added the site C24.0=extrahepatic bile duct as a site for
Klatskin tumor.4 Each edition attempted to include new
nomenclature appearing in the contemporary World Health
Organization Classification of Tumours series, or WHO
“Blue Books.”5,6 Changes in these and other classifications7,8
reflect advances in understanding of liver and intrahepatic
bile duct cancer histologies. The changing classifications
could introduce bias if cases are assigned to different histological groups based on when they were diagnosed. For
example, MONTAC code 8163 (above) includes cancers in 2
histological groups, cholangiocarcinoma and other specified
carcinoma. In an effort to address this issue, we restricted
histologic type-specific analyses to the 30 years covered by
ICD-O, 1978-2007, with additional analyses restricted to
even more recent time periods.
Liver and intrahepatic bile duct cancers are completely
characterized when site of origin and histology are known.
However, this detail is often unavailable. Thus, a high
proportion of cholangiocarcinomas are coded to liver rather
than intrahepatic bile duct. These cancers are therefore
classified as cholangiocarcinomas without consideration
of site of origin. Protocols from the College of American
Pathologists specify clinical information that could improve
diagnostic completeness when examining surgical specimens from patients with cancers of these sites.9,10
Several factors can impede characterization of liver and
intrahepatic bile duct cancers. Some histological terms for
primary cancers of these sites are general, 1-4 and case definitions for histological groups can vary between classification
systems.5-8 Complete characterization requires pathology
review of a primary resection or clinical findings, images11
and pathology reports. Patients with advanced stage cancer
may not have tissue collected.12 Electronic record review13
and greater diagnostic imaging technology14 may also
affect tissue collection. With the increasing incidence of
hepatocellular carcinoma in the United States15 and current
__________
National Cancer Institute, Division of Cancer Control and Population Sciences, Rockville, MD. bNational Cancer Institute, Division of Cancer Epidemiology
and Genetics, Rockville, MD. cNational Cancer Institute, Division of Basic Sciences, Laboratory of Pathology, Bethesda, MD.
a
Address correspondence to Sean F. Altekruse, DVM, PhD, 6116 Executive Boulevard Suite 504, Rockville, MD 20852.
Journal of Registry Management 2011 Volume 38 Number 4
201
Table 1. Reported Liver and Intrahepatic Cancer Cases, by Site, SEER 17, 1978-2007*
Histological classification (ICD-O)
Liver
IHBD†
Total
Carcinoma
51,504
6,483
57,987
Group:
Hepatocellular carcinoma
44,080
40
44,120
Group:
Cholangiocarcinoma
3,483
5,565
9,048
Group:
Other specified carcinoma
1,322
722
2,044
Group:
Poorly specified carcinoma
2,619
156
2,775
527
0
527
~
~
500
Class:
Class:
Hepatoblastoma
Class:
Sarcoma
Group:
Hemangiosarcoma
~
~
190
Group:
Hemangioendothelioma
77
0
77
Group:
Other sarcoma
~
~
233
Class:
Embryonal sarcoma
65
0
65
Class:
Other specified malignancy
~
~
33
Group:
Germ cell tumor
~
~
12
Group:
Carcinosarcoma, NOS
~
~
20
Group:
Malignant melanoma, NOS
~
~
~
Poorly specified malignancy
2,719
159
2,878
55,344
6,646
61,990
Class:
All liver and intrahepatic cancer cases combined
*International Classification of Diseases for Oncology
†IHBD: Intrahepatic Bile Duct.
Source: Incidence-SEER 17, Nov 2009 File, Katrina/Rita Population Adjustment, 1973-2007 varying.
~Data were suppressed when site specific or total counts included less than 12 cases. Zero counts were allowed.
guidelines affirming diagnosis based on imaging only, and
the use of ablative therapy under specified circumstances,16
may affect the percentage of hepatocellular carcinoma cases
that are histologically confirmed. Furthermore, inconsistent definitions of anatomic location and histologies may
impede analysis of epidemiological trends for intrahepatic
cholangiocarcinomas.17
Taken together, these factors could affect interpretation of liver and intrahepatic cancer surveillance data. This
report presents proposed histological groups for cancers
of the liver and intrahepatic bile duct diagnosed within
SEER registries from 1978 through 2007 based on abstracted
data on histology and site of origin. Our goal was to define
histological groups and changes in histologic confirmation
to facilitate cancer surveillance and epidemiologic studies.
Methods
Data
Primary cancers of the liver (ICD-O topography
code=C22.0) and intrahepatic bile duct (ICD-O topography
code=C22.1) were included in this analysis.2-4 Cases were
diagnosed among persons residing within the National
Cancer Institute’s SEER Program (SEER-17) registry areas
during 1978-2007. A total of 61,990 incident cases met the site
criteria. The SEER-9 registries (Connecticut, Metropolitan
Detroit, Hawaii, Iowa, New Mexico, San Francisco Bay
Area, Utah, Seattle-Puget Sound and Atlanta) contributed
cases as of 1978, with the implementation of ICD-O. Cases
202
from San Jose-Monterey, Los Angeles, Alaskan Native
and Rural Georgia registries were included as of 1992. In
Greater California, Kentucky, Louisiana, and New Jersey
registries, cases were included starting in 2000. Registries
collected case data under state-mandated rules for reportable diseases. Incidence data were de-identified prior to
submission to the SEER Program.
Abstracted Data
Histologies of reported liver and intrahepatic bile
duct cancers were abstracted by cancer registrars, usually
from pathology reports. A liver pathologist (DK), a certified
cancer registrar (LD), and epidemiologists with expertise
in liver and intrahepatic bile duct cancer etiology (KM),
surveillance (SA), and cancer classification (SD) analyzed
data regarding reported sites and histologies with the
interest of validating the histological classification. One
interest was to identify histologies that should be classified
as cholangiocarcinomas because inconsistent designation of
this group of cancers may impede analysis and interpretation of surveillance trends.16 Through a process including
literature review and consultation, a proposed classification
was developed for liver and intrahepatic bile duct cancers.
Histological Groups
Hepatocellular carcinomas were defined by ICD-O
morphology codes 8170 through 8175. Cholangiocarcinomas
included the most common histology within this group (ie,
ICD-O-3 topography code 8160: Cholangiocarcinoma) and
Journal of Registry Management 2011 Volume 38 Number 4
Table 2. Proposed Histological Classification of Liver and Intraheptic Bile Duct Cancers, SEER 17, 1978-2007
Class
Group
Hepatocellular carcinoma
8170-8175
Cholangiocarcinoma
8032, 8033, 8070, 8071, 8140, 8141, 8160, 8260, 8480, 8481, 8490,
8560
Other specified carcinoma
8012, 8013, 8041, 8142, 8124, 8161, 8162, 8180, 8190, 8211, 8240,
8246, 8249, 8255, 8290, 8310, 8323, 8337, 8440, 8450, 8453, 8470,
8471, 8500, 8503, 8510, 8521, 8550, 8574, 8576
Poorly specified carcinoma
8010, 8020, 8021, 8022, 8031, 8046, 8050
Carcinoma
Hepatoblastoma
8970
Hemangiosarcoma
9120
Hemangioendothelioma
9130, 9133
Other Sarcoma
8800-8805, 8810, 8815, 8830, 8850, 8852, 8890, 8891, 8894-8896,
8900, 8910, 8920, 8935, 8936, 8940, 8963, 8990, 9040, 9041, 9124,
9150, 9180, 9220, 9260, 9364, 9473, 9500, 9540, 9560
Sarcoma
Embryonal sarcoma
Other specified malignancy
Poorly specified malignancy
ICD-O Morphology Code
8991
Germ cell tumor
9064, 9070, 9071, 9080, 9100
Melanoma, carcinosarcoma
8720, 8980
8000-8004
Database: Incidence - SEER 17 Registries, Nov 2009 Submission, Katrina/Rita Population Adjustment (1973-2007 varying).
12 other histologies deemed to be primary adenocarcinomas
or squamous cell carcinomas arising from the intrahepatic
bile duct epithelium. Other and poorly defined carcinomas
were defined based on the specificity of the ICD-O code.
Sarcomas were classified as hemangiosarcomas, hemangioendotheliomas and other sarcomas. Hepatoblastomas
and embryonal sarcoma were each considered to be unique
histological groups. Other specified malignancies that were
rarely diagnosed within the SEER registries included germ
cell cancers, carcinosarcomas and malignant melanomas.
Approximately 5% of cancers were grouped as poorly
specified malignancies. As in “Cancer Incidence in Five
Continents,”7 information on the primary cancer site, liver
(topography code C22.0) versus intrahepatic bile duct
(topography code C22.1) did not affect the assignment of
histological groups (see discussion).
The resulting classification reflected the logic of the
2010 WHO Classification of Tumours.5,6 Our approach to
classification was also similar to “Cancer Incidence on Five
Continents;” 7 however, we classified 17 spindle cell carcinomas (ICD-O, 8032) and 6 pseudosarcomatous carcinomas
(ICD-O, 8033) as cholangiocarcinomas, as likely variants of
poorly differentiated adenocarcinoma rather than unspecified carcinomas. Eighteen cancers were reassigned from
cholangiocarcinoma to other specified carcinoma (bile duct
cystadenocarcinoma [ICD-O, 8161] and cystadenocarcinoma, not otherwise specified or NOS, [ICD-O-3, 8440]), as
a biologically distinct set of cancers. The 35 cases with the
histologic diagnosis of infiltrating duct carcinomas (ICDO-3, 8500) were grouped with other specified carcinomas.
Papillary carcinoma of the liver was classified as a poorly
specified carcinoma.
Journal of Registry Management 2011 Volume 38 Number 4
Histological Confirmation
The proposed classification system for liver and intrahepatic bile duct cancers was used to assess the frequency
distribution and diagnostic confirmation of these cancers in
the 5 most recent diagnosis years, 2003 to 2007.
Results
Frequencies
Of 61,990 primary liver and intrahepatic bile duct
cancers diagnosed within the SEER 17 registries, 57,987 (94%)
were classified as carcinomas (Table 1). Hepatocellular carcinomas (n=44,120) were diagnosed more often than all other
histologic groups combined and the next most frequent
group of tumors, cholangiocarcinomas (n=9,048), were
reported more often than the remaining histologic groups
combined. Only 3 other histologic groups accounted for
more than 2,000 cases, 2 carcinomas: other specified carcinomas (n=2,044) and poorly specified carcinomas (n=2,775)
and poorly specified malignancy (n=2,878). Hepatoblastoma
was the only other histology reported more than 500 times
(n=527). In the class “sarcoma,” 500 cases were reported,
including 190 hemangiosarcomas. Less than 100 tumors
were reported in each of 2 classes: embryonal sarcomas and
other specified malignancies. Two extrahepatic histologies
were reported: Klatskin tumor (n=691) and hepatoid adenocarcinoma (n=9), data not shown.
Histological Classification
Cancers were assigned into broad histological categories that reflect prior criteria.5,6 Broad histological classes
were carcinomas, hepatoblastomas, sarcomas, embryonal
203
Table 3. Classification of Liver and Intrahepatic Bile Duct Cancers by Histological Confirmation, SEER 17, 2003-2007
Microscopically
Confirmed
All Cases
Class
Group
Unconfirmed Cases
No.
Percent
% Confirmed
No.
Percent
No.
Percent
All Liver and IHBD Cancers
26,130
100%
68%
17,773
100%
8357
100%
Carcinoma
24,367
93%
71%
17,273
97%
7094
85%
Hepatocellular
carcinoma
19,669
75%
69%
13,613
77%
6056
72%
Cholangiocarcinoma
3,092
12%
86%
2,650
15%
442
5%
ICC: Site, IHBD
1,848
7%
80%
1,486
8%
362
4%
ICC: Site, Liver
1,244
5%
94%
1,164
7%
80
1%
Other specified
carcinoma
740
3%
86%
637
4%
103
1%
Poorly specified
carcinoma
866
3%
43%
373
2%
493
6%
Hepatoblastoma
185
1%
97%
179
1%
6
0%
Sarcoma
162
1%
96%
155
1%
7
0%
Hemangiosarcoma
58
0%
97%
56
0%
2
0%
Hemangioendothelioma
35
0%
94%
33
0%
2
0%
Other Sarcoma
69
0%
96%
66
0%
3
0%
Embryonal sarcoma
31
0%
100%
31
0%
0
0%
Other specified malignancies
12
0%
100%
12
0%
0
0%
Poorly specified malignancies
1,373
5%
9%
123
1%
1250
15%
†
* SEER 17: San Francisco, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle, Utah, Atlanta, San Jose-Monterey,
Los Angeles, Alaska Native Registry, Rural Georgia, California excluding SF/SJM/LA, Kentucky, Louisiana and New Jersey.
†IHBD: Intrahepatic Bile Duct.
Database: Incidence - SEER 17 Registries, Nov 2009 Submission, Katrina/Rita Population Adjustment (1990-2007 varying).
sarcomas, other specified malignancies, and poorly specified malignancies (Table 2). Of these 5 classes, 3 were
divided into more detailed histological groups. For example,
carcinomas included hepatocellular carcinomas, cholangiocarcinomas, other specified carcinomas, and poorly
specified carcinomas. Sarcomas included hemangiosarcomas, hemangioendotheliomas, and other sarcomas. Other
specified malignancies included germ cell cancers, melanomas, and carcinosarcomas.
Histological Confirmation
In the SEER 17 registries during the 5 most recent
diagnosis years, 2003-2007, 68% of liver and intrahepatic
bile duct cancers were microscopically confirmed (Table 3).
Microscopic confirmation rates were higher than the overall
rate for specific histological categories with the exception of
hepatocellular carcinoma, the only specified histology for
which less than 70% of cases had microscopic confirmation.
In contrast, less than half of poorly specified carcinomas
(43%) and poorly specified malignancies (9%) were histologically confirmed.
Discussion
The present report is based on the 30 year experience
in SEER registries and included 61,990 cases of liver and
204
intrahepatic bile duct cancer. In diagnosis years 20032007, 93% of liver and intrahepatic bile duct cancers were
carcinomas. The most frequent morphologic type was
hepatocellular carcinoma (75%), followed by cholangiocarcinoma (12%).
Defining ICD-O histologies that correspond with
cholangiocarcinomas in order to facilitate analysis and interpretation of incidence trends for this group of cancers was
a primary study objective because inconsistent designation
of this group of cancers may impede analysis and interpretation of surveillance trends.17 These cancers are primary
carcinomas of the epithelium of the intrahepatic bile duct.
Most were classified as cholangiocarcinomas (ICD-O=8160)
followed by adenocarcinomas, NOS; however, squamous
cell carcinomas infrequently arise within this site and
were here classified as cholangiocarcinomas. Thus, in this
report, with a few exceptions that involved fewer than
20 cases each, our classifications were consistent with
those presented in “Cancer Incidence in Five Continents.”7
Based on tumor biology, spindle cell and pseudosarcomatous carcinomas were grouped as cholangiocarcinomas
rather than unspecified carcinomas while bile duct and
other cystadenocarcinomas were grouped as other specified
carcinomas rather than cholangiocarcinomas. Infiltrating
Journal of Registry Management 2011 Volume 38 Number 4
duct carcinomas, which are elsewhere considered to be
cholangiocarcinomas, 7 were classified as other specified
carcinomas. Although there was agreement between classification systems on the leading cholangiocarcinoma
histologies surveillance data could be affected by inclusion
or exclusion of less common histologies.5-8 Furthermore
trend analyses that fail to account for shifts in histological
classification over time could be biased. For example, before
1978, cystadenocarcinoma and bile duct adenocarcinoma
were classified as 1 cancer type1 but are now classified as
“cholangiocarcinoma” and “other specified carcinoma,”
respectively.2-7
In this report, “liver” rather than “intrahepatic bile
duct” was specified as the primary site of 38% of cholangiocarcinomas. As in the WHO “Blue Books,”5,6 we classified
these histologies as cholangiocarcinomas without respect
to primary site. Since the 2 anatomic sites are intertwined,
when a primary site is not recorded, cholangiocarcinomas
are often coded to the primary site of liver. We suggest
that cholangiocarcinomas arising in 1 of these 2 sites be
assigned to the site of intrahepatic bile duct. In the present
study, 2 extrahepatic histologies were classified as intrahepatic histologies. 7 These histologies were Klatskin tumors
(n=691) and hepatoid adenocarcinoma (n=9). Pathologists
and tumor registrars are encouraged to designate these
histologies to an extrahepatic site of origin. Furthermore,
when the International Classification of Diseases for Oncology is
updated, we recommend that Extrahepatic Bile Duct (C24.0)
alone be suggested as the primary site for Klatskin tumors
(17) without inclusion of Intrahepatic Bile Duct (C22.1).
Liver is not, at present, a suggested site for hepatoid adenocarcinoma in ICD-O.1-3
Approximately one third of cancers in this report
were not histologically confirmed. In addition, 9% of
cases in SEER 17 registries during 5 recent diagnosis years
were diagnosed with either poorly specified carcinomas or
other poorly specified malignancies. Complete histological
classification is preferred to provide users of cancer surveillance data with optimal information on incidence rates and
trends, prognosis, and demographic disparities. Several
factors may contribute to incomplete histological characterization. First, histological terms for liver and intrahepatic
bile duct cancers range from very specific terms such
as hepatocellular carcinoma to more general terms such
as adenocarcinoma, not otherwise specified.2-4 Complete
characterization depends on pathology review of an intact
untreated, resected, primary tumor or review of clinical
findings, images and pathology reports. Poor prognoses
associated with advanced stage liver cancer may dissuade
practitioners from collecting diagnostic specimens.12 The
increasing incidence of hepatocellular carcinoma in the
United States, 15 as well as clinical guidelines affirming the
use of non-invasive imaging for diagnosis and ablative
therapy for treatment16 of hepatocellular, could contribute
to unconfirmed hepatocellular carcinoma diagnoses.
Conclusion: We propose a more defined histological classification system to facilitate studies of liver and intrahepatic
cancers.
Journal of Registry Management 2011 Volume 38 Number 4
Acknowledgements
We thank Kathleen Cronin, Carol Kosary, Lynn Ries,
and Jennifer Ruhl (critical review), Neil Neyman (variable
coding), State and local health officials (case reporting), the
Census Bureau (population data), SEER registries (surveillance and data) and Information Management Services, Inc.
(incidence files).
Funding
Funding was provided by NCI, Division of Cancer
Control and Population Sciences, Surveillance Research
Program Contracts with SEER registries and Information
Management Services, and the Intramural Research Program
of the NIH, National Cancer Institute.
References
1. Percy CL, Berg JW, Thomas LB, eds. Manual of Tumor Nomenclature
and Coding. Atlanta, GA: American Cancer Society; 1968.
2. International Classification of Diseases for Oncology, Geneva: World
Health Organization; 1976.
3. Percy C, Van Holten V, Muir C. International Classification of Diseases for
Oncology. 2nd ed. Geneva: World Health Organization; 1990.
4. Fritz A, Percy C, Jack A, et al. International Classification of Diseases for
Oncology. 3rd ed. Geneva: World Health Organization; 2000.
5. Tumors of the liver and intrahepatic bile ducts. In: Hamilton SR,
Aaltonen LA, eds. World Health Organization Classification of Tumours.
Pathology and Genetics of Tumours of the Digestive System. Lyon: IARC;
2000:157-202.
6. Tumours of the liver and intrahepatic bile ducts. In: Boseman FT,
Carneiro F, Hruban RH, Theise ND, eds. World Health Organization
Classification of Tumours of the Digestive System. 4th ed. Lyon: IARC;
2010:195-262.
7. Egevad L, Heanue M, Berney D, Fleming K, Ferlay J. Histological groups.
In: Curado MP, et al, eds. Cancer Incidence in Five Continents. Vol. 9.
Scientific Publication No. 160, Lyon: IARC; 2009:61-66.
8. Carriaga MT, Henson DE. Liver, gallbladder, extrahepatic bile ducts, and
pancreas. Cancer. 1995;75(1 Suppl):171-90.
9. Washington MK, Berlin J, Branton PA, et al. Protocol for examination of
specimens from patients with hepatocellular carcinoma. CAP. 3rd ed.
Available at: http://www.cap.org.
10.Washington MK, Berlin J, Branton PA, et al. Protocol for the examination of specimens from patients with carcinoma of the intrahepatic bile
ducts. Arch Pathol Lab Med 2010;134(4):e14-18.
11.Sherman M. Hepatocellular carcinoma: epidemiology, surveillance, and
diagnosis. Semin Liver Dis. 2010;30(1):3-16.
12.Abrams P, Marsh JW. Current approach to hepatocellular carcinoma.
Surg Clin North Am. 2010;90(4):803-816.
13.Cheng LT, Zheng J, Savova GK, Erickson BJ. Discerning tumor status
from unstructured MRI reports—completeness of information in existing
reports and utility of automated natural language processing. J Digit
Imaging. 2010;23(2):119-32.
14.Leong E, Chen WW, Ng E, Van Hazel G, Mitchell A, Spry N.
Outcomes from combined chemoradiotherapy in unresectable and
locally advanced resected cholangiocarcinoma. J Gastrointest Cancer.
2011;42: Epub ahead of print.
15.Altekruse SF, Kosary CL, Krapcho M, et al, eds. SEER Cancer Statistics
Review, 1975-2007. Bethesda, MD: NCI. Available at: http://seer.
cancer.gov/csr/1975_2007/.
16.Bruix J, Sherman M. Management of hepatocellular carcinoma: an
update. Hepatology. 2011;53(3):1020-1022.
17.Patel T. Cholangiocarcinoma—controversies and challenges. Nat Rev
Gastroenterol Hepatol. 2011;8(4):189-200.
205
Original Article
Maximizing The Cancer Registry Role and
Data Utilization
Xuan Barzilay, MBA, CTR
Abstract: Objective: The cancer registry is traditionally placed within the department of medical records, which is known
today as the department of health information management (HIM). This arrangement provides cancer registrars easy
access to medical records where large portions of cancer data are collected. However, this placement may not be the ideal
one for some hospitals, especially those with a CoC-accredited cancer program where cancer registrars have broader job
functions than what are normally included in health information management. Electronic medical records eliminate the
need to place the cancer registry within the HIM for easy access to the records. This article analyzes the pros and cons of
some of the most common placements used by hospitals, as well as the impact each design has on information flow and
data utilization.
Key words: cancer registrar, cancer registry, Commission on Cancer (CoC), electronic medical records (EMR), health information
management (HIM)
Introduction
The cancer registry is an information system used to
track etiology, treatments and survival of patients with
cancer, or benign tumor of the central nervous system.1
Cancer registries were traditionally placed within the
department of medical records, which is known today as
the department of health information management (HIM).
This arrangement provides cancer registrars an easy access
to medical records where the majority of cancer data are
collected. Although this type of organizational design is
still the most commonly used in many hospitals, some have
adopted different arrangements that best fit their organizational structure by placing the cancer registry under
the department of medical oncology, radiation oncology,
nursing, or medicine. In some institutions, the cancer
registry is a stand-alone department reporting directly to
one of the senior executives. There were discussions among
cancer registrars nationwide as to whom the registry should
report. Although the best system has not yet been determined, some believe that the registry should not be placed
under HIM.
Organizational Structure and the Role of Cancer Registrars
The organizational structure of the cancer registry is
generally flat. Large registries usually consist of a manager,
a few abstractors whose primary function or only job is to
abstract cancer cases, and 1 or more follow-up clerks. In
larger registries, job functions tend to be much more differentiated in comparison to the smaller ones. Registrars in a
large registry usually have less job functions to perform.
In other words, an abstractor only abstracts cases, while a
follow-up clerk is only responsible for patient follow-ups.
If a hospital has a Commission-on-Cancer–accredited
cancer program, registrars normally assume additional
responsibilities such as coordinating cancer committee meetings and oncology conferences, conducting research studies,
preparing annual reports, and monitoring quality outcomes.
These additional job functions are usually performed by the
206
manager of the cancer registry, or a delegated senior staff
member. Job differentiation is considerably lower in a small
registry in comparison to a larger one. Registrars working
in a smaller registry usually have 2 or more responsibilities.
Those who work alone have to shoulder all the responsibilities on their own.
Data uniformity and comparability require a cancer
registry to be highly standardized. Detailed medical information of patients and their treatments is retrieved (abstracted)
from medical records, then translated into an abbreviated
or symbolic statement using standardized rules.2 Cancer
registrars around the world use the International Statistical
Classification of Diseases and Related Health Problems
(ICD-9) by the World Health Organization (WHO) to
assign codes to cancer sites and morphologies. In the US
and some other countries, the Cancer Staging Manual by
the American Joint Committee on Cancer (AJCC) is used
to determine the stage of malignant solid tumors at diagnosis. Standardization is not only essential to ensure data
uniformity and reliability, it also increases the efficiency and
accuracy of work performance. Without standardization,
it is impossible for researchers and clinicians to use data
collected by cancer registries around the world to evaluate
worldwide cancer trends and etiologies.
Clive and Miller described cancer registrars as the
army intelligence officers who collect critical data to fight
cancer.2 Cancer registrars in a healthcare facility abstract
cancer data from patient medical records, which is one of the
primary reasons that most of the registries are placed under
the department of health information management. At a
hospital level, information collected by the cancer registrars
can be used to assist administrators in making decisions
about physician recruitment, equipment purchases, and
patient needs.2
Over the years, the cancer registrar’s role has been
transformed from simply data entry to that of a more
active participant in a hospital’s cancer program. Cancer
registrars not only need to broaden their knowledge and
Journal of Registry Management 2011 Volume 38 Number 4
understanding of new technology in medicine but also
have to develop their skills in leadership and business.3
A workforce study by Chapman, et al shows that 55%
of those currently working in the field stated that an
associate’s degree would be the most suitable for those
interested in pursuing a career path in cancer registry.4
Based on this study, starting in 2010, the National Cancer
Registrars Association (NCRA) added an associate’s degree
minimum requirement to all candidates applying for a certification exam. Although this new requirement ensures that
newcomers will have the required educational background
to meet their job demands, some worry that it will further
limit the already thin supply of applicants in the workforce.5
Where Does the Registry Belong?
Despite the role cancer registrars play in a hospital’s
cancer program, the registry profession is unknown to most
people, including those working in a hospital setting. The
relatively anonymous state of the cancer registry and the
cancer registrar profession is linked to the placement of the
cancer registry in a hospital’s organizational structure.
There have been discussions among cancer registrars
on the NCRA online discussion forum as to whether the
registry should be a part of the department of health information management. Some registrars believe the registry
does not belong to the HIM because the registry has nothing
to do with the department except for the accessing of patient
records. According to the Commission on Cancer (CoC),
70% of hospitals in the United States and Puerto Rico do not
have a CoC-accredited cancer program.6 In those facilities,
a cancer registrar’s main job functions are to abstract cancer
cases and transmit them to the central or state registry.
Therefore, it is more practical for those hospitals to place the
cancer registry under the department of health information
management.
In facilities that have a CoC-accredited program, not
only do cancer registrars have a much broader responsibility, data utilization is also increased. In addition to
submitting their cancer data to the central or state registries,
cancer registrars are also required to send their data to the
National Cancer Data Base (NCDB). Institution wide, cancer
registrars have to provide benchmark studies, monitor
compliance of clinical practice guidelines, and participate
in community benefit activities as a part of the health care
leadership team.7 Their job scope is beyond the functions
of HIM. Although there are no standard requirements as to
where the registry should be in an organizational hierarchy,
a surveyor from the CoC once suggested that the registry
should be placed close to patient services instead of under
the department of health information management.
Easy access to inpatient medical records and physicians are the 2 advantages of placing the registry under the
HIM. However, in many hospitals, registrars also have to
obtain additional treatment information from departments
such as medical oncology, radiation oncology, pathology,
and radiology. Some of those records can be accessed
electronically while others have to be physically obtained
from those departments. In the hospital accredited by the
CoC, registrars interact mostly with people outside the
Journal of Registry Management 2011 Volume 38 Number 4
department of health information management. Since the 2
major functions of HIM are keeping records and generating
revenue, the department usually does not have budgets for
cancer-related activities that cancer registrars have to coordinate and participate in on a regular basis.
Transformation from paper records to electronic
medical records (EMR) can have a significant impact on
the organizational structure of the hospital, especially the
department of health information management. With the
implementation of EMR, cancer registrars can access patient
records from anywhere in the hospital, or even from a
remote location. The organizational structure of the cancer
registry will be decentralized and more organic. Some
hospitals already allow their cancer registrars to work from
home through the adoption of EMR. The only connection
the cancer registry has with the department of health information management, therefore, may be served.
When the registry is placed under the department
of nursing, it moves the registry close to patient services.
The department of nursing may also have the budget and
staff to provide outreach programs to local communities.
The problem with this arrangement is that cancer patients
are only a small portion of the population the department
serves, since systemic therapies today are mostly given in
outpatient settings. As a result, utilization of cancer data
could be rare, and outreach to cancer patients may not be
the main focus of the department.
In some hospitals, the cancer registry is a part of the
oncology department. I think this is probably the most
suitable department to place a cancer registry because
this department focuses mainly on cancer patients. It has
the most use of data from the registry. Since the department is chaired by a physician, he or she is more likely to
understand the importance of using cancer data in clinical
research or for quality improvement. Disadvantages of this
arrangement are that if the department is small, it may not
have the budget to provide hospital-wide programs, and
that the person in charge of the registry has to take some
administrative responsibilities such as budgeting and staff
evaluation.
Another type of organizational design is to make the
registry an independent department reporting directly to
one of the top executives. This kind of arrangement gives
the registry authority to coordinate the cancer program
and interact with other departments without the restraints
the aforementioned arrangements will inevitably bring.
It also provides the manager of the registry a regulated
control over the budget without “deferring to the needs
of a larger group” as a supervisor of the registry said. In
addition, with fewer reporting levels, information flow
will be much more effcient, and has less chance of data
distortion and/or omission. Hospital administrators have
a more up-to-date awareness of the cancer program, which
enables them to provide financial and workforce support
when needed. Increased exposure of the cancer registry can
also lead to more frequent use of cancer data. Proper use of
information can increase the quality of cancer care provided
by an organization as well as increase the organization’s
competitiveness. This type of design, however, may not
207
work in hospitals that need to integrate their horizontal
differentiation.
All the above mentioned structural arrangements have
their pros and cons. The first 3 designs add an additional
reporting level in the organizational structure; therefore
it is more vertically differentiated than the last. While
vertical differentiation gives an organization more centralized control, the lengthened command chain slows down
communication between managers at the top and those at
the bottom of the organizational hierarchy.8 In the cancer
registry case, information that flows from the registry takes
longer to reach the top.
Conclusion
Placement of cancer registries reflects the strength and
competitiveness of cancer services in a hospital. Currently,
only 30% of hospitals in the United States and Puerto Rico
have a CoC-accredited cancer program; however, they
diagnose and treat 70% of new cancer patients annually.6
The cancer registry and cancer registrars are the keys to
the success of cancer programs in those hospitals. In many
places, however, cancer registrars are not recognized by
their supervisors, administrators, or the cancer community
for the importance of the work they do.4
While hospitals without a CoC-accredited cancer
program may still keep the registry within the department
of health information management, others may start to
realize the limitations in their current structural design and
take steps to make changes.
Technology will further differentiate the cancer registry
field in the future. Abstractors and follow-up personnel will
have less or no involvement in a hospital’s cancer program
while others may branch out to become the administrators of their cancer program, clinical informatists or data
analysts.
208
References
1. National Cancer Registrars Association (NCRA). The Cancer Registry and
the Registrar (n.d.). [Brochure]. Available at: http://www.ncra-usa.org/
files/public/CRWhat.pdf. Accessed November 6, 2010.
2. Clive RE, Miller DS. Introduction to Cancer Registries. In: Hutchison
CL, Roffers SD, Fritz AG, eds. Cancer Registry Management-Principles &
Practice. National Cancer Registrars Association;1997:1-7.
3. Webb MA. Justifying Registry Operations. J Registry Manage.
2010;37:35-36.
4. Chapman SA, Lindler V, McClory V, Nielsen C, Dyer W. Frontline
Workers in Cancer Data Management: Workforce Analysis Study of the
Cancer Registry Field. National Cancer Registrars Association; 2006.
Available at: http://www.ncra-usa.org/files/public/execsum0506.pdf.
Accessed November 2010.
5. Shepherd A. Advanced Placement—The Effects of New CTR Education
Requirements. For the Record. May 2009;20(11):10.
6. American College of Surgeons. Cancer Program Standards 2012: Ensuring
Patient-Centered Care. Chicago, IL: American College of Surgeons;
2011:9.
7. National Cancer Registrars Association (NCRA). Cancer Registrar
FAQ. Available at: http://www.ncra-usa.org/i4a/‌p ages/‌i ndex.
cfm?pageid=3301#sub1. Accessed November 6, 2010.
8. Jones G. Basic Challenges of Organizational Design. Organizational
Theory, Design and Change. New Jersey: Pearson Education, Inc;
2010:145.
Journal of Registry Management 2011 Volume 38 Number 4
Original Article
Embedding QR Codes in Tumor Board
Presentations, Enhancing Educational Content
for Oncology Information Management
Richard Siderits, MDa; Stacy Yatesb; Arelis Rodriguezb; Tina Leeb; Cheryl Rimmer, MDa; Mark Roche, MD, MMIc
Abstract: Quick Response (QR) Codes are standard in supply management and seen with increasing frequency in advertisements. They are now present regularly in healthcare informatics and education. These 2-dimensional square bar
codes, originally designed by the Toyota car company, are free of license and have a published international standard.
The codes can be generated by free online software and the resulting images incorporated into presentations. The images
can be scanned by “smart” phones and tablets using either the iOS or Android platforms, which link the device with the
information represented by the QR code (uniform resource locator or URL, online video, text, v-calendar entries, short
message service [SMS] and formatted text). Once linked to the device, the information can be viewed at any time after the
original presentation, saved in the device or to a Web-based “cloud” repository, printed, or shared with others via email or
Bluetooth file transfer. This paper describes how we use QR codes in our tumor board presentations, discusses the benefits,
the different QR codes from Web links and how QR codes facilitate the distribution of educational content.
Key words: QR code, tumor board, presentation, app, bar code
Introduction
The American College of Surgeons Commission on
Cancer requires hospital oncology information management programs to present and discuss malignancies with
incorporation of National Comprehensive Cancer Network
(NCCN) guidelines and American Joint Cancer Commission
(AJCC) staging. For our weekly tumor board presentations,
we use Microsoft PowerPoint to consolidate and present the
information from different departments within the hospital.
These PowerPoint presentations provide a suitable medium
for inserting images associated with the tumor board
discussion. This paper describes how we make and incorporate QR-code images into our tumor board presentations.
What exactly are QR codes? We see them everywhere
from digital billboards, magazines, store products, newspaper ads, and, increasingly, throughout health care. The
“QR” stands for Quick Response code and is a 2-dimensional bar code that can be scanned by most “Smart” phones
that use a QR-Scanning application. Originally designed
by the Toyota car company, QR use is free of license and is
published as an ISO standard. This means they can be used
in educational presentations without a license.
What can QR codes do? The list is expanding daily.
As of this writing, they can link to Internet addresses
including video, store up to 7k of formatted text, send short
message service (SMS) messages, store phone numbers,
make calendar appointments, show images or maps, and
access pre-run “MEDLINE” searches.
Why use QR codes in a tumor board presentation?
Using QR codes can dramatically increase the amount of
educational content that can be conveyed during a given
presentation. They can facilitate discussions relating to
cancer staging and oncology informatics standards. It is
possible to provide access to saved MEDLINE literature
searches, NCCN guidelines and oncology staging information. The convenience with which the audience member
can save this information into their smart phone or tablet
will also assure that this information remains available after
the presentation, thereby enabling the dissemination of the
information to a broader group.
How do we use them in our presentations? We generate
the QR codes using a free online QR code generator and
embed the code in PowerPoint slides for the tumor board.
If you have a very long URL, you can shorten it online
and paste the shorten version into the QR code generator.
Anyone in the audience can scan the code from their seats
and access the associated information. One QR code that
we include in every presentation is the link to our Tumor
Board Toolbox, which is an archive of all our tumor board
presentations since 2003 as well as the NCCN guidelines
How about presentation handouts? Although the audience can scan the QR codes from the projection screen
during the presentation, a handout that has QR codes and a
caption may also be utilized. The application running in the
smart phone or tablet scans the QR code and opens a link
in its browser which accesses the content. The link may be
saved in the phone, sent to a wireless printer, or emailed to
a contact in the phone. The accessed information can even
be saved into an online repository like “DropBox.” This
process only takes a few seconds.
__________
a
Robert Wood Johnson Medical School, New Brunswick, NJ. bRobert Wood Johnson University Health System Hamilton, Hamilton, NJ. cIntelligent Medical
Objects (IMO), Chicago, IL.
Address correspondence to Richard Siderits, MD, Associate Professor of Pathology, Robert Wood Johnson Medical School, New Brunswick, NJ. Email:
[email protected].
Journal of Registry Management 2011 Volume 38 Number 4
209
We also embed these codes into histology images of
the tumor. The QR code at the bottom of the image links the
user to a Web site of your choice. In our case, this is usually
a Web site relating to standards for processing and fixation
for malignancies, a reference database on immunohistochemical or molecular testing and interpretation.
How do I find the QR code scanner apps? Access the
Apple App store from an iPhone or the Android Market or
from an Android phone and enter “scan QR” into the search
field. This will return several free QR-scanning applications
that you can download into your phone and use for QR
scanning. Find one that appeals to you and give it a try.
Methods
We have detailed a step-by-step approach to making
and embedding QR codes in our tumor board presentations.
Procedure:
1. Decide which online resources you would like to link
with the QR codes to be embedded into the PowerPoint
presentation. One QR code that is always in the beginning of our tumor board presentations is one that links
our audience to the Tumor Board Toolbox archive.
2. Generate the QR code images with a free online QR
code generator (see Figure 1). In our case, we use http://
qrcode.kaywa.com/.
3. A logo in the center of the QR code may be designed.
The design should be small enough to not interfere
with the scan. We make the logos in PowerPoint or a
graphics program (see Figure 2).
4. To shorten the URL, we use http://tinyurl.com.
5. Copy the resulting QR code images from the generator
into memory.
6. Paste the QR code image into your PowerPoint tumor
board presentation. The QR code may be embedded
in the beginning of the presentation on it own slide or
may be embedded on top of a picture thus linking the
audience to more information during the presentation
(see Figure 3).
7.Make handouts of the presentation including the QR
codes.
Caveat: What if you want to place a logo for your
program or institution into your QR code? QR code can
tolerate a certain amount of “disruption” and still contain
the encoded information for scanning. From an informatics
point of view this depends on how many check symbols
the QR code retains after disruption. Theoretically, the
maximum number of QR symbols representing data that
can be deleted or replaced with a logo is about 50%. If
you look at a logo as representing incorrect data then the
practical size limit is about 30% of the central area of the
QR image.
In reality, there are 4 different correction levels (L, M,
Q, H) established as international standards for different
types of data. Level H can tolerate and correct up to 30%
disruptions without loss of integrity.
Discussion
This paper describes how we use QR codes in our
hospital based tumor board conferences. Our experience
210
suggests, from the learner’s perspective, that this is an easy
and effective way to incorporate more educational content
from various sources while allowing audience members
to conveniently access, acquire, manipulate, and share
this information at any time after the presentation. The
difference between QR codes and Web links is primarily
one of convenience for the user. It is unlikely for the user
to remember a long URL or type it into a browser from a
printed handout. Scanning a QR code, on the other hand, is
fast, convenient, and free while maintaining the information
for easy access and sharing in the future. There are several
easy-to-use free online QR code and several free QR-scanner
applications for both Android and iOS smart phones and
tablets. The scan times are usually less than 1 second and
the content are available instantly to the audience member.
This content can then be accessed during the presentation
or at a later time.
Handouts that include the QR codes are a quick way
to incorporate this material into the content. The benefit
to the educator is that of convenience and thoroughness.
Once generated, the codes can be used as an archive for
future presentations. It is possible to provide a broader
scope of resources and depth of material that is relevant to
the presentation by linking this information in a convenient
manner. Having the information readily available to the
learner also facilitates the dissemination of the information
beyond the presentation itself. In summary, we feel that this
technology is easy to use, free to use and can enhance tumor
board presentations.
References
1. A scalable distributed paradigm for multi-user interaction with tiled
rear projection display walls. IEEE Trans Vis Comput Graph. 2010;
Nov-Dec PubMed, NCBI, n.d. Available at: http://www.ncbi.nlm.nih.
gov/pubmed/20975205.
2. An introduction to QR Codes: linking libraries and mobile phones. Med
Ref Serv Q. 2011; PubMed, NCBI, n.d. Available at: http://www.ncbi.
nlm.nih.gov/pubmed/21800986.
3. Introducing QR codes: linking print and digital content via smartphone.
Neurosurgery. 2011; PubMed, NCBI, n.d. Available at: http://www.ncbi.
nlm.nih.gov/pubmed/21792106.
4. The QR code in society, economy and medicine—fields of application,
option and chances. Arch Kriminol. 2011; May-Jun PubMed, NCBI, n.d.
5. Borglum K. New characters on the block: quick response codes can
enhance patient communication, education, and marketing. Med Econ.
2011;88(17):S4-6
6.http://www.ncbi.nlm.nih.gov/pubmed/21805904
7.http://qrcode.kaywa.com/
8.http://mashable.com/2011/04/18/qr-code-design-tips/
9.http://tinyurl.com
Journal of Registry Management 2011 Volume 38 Number 4
Figure 1. Example of one free online QR-code generator.
Figure 3. The QR code will link to a specific Medline search
for “Struma ovarii and metastasis”. The panel on the right
shows the QR code embedded into a tumor board slide.
Figure 2. This QR code is the first slide in our tumor board
conference PowerPoint presentation.
Journal of Registry Management 2011 Volume 38 Number 4
211
How I Do It
The Blending of ICD-O-3 with SEER Inquiry (SINQ)
Antonio Bernal, RHIT, CTR
In my years of abstracting, I depended on the ICD-O-3
codebook. Abstracting at that time was not as complex as
it stands today. Histology codes were being updated and
cross-referenced.
I realize that I did not have enough space in the ICD-O-3
codebook to maintain these updates or my personal notes.
Nor did I have enough memory cells in my brain. In 2000,
I started creating an Adobe PDF version of the ICD-O-3
codebook while maintaining the integrity of the codebook’s
material. I intentionally omitted the alphabetic index; this
would have been repetitive during a search. Through the
years, the ICD-O-3 codebook became a useful resource in
various aspects of registry operations.
212
Updating of the ICD-O-3 sites and histologies in the
Adobe PDF file format provided the tools to insert new
codes, search, add notes or pop-up anchors, create bookmarks, and add references to the attachments.
The paper clip icon at the bottom section lists the
attachments of historically related Errata and Clarifications,
SEER Site Grouping Table, ICD-10 Screening Codes, etc. The
attachments are useful if a situation occurs when there is no
Internet access or quick informational access.
There are criteria defining the 5th-digit behavior code
and the 6th-digit histologic grading and differentiation
codes. The “5th-digit behavior code for neoplasms” and
“6th digit for immunophenotype designation for lymphoma
and leukemias” pages contain reference notes. Placing the
mouse/cursor over the green anchor pop-ups throughout
the ICD-O-3 codebook opens additional information
pertaining to the subject.
Journal of Registry Management 2011 Volume 38 Number 4
Adobe Acrobat allows searching either by code number
or text (site or histology). The search for “intravascular large
B” reveals the code is in red. All the Errata Corrections and
Updates along with the date of issue are also in red. The
green anchor pop-ups that appear in various areas contain
a SINQ reference(s) quotation that may require further
inquiries.
The reference number search method either by subject
or reference number is similar to the SINQ Inquiry System
Web site (http://seer.cancer.gov/seerinquiry/index.php).
The SEER Inquiry (SINQ) is monitored, and the updates are
ongoing.
Antonio Bernal is an independent cancer registry
contractor. Please send your comments or feedback to icdo@
sbcglobal.net.
References
1. Fritz A, Percy C, Jack A, et al. ICD-O-3 International Classification of
Disease for Oncology. 3rd ed. World Health Organization.
2. SEER Inquiry (SINQ); The SEER Data Quality Team, askSEERctr
[[email protected]].
3. California Cancer Reporting System Standard. Vol. 1.
The attachment (paper clip) section is opened to the
file “SINQ_1999 to 201110087_QA.pdf.” Any SINQ reference number that appears in the green anchor pop-ups is
typed in the Adobe search box (20100044), and the reference
is located for review.
Journal of Registry Management 2011 Volume 38 Number 4
213
Special Feature
Raising the Bar: It Matters
Michele Webb, CTR
Have you ever wondered if the work of the
cancer registrar really matters? If you’re like
me, you have had moments where you
were not entirely convinced. How could
data from one single hospital, across the
many hospitals in the United States,
or world, possibly make a difference?
But, it does matter and, even better,
YOU matter!
Not long ago I was in Forsythe,
Missouri with my mother visiting my
aunt in a rehabilitation facility. One
afternoon while chatting with my aunt
and her roommate, the physical therapist
dropped in to take my aunt to her therapy
session. My aunt invited us to go with her,
and so we all trooped off together and down
the hall.
During the session and in between giving my aunt
guidance on how to do her exercises, the physical therapist
began chatting. In addition to the usual questions about
where we lived, what brought us to that part of the country,
and so forth, she asked me what I did for a living. Of course,
I proudly replied that I was a cancer registrar. And, I was
not too surprised when the inevitable, “What’s that?” was
asked!
Happily I responded with a basic, 2-sentence description of what a cancer registrar is and does. To my surprise,
she responded by telling me that her mother was going in for
surgery the following morning for endometrial cancer. She
began talking about her mother’s experience throughout the
diagnostic process and how concerned she and her family
were, despite the physician’s reassurances that “everything
would be OK.” Her mother was to undergo a complete
hysterectomy and bilateral salpingo-oopherectomy with the
da Vinci robotic system early the next morning and she and
her mother were both a bit uncomfortable with the concept
of robotics.
What really caught my attention were her concerns
about whether her mother really had cancer or not, and
that she may not have had a full diagnostic work-up prior
to the surgery. She inquired as to what I thought about the
situation. Of course, I explained I was not a physician but
that there were established national patient care guidelines
that she could view and download online. She was immediately interested and I gave her the URL and information
for the patient version of the NCCN guidelines and other
resources. After returning my aunt to her room, we promised to keep the physical therapist and her mother in our
thoughts and prayers the following morning. Our visit
ended that evening and I returned home the following day.
As cancer registrars, we are in a perfect position, as
214
we interact with our family, friends and community, to share with others the value of our
work. We can also guide them to the
resources and educational information
they need to make informed decisions
about their diagnosis and care. In
my humble opinion, this has more
value, and brings us more reward,
than any other part of our work.
We are so blessed to be a member of
this profession and to make a positive impression on the communities
we serve.
I am reminded of a song Kristen
Chenoweth sings on her new album,
“Some Lessons Learned.” The song is
titled, “I Was Here.” If you don’t have the CD,
I highly recommend that you visit the YouTube
Web site and listen to the song and watch the video. While
written for music, the lyrics are powerful and can be used
by each of us to reconnect with our work and the passion
we have for it. I would like to share the lyrics here with you
now.
I Was Here
You will notice me
I’ll be leavin’ my mark like initials carved in an old oak
tree
Just wait and see
Maybe I’ll write like Twain wrote
Maybe I’ll paint like Van Gogh
Cure the common cold, I don’t know
But I’m ready to start ’cause I know in my heart
CHORUS
I wanna do somethin’ that matters, say somethin’ different
Somethin’ that sets the whole world on its ear
I wanna do somethin’ better with the time I was given
I wanna try
To touch a few hearts in this life
Leave nothing less than somethin’ that says
“I was here”
I will prove you wrong
If you think I’m all talk you’re in for a shock
’Cause this dream’s too strong and before too long
Maybe I’ll compose symphonies
Maybe I’ll fight for world peace
’Cause I know it’s my destiny
To leave more than a trace of myself in this place
Journal of Registry Management 2011 Volume 38 Number 4
CHORUS
I wanna do somethin’ that matters, say somethin’ different
Somethin’ that sets the whole world on its ear
I wanna do somethin’ that matters, say somethin’ different
Somethin’ that sets the whole world on its ear
I wanna do somethin’ that matters, say somethin’ different
Somethin’ that sets the whole world on its ear
I wanna do somethin’ better with the time I was given
I know that I will do more than just pass through this life
I’ll leave nothin’ less than somethin’ that says
“I was here”
Written by Victoria Shaw
Sung by Kristen Chenoweth, Album: Some Lessons Learned
Masterworks, Sony Music Entertainment, 2011
Journal of Registry Management 2011 Volume 38 Number 4
So, what do you want to accomplish as a cancer
registrar? Do you want to do something different? Do
you believe in your heart that the cancer registrar’s work
matters? I hope so. When we show up and are present and
passionate about our work, it does matter to cancer patients,
their families, friends and communities around the world.
Michele is an independent cancer registry consultant, speaker
and e-educator living in Rancho Cucamonga, California. Her
Web sites, http://www.RegistryMindset.com and http://www.
CancerRegistrar.com, offer the cancer registry community
mentoring and continuing education opportunities. She
welcomes your comments at [email protected].
215
Special Feature
Role of Cancer Liaison Physician Will Focus
on Quality under 2012 Standards
Standard 4.3, which became effective January 1, 2012,
provides that:
A Cancer Liaison Physician (CLP) serves in a leadership role within the cancer program and is responsible for
evaluating, interpreting and reporting the program’s performance using the National Cancer Data Base (NCDB) data.
The CLP reports the results of this analysis to the cancer
committee at least four times a year.
Responsibilities of the CLP
The primary responsibility of the CLP is to monitor,
interpret, and report their program’s performance using
National Cancer Data Base (NCDB) data and to use the
information to evaluate and improve the quality of care
their facility provides.
The CLP reports and discusses the facility’s performance and other facility-related data with the cancer
committee at least 4 times per year. A quality-related audit is
to be initiated for any metrics that fall below required levels
of compliance. Resources for quarterly reports include the
Cancer Program Practice Profile Reports (CP3R), the NCDB
Hospital Comparison Benchmark Reports, and NCDB
Survival Reports. Discussions related to facility performance are documented in the cancer committee minutes.
Secondary responsibilities of the CLP are:
•To report on Commission on Cancer (CoC) activities,
initiatives, and priorities to the cancer committee.
•To serve as liaison for the cancer program with the
American Cancer Society (ACS), and support referrals to
ACS services and resources preferably through a formal
collaborative plan between the facility and ACS.
•To be present during the CoC survey and meet with the
surveyor.
To familiarize the CLPs with their new role, the CoC
has developed a series of 5 brief webinars, which CLPs are
required to complete.
Webinar Topics
Orientation to the Cancer Liaison Physician Role: Focus on
Improving the Quality of Cancer Care (13 minutes)
This webinar is to orient the Cancer Liaison Physician
to their role. Dr. Bleznak, Chair of the Committee on Cancer
Liaison, describes the history of the Cancer Liaison Program
and the recommendations that originated from the 2009
Cancer Liaison Program Summit. He demonstrates how
the new direction for the CLP will promote added value to
the Commission on Cancer, the CLP, the cancer program,
and the patients. With the focus on quality improvement
the CLP will use his/her expertise to promote quality
care within his/her program. The responsibilities and
216
expectations are outlined and the plan for training and
evaluation discussed.
Becoming an American Cancer Society Liaison (8 minutes)
In this webinar, the Cancer Liaison Physician will
learn about the almost 100-year history of the relationship between the American College of Surgeons and the
American Cancer Society, and the history of the Cancer
Liaison Program. Information about the value of the
relationship between CoC-accredited programs and their
local American Cancer Society are outlined, including the
services that the American Cancer Society can offer the CLP
and his/her patients. The expectations of the CLP role as a
liaison to the American Cancer Society are presented.
How to Navigate the National Cancer Data Base Tools:
A Primer (12 minutes)
This webinar is a primer on the Commission on
Cancer’s CoC Datalinks and the National Cancer Data
Base tools. The presentation will instruct the CLP on how
to access the tools developed by the NCDB for use by
CoC-accredited cancer programs. The NCDB applications
will be briefly described and possible uses suggested.
Putting the National Cancer Data Base Tools to Work
(17 minutes)
What questions can be answered using the National
Cancer Data Base tools available to accredited cancer
programs? This Webinar will provide the CLP with samples
of questions that are important for cancer programs to have
answered and show how to use the NCDB tools to answer
them. Each of the tools and potential uses for them are
discussed which will help the CLP plan his/her reports to
their cancer committee.
Analyzing and Reporting Your Cancer Program’s Quality
Data (11 minutes)
This presentation provides the CLP with ideas for using
the tools to report to their cancer committee. Useful suggestions are given for the types of questions that the CLP may
pose to the cancer committee membership for thoughtful
consideration of program and practice trends and how they
may be impacting patient care in the program. Suggestions
include how to use the reports to promote the cancer
program and how to use benchmark reports to identify
patient migration patterns.
Registrars are encouraged to view the webinars with
their CLPs to better understand their new role and how to
navigate the NCDB quality reporting tools. Questions about
the CLP role can be directed to the Cancer Liaison Program
at [email protected].
Journal of Registry Management 2011 Volume 38 Number 4
CORRECT ANSWERS FOR Fall 2011
Journal of Registry Management Continuing Education Quiz
FREQUENCY AND DETERMINANTS OF MISSING DATA IN CLINICAL AND PROGNOSTIC
VARIABLES RECENTLY ADDED TO SEER
1. Cancer incidence and mortality observed for SEER areas are
generally consistent with those for the entire United States in all
of the following, except
a)age and sex distributions are comparable
b)SEER areas tend to be more affluent and more urban
c)SEER areas tend to be less affluent and more rural
d)cancer incidence trends for the SEER Program are generally
representative of those for the total United States
2. The primary goals of the Collaborative Staging (CS) System are
to
a)facilitate a mechanism for registries to collect more clinically
relevant data
b)eliminate duplicate data collection processes for staging
cancers
c)provide compatibility among the 3 major staging systems
d)all of the above
3. According to this study, the data collected with SSF may be of
limited use if information on a large proportion of cases is not
available in the source records used for data capture.
a)True
b)False
4. This study defined all of the following codes as “missing data”
except
a)000
b)080
c)888
d)099 or 999
5. According to Table 2: Frequency of missing data for CS SSF by
cancer site, the percent of missing data was highest for
a)Breast—Molecular Studies of Regional LN
b)Other Endocrine—WHO Grade Classification
c)Melanoma of Skin—LDH
d)Prostate—Pathologic Extension
7. Breast cancer cases examined revealed
a)5 of the 6 SSF showed a consistent decrease in the
proportion of missing data between 2004 and 2007
b)the reference group was more likely to have missing data for
most variables
c)cases from metropolitan areas were more likely to have
missing data compared to those that came from nonmetropolitan areas
d)the variable that showed the most improvement over time
was “Molecular Studies of Regional Lymph Nodes” (SSF5;
Breast)
8. Most of the recently added SSF are used to provide information
on
a)responsiveness to a specific treatment
b)resistance to a specific treatment
c)the likely future behavior of a tumor
d)all of the above
9. The search for determinants of missing data demonstrated
a)older patients are more likely to have incomplete
information
b)white patients were more likely to have missing data
compared to black patients
c)patients diagnosed in non-metropolitan areas had
consistently lower proportions of missing data compared to
those diagnosed in metropolitan areas
d)for most SSF there was no evidence of improvement in data
completeness between 2004 and 2007
10.According to the registrars’ reports, the main barrier to data
completeness is the
a)amount of time required to collect SSF data
b)experience of the registrar
c)availability of information in the medical records
d)reporting facility characteristics
6. Analyses for colorectal cancer demonstrated that only the
youngest age category was consistently associated with missing
data.
a)True
b)False
Journal of Registry Management 2011 Volume 38 Number 4
217
Journal of Registry Management Continuing Education Quiz—winter 2011
SURVEILLANCE OF US DEATHS RELATED TO MYELODYSPLASTIC SYNDROMES, AND THE
NEED FOR LINKAGES WITH CENTRAL CANCER REGISTRIEs
Quiz Instructions: The multiple choice or true/false quiz below is provided as an alternative method of earning CE credit hours.
Refer to the article for the ONE best answer to each question. The questions are based solely on the content of the article. Answer
the questions and send the original quiz answer sheet and fee to the NCRA Executive Office before the processing date listed on
the answer sheet. Quizzes may not be retaken nor can NCRA staff respond to questions regarding answers. Allow 4–6 weeks for
processing following the submission deadline to receive return notification of your completion of the CE process. The CE hour will
be dated when it is submitted for grading; that date will determine the CE cycle year.
After reading this article and taking the quiz, the participants will be able to:
• Compare and contrast prognosis and survival rates for the subgroups of Myelodysplastic syndromes (MDS)
• Identify problems associated with the surveillance of MDS mortality in comparison to most types of cancer
• Explain how the use of multiple causes of death improves estimation of the burden of MDS-related deaths
1. Myelodysplastic syndromes (MDS) may be described by
all of the following statements, except:
a)rarely diagnosed in children and young adults
b)a homogeneous group of clonal myeloid neoplasms
c)diagnosed most commonly in elderly persons
d)risk increases with rising age
2. MDS has been a reportable diagnosis since 2001.
a)True
b)False
3. MDS patients have high morbidity and mortality
from infections and bleeding because symptoms or
complications may include:
a)neutropenia, associated with increased risk of
infection
b)thrombocytopenia, associated with increased risk of
bleeding (hemorrhage)
c)both a and b above
d)neither a nor b above
4. Improving the estimation of the true burden of MDSrelated deaths in the U.S. population could enhance:
a)the utility of mortality surveillance data in cancer
epidemiology
b)cancer control
c)planning for research and treatment resources in an
“aging” population
d)all of the above
5. In ICD-10 (International Classification of Diseases
Version 10), MDS:
a)is coded under “D” for “neoplasms of uncertain or
unknown behavior”
b)is coded as malignant behavior
c)includes the subgroup with isolated deletion of the
long arm of chromosome 5
d)distinguishes “therapy-related” MDS (t-MDS)
218
6. Potential errors in the death certification process may
result from:
a)the high degree of familiarity of the certifying
physician or coroner with the clinical history of the
decedent
b)the difficulty in discerning the role of each specific
condition in causing death
c)taking the necessary time to properly complete the
certificate
d)all of the above
7. According to Table 1, in 2005-2006, age-standardized
rates (ASR) were higher in:
a)females than in males
b)African Americans/blacks or other groups than in
whites
c)non-Hispanics than Hispanics
d)the 55-64 age group than the 65-74 age group
8. According to Table 2, the most common underlying
cause of death coded among deaths with
myelodysplastic syndromes is:
a)cardiovascular system
b)diabetes mellitus
c)respiratory
d)malignant neoplasms
9. Death records may be used to identify high-risk
subgroups of MDS, since most MDS deaths are coded to
a specific MDS subgroup (Table 1).
a)True
b)False
10.Recent developments that may encourage more
diagnostic testing are related to
a)the approval of new drugs for MDS that offer promise
for improved survival
b)the increase in use of potentially curative allogenic
hematopoietic stem-cell transplants in elderly MDS
patients
c)a desire by clinicians to provide patients with
unexplained cytopenias access to effective treatments
for MDS
d)all of the above
Journal of Registry Management 2011 Volume 38 Number 4
Journal of Registry Management Continuing Education Quiz
Answer Sheet
Please print clearly in black ballpoint pen.
m.i.
First Name
Last Name
Address
Address
—
City
State/Province
NCRA Membership Number (MUST complete if member fee submitted)
Instructions: Mark your
answers clearly by filling in
the correct answer, like this ■
not like this . Passing score of
70% entitles one (1) CE clock
hour per quiz.
Zip Code/Postal Code
CTR Number
This original quiz answer sheet will not be graded, no CE credit will be
awarded, and the processing fee will be forfeited unless postmarked by:
May 4, 2012
Quiz Identification Number:
Please use black ballpoint pen.
1
A
B
2
A
B
3
A
B
C
D
4
A
B
C
D
5
A
B
C
D
6
A
B
C
D
7
A
B
C
D
8
A
B
C
D
9
A
B
10
A
B
C
D
3804
JRM Quiz Article:
SURVEILLANCE OF U.S. DEATHS RELATED TO MYELODYSPLASTIC SYNDROMES,
AND THE NEED FOR LINKAGES WITH CENTRAL CANCER REGISTRIES
Processing Fee:
Member $25
Nonmember $35
Payment is due with submission of answer sheet. Make check or money
order payable to NCRA. U.S. currency only. Do not send cash. No refund
under any circumstances. Please allow 4–6 weeks following the submission
deadline for processing.
Please check one:
C
D
Submit the original quiz
answer sheet only!
No photocopies will be accepted.
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Journal of Registry Management 2011 Volume 38 Number 4
Mail to:
NCRA Executive Office
JRM CE Quiz
1340 Braddock Place
Suite 203
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219
Index
Journal of
Registry Management
Volume 38, Spring 2011 to Winter 2011
Reviewer acknowledgement: JRM gratefully acknowledges the individuals who have served as manuscript reviewers or have otherwise assisted in the review process during the past year. Their wise counsel and contributions to the Journal have been most valued.
Multiple Author Index—Vol. 38 (2011)
A
Bernal, Antonio
Adamo, Peggy
Bernal A. The Blending of ICD-O-3 with SEER Inquiry (SINQ).
Winter;38(4):212-213.
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Almon, Lyn
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Altekruse, Sean F.
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Berryhill, Tammy Lynn
Berryhill TL. Interactive Learning Tool: Site-Specific Schema
Crossword Puzzles. Summer;38(2):102-104.
Berryhill TL. Interactive Learning Tool: Site-Specific Schema
Crossword Puzzles, Appendix: Crossword Puzzle Answer Keys.
Summer;38(2):110.
Block, Suzanne
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Bodurtha, Joann N.
B
Bailey, Marie
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Banasiak, James
Stewart AK, McNamara E, Gay EG, Banasiak J, Winchester DP.
The Rapid Quality Reporting System - A New Quality of Care
Tool for CoC-Accredited Cancer Programs. Spring;38(1):61-63.
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Buchanich, Jeanine M.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
C
Barzilay, Xuan
Calkins, Casey M.
Barzilay X. Maximize Cancer Registry Role and Data Utilization.
Winter;38(4):206-208.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
Bauer, Katrina
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
220
Canfield, Mark A.
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Journal of Registry Management 2011 Volume 38 Number 4
Carter, M. Asa
Landvogt L, Carter MA, Chiappetta V, Etheridge D, Stachon
K. The New Cancer Program Standards Pilot Project, 2011.
Fall;38(3):173-174
Cassidy, Laura D.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1)24-29.
Chapman, Derek A.
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Chen, Vivien W.
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Chiappetta, Vicki
Landvogt L, Carter MA, Chiappetta V, Etheridge D, Stachon
K. The New Cancer Program Standards Pilot Project, 2011.
Fall;38(3):173-174
Collins, Elaine N.
Collins EN. The Collaborative Stage Version 2 Data Validation
Project, 2010. Spring;38(1):39-60.
Collins, Julianne S.
Collins JS, Kirby RS. Timely Findings from Birth Defects
Surveillance Programs. Spring;38(1):3.
Correia, Jane A.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Cronk, Christine
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1)24-29.
Cunningham Michael A.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Journal of Registry Management 2011 Volume 38 Number 4
D
Devesa, Susan S.
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Dickie, Lois A.
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Douglas, Lynda
Douglas L, Stengel J, Madera M. The Importance of Learning
Collaborative Stage Coding. Fall;38(3):171-172.
Durkee, Charles T.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
Dykstra-Long, Gwendylen R.
Dykstra-Long GR. Conforming to Cancer Staging,
Prognostic Indicators and National Treatment Guidelines.
Winter;38(4):196-200.
E
Esmen, Nurtan A.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Etheridge, Debbie
Landvogt L, Carter MA, Chiappetta V, Etheridge D, Stachon
K. The New Cancer Program Standards Pilot Project, 2011.
Fall;38(3):173-174
Etheridge, Deborah
Etheridge D. Role of CLPs Will Focus on Quality under 2012
Standards. Winter;38(4):216.
Eziefule, Akwugo A.
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
F
Farag, Noha H.
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
221
Fleming, Steven
Griffin, Ann
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Fleissner, Mary Lou
H
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Hancock, Roger P.
Ford, Nancy
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Fritz, April
Fritz A. Is it Reportable? Spring;38(1):66-67.
Fufaa, Gudeta D.
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
G
Gay, Greer
Stewart AK, McNamara E, Gay EG, Banasiak J, Winchester DP.
The Rapid Quality Reporting System - A New Quality of Care
Tool for CoC-Accredited Cancer Programs. Spring;38(1):61-63.
German, Robert R.
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Goodman, Michael
Kim HM, Goodman M, Kim B, Ward KC. Frequency and
Determinants of Missing Data in Clinical and Prognostic
Variables Recently Added to SEER. Fall;38(3):120-131
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Gress, Donna
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
222
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Harris, Susan E.
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1)24-29.
Harrison, Denise
Roberson DC, Harrison D. Winter 2010 Continuing Education
Quiz Answers. Spring;38(1):68.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz. Spring;38(1):69.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz Answers. Summer;38(2):107.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz. Summer;38(2):109.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz Answers. Fall;38(3):175.
Roberson DC, Harrison D. Fall 2011 Continuing Education
Quiz. Fall;38(3):176.
Hoffman, George M.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
Hofferkamp, Jim
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Hopewood, Ian
Hopewood I. Analyzing Quality of Colorectal Cancer Care
Through Registry Statistics: A Small Community Hospital
Example. Summer;38(2):93-96.
Hsieh, Mei-Chin
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Journal of Registry Management 2011 Volume 38 Number 4
J
Jensen John N.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
Johnson, Carol Hahn
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Joshi, Viral
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
K
Kennedy, Kathleen J.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Kersschner, Joseph
Kleiner, David E.
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Knight, Karen
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
L
Lacey, Steven E.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Landvogt, Lisa
Landvogt L, Carter MA, Chiappetta V, Etheridge D, Stachon
K. The New Cancer Program Standards Pilot Project, 2011.
Fall;38(3):173-174.
Lee, Tina
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):
Lewis, Mary
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Kim, Brian
Lieberman, Frank S.
Kim HM, Goodman M, Kim B, Ward KC. Frequency and
Determinants of Missing Data in Clinical and Prognostic
Variables Recently Added to SEER. Fall;38(3):120-131.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Kim, Hye Mi
Kim HM, Goodman M, Kim B, Ward KC. Frequency and
Determinants of Missing Data in Clinical and Prognostic
Variables Recently Added to SEER. Fall;38(3):120-131.
M
Kirby, Russell S.
Madera, Martin
Collins JS, Kirby RS. Timely Findings from Birth Defects
Surveillance Programs. Spring;38(1):3.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Douglas L, Stengel J, Madera M. The Importance of Learning
Collaborative Stage Coding. Fall;38(3):171-172.
Journal of Registry Management 2011 Volume 38 Number 4
Marengo, Lisa
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
223
Marsh, Gary M.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
N
Namiak, Mary
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Martinez, Carla A.
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
McGlynn, Katherine A.
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
McNamara, Erica
Stewart AK, McNamara E, Gay EG, Banasiak J, Winchester DP.
The Rapid Quality Reporting System - A New Quality of Care
Tool for CoC-Accredited Cancer Programs. Spring;38(1):61-63.
Menck, Herman
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Mink, Pamela J.
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Mitchell, Michael E.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
Mulla, Zuber D.
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
Mulvihill, Linda
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Myles, Zachary M.
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
O
Oldham, Keith T.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
P
Pareti, Lisa A.
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Patzer, Rachel E.
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Pearson, Melissa
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Pelech, Andrew N.
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1)24-29.
Perkins, Carin
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Phillips, Jerri Linn
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Phillips, Joan L.
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
224
Journal of Registry Management 2011 Volume 38 Number 4
Polednak, Anthony P.
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
Polednak AP. US Death Rates from Myeloproliferative
Neoplasms, and Implications for Cancer Surveillance.
Summer;38(2):87-92.
R
Ramadhani, Tunu
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Ries, Lynn
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Rimmer, Cheryl
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Roberson, Deborah C.
Roberson DC, Harrison D. Winter 2010 Continuing Education
Quiz Answers. Spring;38(1):68.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz. Spring;38(1):69.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz Answers. Summer;38(2):107.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz. Summer;38(2):109.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz Answers. Fall;38(3):175.
Roberson DC, Harrison D. Fall 2011 Continuing Education
Quiz. Fall;38(3):176.
Roberson DC, Harrison D. Fall 2011 Continuing Education Quiz
Answers. Winter;38(4):217.
Roberson DC, Harrison D. Winter 2011 Continuing Education
Quiz. Winter;38(4):218.
Roche, Mark
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Rodriguez, Arelis
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Journal of Registry Management 2011 Volume 38 Number 4
S
Salemi, Jason L.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Sato, Thomas
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
Scheuerle, Angela
Scheuerle A. Clinical Differentiation of Patent Foramen Ovale
and Secundum Atrial Septal Defect: A Survey of Pediatric
Cardiologists in Dallas, Texas, USA. Spring;38(1):4-8.
Schrager, Justin
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Siderits, Richard
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Simpson, Pippa
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1)24-29.
Stachon, Karen
Landvogt L, Carter MA, Chiappetta V, Etheridge D, Stachon
K. The New Cancer Program Standards Pilot Project, 2011.
Fall;38(3):173-174.
Stengel, Janet
Douglas L, Stengel J, Madera M. The Importance of Learning
Collaborative Stage Coding. Fall;38(3):171-172.
Stewart, Andrew K.
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Stewart AK, McNamara E, Gay EG, Banasiak J, Winchester DP.
The Rapid Quality Reporting System - A New Quality of Care
Tool for CoC-Accredited Cancer Programs. Spring;38(1):61-63.
Stinchcomb, Dave
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
225
Swain, Lori
Watkins, Sharon M.
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA).
Summer;38(2):97-99.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
T
Webb, Michelle
Tanner, Jean Paul
Webb M. Raising the Bar: What is Your Strategy for the 21st
Century? Fall;38(3):169-170.
Webb M. Raising the Bar: It Matters! Winter;38(4):
Webb M. Raising the Bar: Rejuvenating the Cancer Registrar.
Spring;38(1):64.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Tassone, Channing
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
Thielke, Robert J.
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
Tlusty, Susan
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Tomita-Michell, Aoy
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1):24-29.
Wike, Jennifer
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Wilson, Reda J.
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Winchester, David P.
Stewart AK, McNamara E, Gay EG, Banasiak J, Winchester DP.
The Rapid Quality Reporting System - A New Quality of Care
Tool for CoC-Accredited Cancer Programs. Spring;38(1):61-63.
Wu, Manxia
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Y
Trentham-Dietz, Amy
Yates, Stacy
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
W
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115119.
Ward, Kevin C.
Kim HM, Goodman M, Kim B, Ward KC. Frequency and
Determinants of Missing Data in Clinical and Prognostic
Variables Recently Added to SEER. Fall;38(3):120-131
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
226
Youk, Ada O.
Journal of Registry Management 2011 Volume 38 Number 4
Key Word Index—Vol. 38 (2011)
Cancer Registries
Collins EN. The Collaborative Stage Version 2 Data Validation
Project, 2010. Spring;38(1):39-60.
Polednak AP. US Death Rates from Myeloproliferative
Neoplasms, and Implications for Cancer Surveillance.
Summer;38(2):87-92.
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
Anemia
Cancer Registry
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
A
AAJCC TNM Stage
App
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Asians
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Atrial Septal Defect
Scheuerle A. Clinical Differentiation of Patent Foramen Ovale
and Secundum Atrial Septal Defect: A Survey of Pediatric
Cardiologists in Dallas, Texas, USA. Spring;38(1):4-8.
Cancer Staging
Dykstra-Long GR. Conforming to Cancer Staging,
Prognostic Indicators and National Treatment Guidelines.
Winter;38(4):196-200.
Cancer Surveillance
Polednak AP. US Death Rates from Myeloproliferative
Neoplasms, and Implications for Cancer Surveillance.
Summer;38(2):87-92.
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
Capture-Recapture Method
B
Bar code
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
Capture-Recapture Sampling
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
Birth Certificate
Cardiology
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Scheuerle A. Clinical Differentiation of Patent Foramen Ovale
and Secundum Atrial Septal Defect: A Survey of Pediatric
Cardiologists in Dallas, Texas, USA. Spring;38(1):4-8.
Birth Defects
Case Ascertainment
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Census
C
Marengo L, Ramadhani T, Farag NH, Canfield MA. Should
Aggregate US Census Data Be Used as a Proxy for Individual
Household Income in a Birth Defects Registry? Spring;38(1):9-14.
Cancer Incidence
Central Nervous System Neoplasms
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115-119.
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115-119.
Journal of Registry Management 2011 Volume 38 Number 4
227
Cholangiocarcinoma
Continuing Education Quiz and Answers
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Roberson DC, Harrison D. Winter 2010 Continuing Education
Quiz Answers. Spring;38(1):68.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz. Spring;38(1):69.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz Answers. Summer;38(2):107.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz. Summer;38(2):109.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz Answers. Fall;38(3):175.
Roberson DC, Harrison D. Fall 2011 Continuing Education
Quiz. Fall;38(3):176.
Roberson DC, Harrison D. Fall 2011 Continuing Education Quiz
Answers. Winter;38(4):217.
Roberson DC, Harrison D. Winter 2011 Continuing Education
Quiz. Winter;38(4):218.
Classification
Scheuerle A. Clinical Differentiation of Patent Foramen Ovale
and Secundum Atrial Septal Defect: A Survey of Pediatric
Cardiologists in Dallas, Texas, USA. Spring;38(1):4-8.
Cleft Lip with and without Cleft Palate
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
Cleft Palate without Cleft Lip
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
D
Code
Databases
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
Cohort Study
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115-119.
Collaborative Stage Data Collection System
Collins EN. The Collaborative Stage Version 2 Data Validation
Project, 2010. Spring;38(1):39-60.
Colorectal Cancer Care
Hopewood I. Analyzing Quality of Colorectal Cancer Care
Through Registry Statistics: A Small Community Hospital
Example. Summer;38(2):93-96.
Congenital Abnormalities
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Congenital Anomalies
Data Collection
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Data Linkages
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Data Mapping
Collins EN. The Collaborative Stage Version 2 Data Validation
Project, 2010. Spring;38(1):39-60.
Data Quality
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Data Validation
Congenital Malformations
Disparities
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
228
Collins EN. The Collaborative Stage Version 2 Data Validation
Project, 2010. Spring;38(1):39-60.
Journal of Registry Management 2011 Volume 38 Number 4
E
L
Epidemiology
Leukemia
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
Ethnicity
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve the
Accuracy of Asian Race Code in Registry Data
Winter;38(4):190-195.
Ewing’s sarcoma
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
F
Falmouth Hospital
Hopewood I. Analyzing Quality of Colorectal Cancer Care
Through Registry Statistics: A Small Community Hospital
Example. Summer;38(2):93-96.
Lincoln-Petersen Model
Log-Linear Model
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
Long-Term Survival
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
M
Microscopic confirmation
H
Hearing Loss
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution of an
Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Hearing Screening
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Hepatocellular carcinoma
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
I
Income
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
J
Jet Engine Manfacturing
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine
Manufacturing Workers: V. Issues with the Analysis of NonMalignant Central Nervous System Neoplasms. Fall;38(3):115-119.
Journal of Registry Management 2011 Volume 38 Number 4
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Misclassification
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Mortality
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
Multiple Causes of Death
Polednak AP. US Death Rates from Myeloproliferative
Neoplasms, and Implications for Cancer Surveillance.
Summer;38(2):87-92.
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
Myeloproliferative Neoplasms
Polednak AP. US Death Rates from Myeloproliferative
Neoplasms, and Implications for Cancer Surveillance.
Summer;38(2):87-92.
Myelodysplastic syndromes
Polednak AP. Surveillance of U.S. deaths related to
myelodysplastic syndromes (MDS), and the need for linkages
with central registries. Winter;38(4):183-189.
229
N
National Program of Cancer Registries
German RR, Wike JM, Bauer KR, Fleming ST, TrenthamDietz A, Namiak M Almon L, Knight K, Perkins C. Quality
of Cancer Registry Data: Findings from CDC-NPCR’s Breast
and Prostate Cancer Data Quality and Patterns of Care Study.
Summer;38(2):75-86.
National Treatment Guidelines
Dykstra-Long GR. Conforming to Cancer Staging,
Prognostic Indicators and National Treatment Guidelines.
Winter;38(4):196-200.
O
Osteosarcoma
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Outcomes
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
P
Patent Foramen Ovale
Scheuerle A. Clinical Differentiation of Patent Foramen Ovale
and Secundum Atrial Septal Defect: A Survey of Pediatric
Cardiologists in Dallas, Texas, USA. Spring;38(1):4-8.
Patient Registries
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
Pediatric Oncology
Presentation
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Process Control
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Prognostic Indicators
Dykstra-Long GR. Conforming to Cancer Staging,
Prognostic Indicators and National Treatment Guidelines.
Winter;38(4):196-200.
Q
QR
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Quality Assessment
Hopewood I. Analyzing Quality of Colorectal Cancer Care
Through Registry Statistics: A Small Community Hospital
Example. Summer;38(2):93-96.
Quality Control
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Quality of Life
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
R
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Race
Pediatric Surgery
Registries
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3):138-143.
Preeclampsia
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
230
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data.
Winter;38(4):190-195.
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Journal of Registry Management 2011 Volume 38 Number 4
S
Title Index—Vol. 38 (2011)
Secondary Data Sources
A
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Socioeconomic Factor
Marengo L, Ramadhani T, Farag NH, Canfield MA.
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Statistical Comparison
Hopewood I. Analyzing Quality of Colorectal Cancer Care
Through Registry Statistics: A Small Community Hospital
Example. Summer;38(2):93-96.
Statistical Methods
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Surgery
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
Surveillance
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution
of an Integrated Public Health Surveillance System.
Spring;38(1):15-23.
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
T
Thrombosis
Polednak AP. US Death Rates from Myeloproliferative
Neoplasms, and Implications for Cancer Surveillance.
Summer;38(2):87-92.
Trends
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Tumor Board
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Journal of Registry Management 2011 Volume 38 Number 4
Analyzing Quality of Colorectal Cancer Care Through
Registry Statistics: A Small Community Hospital Example
Hopewood I. Analyzing Quality of Colorectal Cancer Care
Through Registry Statistics: A Small Community Hospital Example. Summer;38(2):93-96.
Assessment of Completeness of Reporting of Oro-facial
Cleft Cases in Arizona Using the Capture-Recapture Method
Fufaa GD, Joshi V. Assessment of Completeness of Reporting of
Oro-facial Cleft Cases in Arizona Using the Capture-Recapture
Method. Fall;38(3):132-137.
C
Clarification From the CoC, NPCR, SEER Technical
Workgroup
Johnson CH, Phillips JL, Stewart AK, Lewis M, Phillips JL, Adamo
P, Ries L, Stinchcomb D. Clarification From the CoC, NPCR,
SEER Technical Workgroup. Fall;38(3):166-168.
Clinical Differentiation of Patent Foramen Ovale and Secundum Atrial Septal Defect: A Survey of Pediatric Cardiologists in Dallas, Texas, USA.
Scheuerle A. Clinical Differentiation of Patent Foramen Ovale
and Secundum Atrial Septal Defect: A Survey of Pediatric Cardiologists in Dallas, Texas, USA. Spring;38(1):4-8.
Conforming to Cancer Staging, Prognostic Indicators and
National Treatment Guidelines.
Dykstra-Long GR. Conforming to Cancer Staging, Prognostic Indicators and National Treatment Guidelines. Winter;38(4):196-200.
Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry
Cassidy LD, Jensen JN, Durkee CT, Calkins CM, Sato T, Tassone
C, Kerschner J, Thielke RJ, Mitchell ME, Hoffman GM, Oldham
KT. Creation and Implementation of a Prospective Pediatric
Clinical Outcomes Registry. Fall;38(3) 138-143.
E
Embedding QR codes in Tumor Board presentations,
enhancing educational content for Oncology Information
Management.
Siderits R, Yates S, Rodriguez A, Lee T, Rimmer C, Roche M.
Embedding QR codes in Tumor Board presentations, enhancing
educational content for Oncology Information Management.
Winter;38(4):209-210.
Evolution of an Integrated Public Health Surveillance
System.
Chapman DA, Ford N, Tlusty S, Bodurtha JN. Evolution of an Integrated Public Health Surveillance System. Spring;38(1):15-23.
231
Exploring the Environmental and Genetic Etiologies of
Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry.
M
Maximize Cancer Registry Role and Data Utilization.
Harris SE, Cronk C, Cassidy LD, Simpson P, Tomita-Mitchell A,
Pelech AN. Exploring the Environmental and Genetic Etiologies
of Congenital Heart Defects: The Wisconsin Pediatric Cardiac
Registry. Spring;38(1)24-29.
Barzilay X. Maximize Cancer Registry Role and Data Utilization.
Winter;38(4):206-208.
F
Preeclampsia Mortality in Texas: A Capture-Recapture
Analysis
Fall 2011 Continuing Education Quiz
Eziefule AA, Martinez CA, Mulla ZD. Preeclampsia Mortality in
Texas: A Capture-Recapture Analysis. Fall;38(3):150-152.
Roberson DC, Harrison D. Fall 2011 Continuing Education
Quiz. Fall;38(3):176.
Fall 2011 Continuing Education Quiz Answers
Roberson DC, Harrison D. Fall 2011 Continuing Education Quiz
Answers. Winter;38(4):217.
Frequency and Determinants of Missing Data in Clinical and
Prognostic Variables Recently Added to SEER.
P
Q
Quality of Cancer Registry Data: Findings from CDCNPCR’s Breast and Prostate Cancer Data Quality and Patterns of Care Study
Kim HM, Goodman M, Kim B, Ward KC. Frequency and Determinants of Missing Data in Clinical and Prognostic Variables
Recently Added to SEER. Fall;38(3):120-131
German RR, Wike JM, Bauer KR, Fleming ST, Trentham-Dietz
A, Namiak M Almon L, Knight K, Perkins C. Quality of Cancer
Registry Data: Findings from CDC-NPCR’s Breast and Prostate Cancer Data Quality and Patterns of Care Study. Summer;38(2):75-86.
H
R
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries.
Raising the Bar: It Matters!
Altekruse SF, Devesa SS, Dickie LA, McGlynn KA Kleiner DE.
Histological classification of liver and intrahepatic bile duct
cancers in SEER registries. Winter;38(4):201-205.
Raising the Bar: Rejuvenating the Cancer Registrar.
I
Webb M. Raising the Bar: It Matters! Winter;38(4):214-215.
Webb M. Raising the Bar: Rejuvenating the Cancer Registrar.
Spring;38(1):64.
Raising the Bar: What is Your Strategy for the 21st Century?
Interactive Learning Tool: Site-Specific Schema Crossword
Puzzles
Webb, M. Raising the Bar: What is Your Strategy for the 21st
Century? Fall;38(3):169-170.
Berryhill TL. Interactive Learning Tool: Site-Specific Schema
Crossword Puzzles. Summer;38(2):102-104.
Role of CLPs Will Focus on Quality under 2012 Standards.
Interactive Learning Tool: Site-Specific Schema Crossword
Puzzles. Appendix: Crossword Puzzle Answer Keys
Berryhill TL. Interactive Learning Tool: Site-Specific Schema
Crossword Puzzles, Appendix: Crossword Puzzle Answer Keys.
Summer;38(2):110.
Is it Reportable?
Fritz A. Is it Reportable? Spring;38(1):66-67.
L
Long-Term Health Experience of Jet Engine Manufacturing
Workers: V. Issues with the Analysis of Non-Malignant
Central Nervous System Neoplasms
Buchanich JM, Youk AO, Marsh GM, Kennedy KJ, Lacey SE,
Hancock RP, Esmen NA, Cunningham MA, Lieberman FS,
Fleissner ML. Long-Term Health Experience of Jet Engine Manufacturing Workers: V. Issues with the Analysis of Non-Malignant
Central Nervous System Neoplasms. Fall;38(3):115-119.
232
Etheridge D. Role of CLPs Will Focus on Quality under 2012
Standards. Winter;38(4):216.
S
Should Aggregate US Census Data Be Used as a Proxy for
Individual Household Income in a Birth Defects Registry?
Marengo L, Ramadhani T, Farag NH, Canfield MA. Should
Aggregate US Census Data Be Used as a Proxy for Individual Household Income in a Birth Defects Registry?
Spring;38(1):9-14.
Spring 2011 Continuing Education Quiz.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz. Spring;38(1):69.
Spring 2011 Continuing Education Quiz Answers.
Roberson DC, Harrison D. Spring 2011 Continuing Education
Quiz Answers. Summer;38(2):107.
Journal of Registry Management 2011 Volume 38 Number 4
Summer 2011 Continuing Education Quiz.
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz. Summer;38(2):109.
Summer 2011 Continuing Education Quiz Answers
Roberson DC, Harrison D. Summer 2011 Continuing Education
Quiz Answers. Fall;38(3):175.
Surveillance of U.S. deaths related to myelodysplastic
syndromes (MDS), and the need for linkages with central
registries.
Polednak AP. Surveillance of U.S. deaths related to myelodysplastic syndromes (MDS), and the need for linkages with central
registries. Winter;38(4):183-189.
Survival Outcomes of Pediatric Osteosarcoma and Ewing’s
Sarcoma: A Comparison of Surgery Type within the SEER
Database, 1988-2007.
Schrager J, Patzer RE, Mink PJ, Ward KC, Goodman M. Survival
Outcomes of Pediatric Osteosarcoma and Ewing’s Sarcoma: A
Comparison of Surgery Type within the SEER Database, 19882007. Fall;38(3):153-161.
T
The Rapid Quality Reporting System - A New Quality of
Care Tool for CoC-Accredited Cancer Programs.
Stewart AK, McNamara E, Gay EG, Banasiak J, Winchester DP.
The Rapid Quality Reporting System - A New Quality of Care
Tool for CoC-Accredited Cancer Programs. Spring;38(1):61-63.
The Relative Contribution of Data Sources to a Birth Defects
Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment
Net Lead to Overall or Disproportionate Loss?
Salemi JL, Tanner JP, Block S, Bailey M, Correia JA, Watkins SM,
Kirby RS. The Relative Contribution of Data Sources to a Birth
Defects Registry Utilizing Passive Multi-Source Ascertainment
Methods: Does a Smaller Birth Defects Case Ascertainment Net
Lead to Overall or Disproportionate Loss? Spring;38(1):30-38.
Timely Findings from Birth Defects Surveillance Programs.
Collins JS, Kirby RS. Timely Findings from Birth Defects Surveillance Programs. Spring;38(1):3.
U
US Death Rates from Myeloproliferative Neoplams, and
Implications for Cancer Surveillance
Textbook Development at the National Cancer Registrars
Association (NCRA)
Polednak AP. US Death Rates from Myeloproliferative Neoplasms, and Implications for Cancer Surveillance. Summer;38(2):87-92.
Menck HR, Gress DM, Griffin A, Mulvihill L, Hofferkamp J,
Johnson CH, Pearson M, Swain L. Textbook Development
at the National Cancer Registrars Association (NCRA). Summer;38(2):97-99.
Using a Statistical Process Control Chart during the Quality
Assessment of Cancer Registry Data
The Blending of ICD-O-3 with SEER Inquiry (SINQ).
Bernal A. The Blending of ICD-O-3 with SEER Inquiry (SINQ).
Winter;38(4):212-213.
The Collaborative Stage Version 2 Data Validation Project,
2010.
Collins EN. The Collaborative Stage Version 2 Data Validation
Project, 2010. Spring;38(1):39-60.
Myles ZM, German RR, Wilson RJ, Wu M. Using a Statistical
Process Control Chart during the Quality Assessment of Cancer
Registry Data. Fall;38(3):162-165.
Using NAPIIA to Improve the Accuracy of Asian Race Code
in Registry Data.
Hsieh MC, Pareti LA, Chen VW. Using NAPIIA to Improve
the Accuracy of Asian Race Code in Registry Data. Winter;38(4):190-195.
The Importance of Learning Collaborative Stage Coding
W
Douglas L, Stengel J, Madera M. The Importance of Learning
Collaborative Stage Coding. Fall;38(3):171-172.
Winter 2011 Continuing Education Quiz
The New Cancer Program Standards Pilot Project, 2011
Roberson DC, Harrison D. Winter 2011 Continuing Education
Quiz. Winter;38(4):218.
Landvogt L, Carter MA, Chiappetta V, Etheridge D, Stachon
K. The New Cancer Program Standards Pilot Project, 2011.
Fall;38(3):173-174.
Journal of Registry Management 2011 Volume 38 Number 4
233
New Cancer
Program
Standards
ImPlemeNtatIoN BegINS
IN 2012: are You readY?
a patient-centered approach is at
the forefront of new accreditation
standards for hospital cancer
programs, released by the
Commission on Cancer (CoC)
of the american College of
Surgeons (aCS). “the changing
landscape of cancer patient care
motivated us to develop new
standards to directly address
patient concerns,” said Stephen
edge, md, FaCS, Chair of the
Commission on Cancer. “these
standards enhance the focus of
care so that it is much more than
a defined structure of clinical
treatment.”
the new CoC standards ensure
that key elements of quality
cancer care are provided to every
person with cancer who is treated
in a CoC-accredited facility
throughout their diagnosis and
treatment process, as well as
during psychosocial support, care
for cancer-related pain, palliative
care, and hospice care.
234
Order Your Printed Version ($50) at:
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Download for FREE Today at:
http://www.facs.org/cancer/coc/programstandards2012.html
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Journal of Registry Management 2011 Volume 38 Number 4
National Cancer Registrars Association
CALL FOR PAPERS
Topic:
1. Birth Defects Registries
2. Cancer Registries
Cancer Collaborative Stage
Cancer and Socioeconomic Status
History
3. Trauma Registries
4. Recruitment, Training, and Retention
5. Public Relations
The Journal of Registry Management, official journal of the National Cancer Registrars Association (NCRA), announces a call
for original manuscripts on registry methodology or research findings related to the above 5 subjects, and related topics.
Contributed manuscripts are peer-reviewed prior to publication.
Manuscripts of the following types may be submitted for publication:
1. Methodology Articles addressing topics of broad interest and appeal to the readership, including methodological
aspects of registry organization and operation.
2. Research articles reporting findings of original, reviewed, data-based research.
3. Primers providing basic and comprehensive tutorials on relevant subjects.
4. “How I Do It” Articles describe tips, techniques, or procedures for an aspect of registry operations that the author does
particularly well. The “How I Do It” feature in the Journal provides registrars with an informal forum for sharing strategies with colleagues in all types of registries.
5. Opinion papers/editorials including position papers, commentaries, essays, and interviews that analyze current or
controversial issues and provide creative, reflective treatments of topics related to registry management.
6. Bibliographies which are specifically targeted and of significant interest will be considered.
7. Letters to the Editor are also invited.
Address all manuscripts to: Vicki G. Nelson, MPH, RHIT, CTR, Editor-in-Chief, Journal of Registry Management, (770) 488-6490,
[email protected].
Manuscript submission requirements are given in “Information for Authors” found on the inside back cover of each Journal
and on the NCRA Web site at http://www.ncra-usa.org/jrm.
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Journal of Registry Management
INFORMATION FOR AUTHORS
Journal of Registry Management (JRM), the official journal of the National Cancer Registrars Association, invites submission of original manuscripts on topics related to management of
disease registries and the collection, management, and use of cancer, trauma, AIDS, and other disease registry data. Reprinting of previously published material will be considered for
publication only when it is of special and immediate interest to the readership. JRM encourages authorship by Certified Tumor Registrars (CTRs); special value is placed on manuscripts
with CTR collaboration and publication of articles or texts related to the registry profession. CTR continuing education (CE) credits are awarded; a published chapter or full textbook
article equals 5 CE hours. Other published articles or documents equal CE hours. All correspondence and manuscripts should be addressed to the Editor-in-Chief, Vicki Nelson, MPH,
RHIT, CTR at: [email protected], or at: CDC/NCCDPHP/DCPC/CSB, 4770 Buford Drive, MS K-53, Atlanta, GA 30341-3717, 770-488-6490 (office), 770-488-4759 (fax).
Manuscripts may be submitted for publication in the following categories: Articles addressing topics of broad interest and appeal to the readership, including Methodology papers
about registry organization and operation; Research papers reporting findings of original, reviewed, data-based research; Primers providing tutorials on relevant subjects; and “How I
Do It” papers are also solicited. Opinion papers/editorials including position papers, commentaries, and essays that analyze current or controversial issues and provide creative, reflective treatments of topics related to registry management; Letters to the Editor; and specifically-targeted Bibliographies of significant interest are invited.
The following guidelines are provided to assist prospective authors in preparing manuscripts for the Journal, and to facilitate technical processing of submissions. Failure to follow the
guidelines may delay consideration of your manuscript. Authors who are unfamiliar with preparation and submission of manuscripts for publication are encouraged to contact the
Editor for clarification or additional assistance.
Submission Requirements
Manuscripts. The terms manuscripts, articles, and papers are used synonymously herein. E-mail only submission of manuscripts is encouraged. If not feasible, submit the original manuscript and 4 copies to the Editor. Manuscripts should be double-spaced on white 8-1/2” x 11” paper, with margins of at least 1 inch. Use only letter-quality printers; poor quality copies
will not be considered. Number the manuscript pages consecutively with the (first) title page as page one, followed by the abstract, text, references, and visuals. The accompanying cover
letter should include the name, mailing address, e-mail address, and telephone number of the corresponding author. For electronic submission, files should be 3-1/2”, IBM-compatible
format in Corel WordPerfect™, Microsoft® Word for Windows®, or converted to ASCII code.
Manuscripts (Research Articles). Articles should follow the standard format for research reporting (Introduction, Methods, Results, Discussion, References), and the submission instructions outlined above. The introduction will normally include background information, and a rationale/justification as to why the subject matter is of interest. The discussion often
includes a conclusion subsection. Comprehensive references are encouraged., as are an appropriate combination of tables and figures (graphs).
Manuscripts (Methodology/Process Papers). Methodology papers should follow the standard format for research reporting (Introduction, Methods, Results, Discussion), or for explanatory papers not reporting results (Introduction, Methods, Discussion), as well as the submission instructions outlined above.
Manuscripts (“How I Do It” articles). The “How I Do It” feature in the Journal provides registrars with a forum for sharing strategies with colleagues in all types of registries. These
articles describe tips, techniques, or procedures for an aspect of registry operations that the author does particularly well. When shared, these innovations can help registry professionals
improve their skills, enhance registry operations, or increase efficiency.
“How I Do It” articles should be 1,500 words or less (excepting references) and can contain up to 2 tables or figures. To the extent possible, the standard headings (Introduction, Methods,
Results, Discussion) should be used. If results are not presented, that section may be omitted. Authors should describe the problem or issue, their solution, advantages (and disadvantages) to the suggested approach, and their conclusion. All submitted “How I Do It” articles will have the benefit of peer/editorial review.
Authors. Each author’s name, degrees, certifications, title, professional affiliation, and email address must be noted on the title page exactly as it is to appear in publication. The corresponding author should be noted, with mailing address included. Joint authors should be listed in the order of their contribution to the work. Generally, a maximum of 6 authors for
each article will be listed.
Title. Authors are urged to choose a title that accurately and concisely describes the content of the manuscript. Every effort will be made to use the title as submitted, however, Journal
of Registry Management reserves the right to select a title that is consistent with editorial and production requirements.
Abstract. A brief abstract must accompany each article or research paper. The abstract should summarize the main point(s) and quickly give the reader an understanding of the manuscript’s content. It should be placed on a page by itself, immediately following the title page.
Length. Authors are invited to contact the Editor regarding submission of markedly longer manuscripts.
Style. Prepare manuscripts using the American Medical Association Manual of Style. 9th ed. (1998)
Visuals. Use visuals selectively to supplement the text. Visual elements—charts, graphs, tables, diagrams, and figures—will be reproduced exactly as received. Copies must be clear
and properly identified, and preferably e-mailed. Each visual must have a brief, self-explanatory title. Submit each visual on a separately numbered page at the end of the manuscript,
following the references.
Attribution. Authors are to provide appropriate acknowledgment of products, activities, and support especially for those articles based on, or utilizing, registry data (including
acknowledgment of hospital and central registrars). Appropriate attribution is also to be provided to acknowledge federal funding sources of registries from which the data are obtained.
References. References should be carefully selected, and relevant. References must be numbered in order of their appearance in the text. At the end of the manuscript, list the references
as they are cited; do not list references alphabetically. Journal citations should include author, title, journal, year, volume, issue, and pages. Book citations should include author, title,
city, publisher, year, and pages. Authors are responsible for the accuracy of all references. Examples:
1. LeMaster PL, Connell CM. Health education interventions among Native Americans: A review and analysis. Health Education Quarterly. 1995;21(4):521–38.
2. Hanks GE, Myers CE, Scardino PT. Cancer of the Prostate. In: DeVita VT, Hellman S, Rosenberg SA. Cancer: Principles and Practice of Oncology, 4th ed. Philadelphia, PA: J.B. Lippincott
Co.; 1993:1,073–1,113.
Key words. Authors are requested to provide up to 5, alphabetized key words or phrases which will be used in compiling the Annual Subject Index.
Affirmations
Copyright. Authors submitting a manuscript do so on the understanding that if it is accepted for publication, copyright in the article, including the right to reproduce the article in all
forms and media, shall be assigned exclusively to NCRA. NCRA will not refuse any reasonable requests by the author(s) for permission to reproduce any of his or her contributions to the
Journal. Further, the manuscript’s accompanying cover letter, signed by all authors, must include the following statement: “We, the undersigned, transfer to the National Cancer Registrars
Association, the copyright for this manuscript in the event that it is published in Journal of Registry Management.” Failure to provide the statement will delay consideration of the manuscript.
It is the author’s responsibility to obtain necessary permission when using material (including graphs, charts, pictures, etc.) that has appeared in other published works.
Originality. Articles are reviewed for publication assuming that they have not been accepted or published previously and are not under simultaneous consideration for publication
elsewhere. If the article has been previously published or significantly distributed, this should be noted in the submission for consideration.
Editing
Journal of Registry Management reserves the right to edit all contributions for clarity and length. Minor changes (punctuation, spelling, grammar, syntax) will be made at the discretion of
the editorial staff. Substantive changes will be verified with the author(s) prior to publication.
Peer Review
Contributed manuscripts are peer-reviewed prior to publication, generally by 3 reviewers. The Journal Editor makes the final decision regarding acceptance of manuscripts. Receipt of
manuscripts will be acknowledged promptly, and corresponding authors will be advised of the status of their submission as soon as possible.
Reprints
Authors receive 5 complimentary copies of the Journal in which their manuscript appears. Additional copies of reprints may be purchased from the NCRA Executive Office.
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