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Blood First Edition Paper, prepublished online January 30, 2013; DOI 10.1182/blood-2012-09-454553
Time from diagnosis to intensive chemotherapy initiation does not adversely impact the outcome
of patients with acute myeloid leukemia
Running Head: Delay to chemotherapy in AML
Sarah Bertoli,1 Emilie Bérard,2,3,4 Françoise Huguet,1 Anne Huynh,1 Suzanne Tavitian,1 François
Vergez,5 Sophie Dobbelstein, 5 Nicole Dastugue,5 Véronique Mansat-De Mas, 2,5 Eric Delabesse,2,5
Eliane Duchayne,5 Cécile Demur,5 Audrey Sarry,1 Valérie Lauwers-Cances,3 Guy Laurent,
1,2
Michel
Attal,1,2 and Christian Récher *1,2
1
Service d’Hématologie, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31059
Toulouse, France.
2
Université Toulouse III Paul Sabatier, Toulouse, France.
3
Département d'Epidémiologie, Economie de la Santé et Santé Publique, Centre Hospitalier
Universitaire de Toulouse, Toulouse, France.
4
INSERM UMR 1027, Epidémiologie et analyses en santé publique : Risques, maladies chroniques et
handicaps, Faculté de médecine, 37 allées Jules Guesde, 31073 Toulouse, France.
5
Laboratoire d’Hématologie, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31059
Toulouse, France.
Corresponding author: Pr Christian Récher, Service d’Hématologie, CHU de Toulouse, Hôpital
Purpan, place du Dr Baylac, 31059 Toulouse cedex 9, France ; phone : +33561772078 ; fax :
+33561777541 ; email : [email protected].
Scientific Category: Clinical Trials and Observations – Myeloid Neoplasia
1
Copyright © 2013 American Society of Hematology
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Key point 1: The prognostic impact of time from diagnosis to treatment in AML is offset by other
factors such as age, secondary AML or genetic abnormalities.
Key point 2: Waiting a short period of time to characterize leukemias better and design adapted
treatments at diagnosis seems possible.
Abstract
In acute myeloid leukemia (AML), new strategies assess the potential benefit of genetically targeted
therapy at diagnosis. This implies waiting for laboratory tests and therefore a delay in initiation of
chemotherapy. We studied the impact of time from diagnosis to treatment (TDT) on overall survival,
early death and response rate in a retrospective series of 599 newly diagnosed AML patients treated
by induction chemotherapy between the years 2000 and 2009. The effect of TDT was assessed using
multivariate analysis. TDT was analyzed as a continuous variable using a specific polynomial function
to model the shape and form of the relationship. The median TDT was 8 days (IQR, 4-16) and was
significantly longer in patients with white blood cell count (WBC) less than 50 G/L (p<0.0001) and in
older patients (p=0.0004). In multivariate analysis, TDT had no impact on overall survival (p=0.4095)
as compared to age older than 60, secondary AML, WBC higher than 50 G/L, European LeukemiaNet
risk groups and ECOG performance status. Furthermore, TDT was not associated with response rate
and early death. Thus, waiting a short period of time for laboratory tests to characterize leukemias
better and design adapted therapeutic strategies at diagnosis seems possible.
2
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Introduction
Acute myeloid leukemia (AML) is a disease induced by the oncogenic transformation of myeloid
progenitors, which leads to bone marrow failure and related complications including severe
infections, anemia or bleeding. From both a clinical and genetic point of view, AML is very
heterogeneous.1-2 The clinical presentation may vary from moderate and well-tolerated cytopenias to
highly proliferative states with extramedullary involvement that are sometimes complicated by
severe coagulopathy, leukostasis or metabolic disturbances requiring immediate therapeutic
intervention. Moreover, the increasing knowledge of AML biology has led to the establishment of the
2008 WHO classification, which is a mix between morphologic features and recurrent cytogenetic or
molecular abnormalities.3 An international expert panel from the European LeukemiaNet (ELN) has
also recently proposed new guidelines for the management and stratification of therapies based on
the strongest prognostic factors identified to date such as cytogenetic or molecular defects. 4 Many
groups now stratify the indication of allogeneic stem-cell transplantation according to genetic
subgroups: patients with AML1-ETO or CBFb-MYH11 rearrangement and patients with favorable
genotype (i.e., NPM1 or CEBPA mutation without FLT3-ITD mutation) are no longer referred to
allogeneic stem-cell transplantation in first complete response. 5 Besides, therapies targeting some
specific molecular defects are being developed, such as small molecule inhibitors of the FLT3 kinase
in patients harboring the FLT3-ITD mutation and all-trans retinoic acid in patients with NPM1
mutation.6-7 Some study groups have recently designed clinical trials in which patients are stratified
at diagnosis according to chromosomal abnormalities but also to specific gene mutations. 8-9 Thus,
there is a common trend to characterize better AML subtypes as soon as the diagnosis is made to
stratify tailored therapies earlier in the treatment course. This is also exemplified by the subgroup of
patients with monosomal karyotype, who share such a dismal outcome with standard treatment,
including transplantation that new approaches are specificically needed for them. 10-11
3
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The morphologic diagnosis of AML can be easily made in a few hours but the results of cytogenetic
analyses are not available before at least one week. This period could be even longer for some
molecular analyses, although the most frequent markers such as NPM1 and FLT3-ITD mutations
could be obtained in a few days. Thus, there is a dilemma between the potential benefit of
genetically targeted therapy early at diagnosis and the risk of delaying the initiation of
chemotherapy. This fear has been recently addressed by two North American centers in a
retrospective study showing that the time from diagnosis to treatment (TDT) independently
predicted survival in younger but not older patients. 12 In that study, response rate and overall
survival were worsened after a treatment delay of five days. On the basis of these results, it is
commonly admitted that treatment of younger AML patients should be started with minimal delay. 4
Because of limited capacity for the admission of patients in our unit and hypothesizing that many of
them probably have had a TDT longer than five days, our objectives were to assess the effect of TDT
on overall survival, early death and complete response in a retrospective cohort of 599 patients with
AML treated by intensive chemotherapy between 2000 and 2009.
4
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Methods
Study population and treatment
The leukemia unit of the University Hospital in Toulouse is the only certified center for the treatment
of acute leukemias in the Midi-Pyrénées region (3 million inhabitants). Patients are referred by
personal physicians or primary care centers and are first seen by leukemia specialists either as
outpatients for rapid diagnosis and work-up or directly as inpatients if urgent medical interventions
are needed. Data are recorded each week according to guidelines from the Oncomip network
(http://www.oncomip.org). Between Jan 1, 2000, and Dec 31, 2009, all consecutive patients with a
new diagnosis of AML (excepting acute promyelocytic leukemia) have been registered (N=1117) in
order to have a representative sample of a homogeneous management period. Among them, 474
were deemed unfit for intensive chemotherapy and were excluded from the study. We excluded
patients with a TDT longer than 90 days (n=18) and patients with incomplete biological data (n=26),
leading to a sample of 599 patients. Before doing any analysis, we assessed the power of the study.
In order to show a significant hazard ratio for overall survival of 1.4 or 1.5 for subjects with a TDT ≥ 5
days versus subjects with a TDT < 5 days (whose median survival time is considered to be equal to 48
weeks)12, for two-sided alpha log-rank test = 0.05 and for allocation ratio of 1:1, 1:1.5 and 1:2
(proportion of subjects with TDT < 5 days and TDT ≥ 5 days), 599 patients involved a power ≥ 0.80.
Informed consent was obtained from all patients in accordance with the Declaration of Helsinki. This
study was approved by the institutional review board (Ethical Committee of Research) (N° 20-0511).
Patients were treated by intensive induction chemotherapy as part of, or according to BGMT,
GOELAMS, GFM or French CBF Intergroup protocols. 9,13-15 Gemtuzumab ozogamycin (n=18), imatinib
(n=5), lenalidomide (n=3) and cloretazine (n=2) were occasionally added. Responding patients with
HLA-identical sibling (except patients with Core Binding Factor-AML) were allocated to allogeneic
stem-cell transplantation (alloSCT). Patients with no HLA-identical sibling received a consolidation
regimen based on high-dose cytarabine (HDAC, 10 to 24 g/m 2) then autologous stem-cell
5
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transplantation or three courses of HDAC. Since 2008, patients with favorable genotype were no
longer allocated to alloSCT. After achieving complete response, patients over 60 received
maintenance therapy with idarubicin and low-dose cytarabine. The cytogenetic and molecular risk
classifications were in accordance with the Medical Research Council (MRC) and ELN classifications,
respectively.4,16 Retrospective analyses of molecular abnormalities were performed from samples
stored in the HIMIP tumor bank of the U1037 Inserm department (n°DC-2008-307-CPTP1 HIMIP). 17
Pretreatment characteristics at diagnosis (age, gender, ECOG performance status 18, secondary AML
(sAML), extramedullary involvement including splenomegaly, hepatomegaly, lymphadenopathies,
leukemic gingival or cutaneous infiltration, leukostasis, infection, white blood cell (WBC), platelet
counts, fibrinogen level) were collected in medical files by S.B, A.S and C.R.
Statistical analysis
Statistical analysis was performed on STATA statistical software, release 11.2 (STATA Corporation,
College station, TX, USA). We described patients’ characteristics using number and frequency for
qualitative data and median, Inter-Quartile Range (IQR) and range for quantitative data. We then
compared TDT according to baseline characteristics using Mann-Whitney’s or Kruskall-Wallis’s test.
TDT was defined as the number of days between diagnosis in Toulouse University Hospital and
chemotherapy initiation (n=491) or the number of days between first bone marrow aspirate and
chemotherapy initiation if the first bone marrow aspirate leading to diagnosis had been made out of
the Toulouse University Hospital (n=108). The primary endpoint of the study was overall survival. For
each participant, the length of follow-up corresponds to the period between the date of diagnosis
and May 31, 2011 or the date of death if the patient died during the study period. The response to
treatment was usually evaluated after full hematological recovery (e.g, when neutrophils and platelet
counts were > 1 G/L and > 100 G/L to document complete responses) or at day 35 in case of
prolonged aplasia and was defined according to the international consensus criteria as complete
response (CR) or complete response with incomplete blood count recovery (CRi). 19 Early death was
defined as death from any cause occurring between the start of chemotherapy and the response
6
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assessment. Differences in survival functions were tested using the Log-Rank test; differences in
response rate and early death were compared between groups using the χ2-test (or Fisher’s exact
test in case of small expected numbers). Multivariate analysis of response rate and early death was
conducted using logistic regression and using a Cox model for overall survival. Since the linearity
hypothesis was not fully respected, the following continuous variables were transformed into
ordered data: age (≤ 60 and > 60), WBC (≤ 50 G/L and > 50 G/L). To avoid the loss of information and
the reduction in power, which will be introduced by the categorization of TDT, and to deal with the
supposed non-linearity in the relationship between outcomes and TDT, we explored the relationship
between TDT and outcomes using restricted cubic spline (RCS). 20-23 RCS is a polynomial function that
is piecewise defined into pre specified adjacent intervals as recommended by Harrell et al. 22 The
proportional-hazard assumption was tested for each covariate of the Cox model by the “log-log” plot
method curves ((-ln{-ln(survival)}), for each category of nominal covariate, versus ln(analysis time)).
None of the assumptions could be rejected. Multivariate analyses initially included TDT together with
potential confounding factors. Then we used a stepwise regression to assess variables that were
significantly and independently associated with endpoints (P-value < 0.05). The time period effect
was tested in all analyses. Interactions between TDT and the independent covariates (in particular
interactions with age, WBC or type of consolidation treatment) were tested in final logistic and
survival models. We also conducted a sensitivity analysis for TDT defined as the number of days
between diagnosis in Toulouse University Hospital and chemotherapy initiation using the same
methodology. All reported p-values were two-sided and the significance threshold was < 0.05.
7
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Results
Patients
The characteristics of the 599 patients and the comparison of TDT according to these characteristics
are presented in table 1. The median age at diagnosis was 58 years old (range, 16 to 83 years; IQR 4568), 60% of the patients were 60 years of age or younger (“younger patients”) and 54% were male.
The percentage of patients with sAML was 20% and 22% had WBC > 50 G/L. According to the MRC
classification, 10%, 66%, and 24% of patients, had favorable, intermediate and adverse karyotypes,
respectively. The induction chemotherapy regimens were homogeneous since 94% of patients
received either daunorubicin (60 mg/m 2/d for three days) or idarubicin (8 mg/m 2/d for five days) in
combination with standard doses of cytarabine (100 or 200 mg/m 2/d for seven days according to
age). The therapeutic course of all patients is shown in figure 1.
Variables affecting the TDT
The median TDT was 8 days (IQR 4-16). Notably, 378 patients (63%) had a TDT longer than five days.
The median TDT was significantly longer in patients with WBC less than 50 G/L (9 days; IQR 5-20 vs 2
days; IQR 1-4 if WBC > 50 G/L, p<0.0001) and in older patients (9 days; IQR 4-23 vs 7 days; IQR 3-14
in younger patients, p=0.0004). TDT was significantly longer in the 2006-2009 period as compared to
the 2000-2005 period (9 days; IQR 5-19 vs 7 days; IQR 3-14, p<0.0001). In the 378 patients who
received chemotherapy more than five days after the diagnosis, the main causes leading to a delayed
treatment were diagnosis out of Toulouse University Hospital (25%), waiting for cytogenetics (11%),
diagnosis out of the leukemia unit (12%), infection (7%) or other less common reasons (Table 2). The
cause of delay could not be identified in 50% of cases.
TDT and overall survival
The median follow-up of the cohort was 71 months. Between Jan 1, 2000, and May 31, 2011, 397
deaths (66%) were recorded, 206 (58%) and 191 (79%) in younger and older patients, respectively.
8
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The median overall survival was 17.9 months (26.1 and 12.1 in younger and older patients,
respectively). Variables associated with OS in univariate analysis are shown in table 3. As shown in
Figure 2A, the non-adjusted risk of death according to TDT is U-shaped with a nadir to day 6. Subjects
with a TDT lower than 3 days and equal to 16 to 31 days had a risk of death significantly higher than
subjects with a TDT equal to 6 days. However, after adjustment for age, sAML, WBC, ECOG
performance status, ELN risk groups and type of consolidation treatment, TDT was no longer
associated with OS (p=0.4095) (Figure 2B). In multivariate analysis, risk factors for shorter OS were
age older than 60 years (HR=1.36; 95% CI [1.08- 1.70]; p=0.008), sAML (HR=1.51; 95% CI [1.18-1.93];
p=0.001), WBC higher than 50 G/L (HR=1.59; 95% CI [1.18-2.15]; p=0.002), ELN risk groups (HR=2.29;
95% CI [1.61-3.24]; HR=2.79; 95% CI [1.98-3.94]; HR=3.86; 95% CI [2.69-5.55] for intermediate-I, -II
and adverse respectively as compared to favorable; p<0.001), ECOG performance status 1 or 2 vs 0
(HR=1.46; 95% CI [1.12-1.91]; p=0.006 and HR=1.76; 95% CI [1.22-2.53]; p=0.002, respectively).
Consolidation with autologous (HR=0.47; 95% CI [0.30-0.76]; p=0.002) or allogeneic stem-cell
transplantation (HR=0.63; 95% CI [0.45-0.88]; p=0.007) was significantly associated with a better OS.
Interactions between TDT and the independent covariates were not significant. TDT did not have an
impact on OS regardless of age (younger vs older). The effect of TDT on OS in younger and older
patients is shown in eFigures 1 and 2. After removing cytogenetics, ELN classification and type of
consolidation from the model to solely assess clinical factors known early at diagnosis (i.e., age,
sAML, WBC and ECOG performance status), TDT did not affect OS (p=0.6069). In order to illustrate
better the lack of impact of TDT on OS according to the cut-off of 5 days proposed by Sekeres et al.,
Kaplan-Meier curves are shown in figure 3 (the cut-off of 5 days implies a loss of information in the
description of the relationship between TDT and OS which is better shown in figure 2).
TDT, early deaths and response to therapy
Among the 397 deaths recorded during the follow-up, there were 58 early deaths. Variables
associated with early death in univariate analysis are shown in table 3. TDT was not significantly
9
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associated with early death, both in non-adjusted analysis (p=0.4134) and after adjustment for age (>
60 vs ≤ 60), ECOG performance status, sAML, ELN classification and WBC (> 50 G/L vs ≤ 50 G/L)
(p=0.1544) (Figure 4). Interactions between TDT and the independent covariates were not significant.
TDT did not have an impact on early death regardless of age (younger vs older). The effect of TDT on
early death in younger and older patients is shown in eFigure 3. CR or CRi was obtained in 432
patients (72%). Variables associated with response rate in univariate analysis are shown in table 3.
Interaction between TDT and age, as well as interaction between TDT and WBC being significant,
analyses were stratified from age (> 60 vs ≤ 60) and WBC (> 50 G/L vs ≤ 50 G/L). After adjustment for
ECOG performance status, sAML, ELN classification, TDT was not significantly associated with
response rate (p=0.5840 for younger patients with WBC ≤ 50 G/L; p=0.7127 for older patients with
WBC ≤ 50 G/L; p=0.8993 for younger patients with WBC > 50 G/L; p=0.9518 for older patients with
WBC > 50 G/L) (Figure 5). The sensitivity analysis considering TDT as the number of days between
diagnosis in Toulouse University Hospital and chemotherapy initiation did not change the results.
10
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Discussion
In this study, we did not find any harmful signal concerning the effect of time from diagnosis to
treatment on overall survival, early death and response rate, both in younger and older patients with
newly diagnosed AML treated by intensive chemotherapy. The prognostic impact of TDT, if any, was
offset by other more powerful prognostic factors such as age, secondary AML, cytogenetic and
molecular abnormalities. Our results contrast with those of Sekeres et al., who found that delaying
intensive chemotherapy more than five days after diagnosis could be detrimental for younger AML
patients.12 In our study, we found much less secondary AML (20% vs 45%) in both younger and older
patients even though the repartition of cytogenetic groups was comparable. The other main
difference resides in the chemotherapy regimen. For induction therapy, we have invariably used
daunorubicin (180 mg/m2) or idarubicin (40 mg/m2) in combination with standard-dose cytarabine. In
contrast, induction chemotherapies were variable in the Sekeres’ study with several modalities of
cytarabine
administration,
other
compounds
than
anthracyclines
(such
as
topotecan,
cyclophosphamide or clofarabine) used in combination with cytarabine and no description of the
dose of daunorubicin, which is crucial for complete response and overall survival. 24-25 Lastly, we have
no information on the modalities of consolidation therapies and the proportion of patients receiving
allogeneic stem-cell transplantation.
The current assertion that AML is an oncologic emergency is generally accepted. However, true early
emergencies such as coagulopathy, leukostasis with respiratory distress syndrome or tumor lysis
syndrome requiring specific therapy in the hours following diagnosis are not so frequent. In our
study, it may have concerned less than 10% of patients. The level of hyperleukocytosis is a
recognized factor of early death. However, not all patients with high WBC display the so-called
leukostasis syndrome, which is the most serious complication correlated to early death. The
incidence of pulmonary or central nervous system leukostasis is about 30% of patients with WBC
above 100 G/L. 26 Further, most patients with high WBC could respond well to oral hydroxyurea
11
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before starting induction chemotherapy. 27 Thus, we decided not to exclude those patients with WBC
more than 50 G/L as was the case in the Sekeres’ study. In our study, about a quarter of patients with
hyperleukocytosis received hydroxyurea for a median time of five days. Although the TDT was
shorter in those patients, some of them had a delayed TDT without apparent worse outcome.
Whether hydroxyurea could offer a short delay between diagnosis and initiation of chemotherapy
remains to be fully studied.
It was difficult to analyze exhaustively the factors that contributed to delay chemotherapy. First of
all, we must emphasize that the decision to postpone the initiation of intensive chemotherapy was
made by leukemia specialists in agreement with personal physicians, primary care centers and
patients. We acknowledge that if patients were just made to wait for several days without careful
analysis of their clinical presentations, the outcome could have been different. Since 2006, we have
been waiting for the results of cytogenetics before enrolling patients in prospective trials designed
for CBF, intermediate and high-risk AML. Thus, our cytogenetic laboratory has to report results within
five days. This could partly explain the difference in median TDT between the two periods. The time
period effect was tested in all analyses and was not significant. Several other points in the
organization of care need to be taken into account when assessing the TDT. Chemotherapy is usually
performed in tertiary care facilities most often located in big cities. Although this has not yet been
studied in AML, it implies unavoidable geographical inequalities towards access to care for patients
residing far from tertiary centers. We were able to determine that the median TDT for the 108
patients from the Midi-Pyrénées region who had a diagnosis before coming to our center was 16
days. The outcome of these patients did not differ from those diagnosed in the university hospital
(not shown). The organization of care also requires the placement of a central catheter or sperm
conservation for fertility sparing before chemotherapy exposure. Furthermore, as prognosis is
recognized to be poorer in elderly patients, both patients and physicians may also request time for
decision-making before choosing intensive chemotherapy. 28 Finally, early complications, such as
severe infections, could also delay chemotherapy initiation. Overall, a causal factor could not be
12
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identified in half of the cases and in fact, the main reason for delay in chemotherapy initiation must
have been the chronic overload of the leukemia unit.
It is unlikely that a randomized trial addressing the effect of TDT would be undertaken. Therefore,
studies from other centers relating their own experience are needed. Since personalized therapies
based on genetic features of AML are going to be developed, it is fundamental to have a clear vision
of the impact of TDT on the outcome of AML patients. Although AML remains an oncologic
emergency, our study suggests that, except for specific conditions, it does not seem unreasonable to
wait for specialized laboratory tests in order to characterize better leukemias and design new
therapeutic strategies.
Acknowledgements: We thank all the clinicians of the Oncomip Network who referred their patients,
all the nurses and other health care providers from the Hematology Department of Toulouse
University Hospital. We also thank Sarah Scotland and Karine Nguyen for the correction of the
manuscript.
Authorship contributions: S.B. collected and analyzed data; and wrote the paper; E.B. performed
statistical analysis and wrote the paper; F.H.; A.H. and G.L. treated patients; S.T.; F.V. collected data;
S.D.; N.D. performed cytogenetic studies; E.De. and V.d.M. performed molecular analysis; E.D.; C.D.
and V.d.M. performed cytologic analysis; A.S. collected data; V.L-C. managed statistical analysis and
corrected the paper; M.A. analyzed data; C.R. treated patients, collected and analyzed data, and
wrote the paper. All the authors checked the final version of the manuscript.
Disclosure of conflicts of interest : the authors declare no competing financial interests.
13
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Regression, and Survival Analysis. . In: Bickel PD, P.J. Fienberg, S.E. Gather, U. Olkin, I. Zeger, S. ed.
Springer Series in Statistics New York: Springer; 2001.
23.
Altman DG, Lausen B, Sauerbrei W, Schumacher M. Dangers of using "optimal" cutpoints in
the evaluation of prognostic factors. J Natl Cancer Inst . 1994;86(11):829-835.
24.
Fernandez HF, Sun Z, Yao X, et al. Anthracycline dose intensification in acute myeloid
leukemia. N Engl J Med. 2009;361(13):1249-1259.
25.
Lowenberg B, Ossenkoppele GJ, van Putten W, et al. High-dose daunorubicin in older patients
with acute myeloid leukemia. N Engl J Med. 2009;361(13):1235-1248.
26.
Marbello L, Ricci F, Nosari AM, et al. Outcome of hyperleukocytic adult acute myeloid
leukaemia: a single-center retrospective study and review of literature. Leuk Res. 2008;32(8):12211227.
27.
Grund FM, Armitage JO, Burns P. Hydroxyurea in the prevention of the effects of leukostasis
in acute leukemia. Arch Intern Med . 1977;137(9):1246-1247.
28.
Estey E. What is the optimal induction strategy for older patients? Best Pract Res Clin
Haematol. 2011;24(4):515-522.
15
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Table 1: Characteristics of the 599 patients with newly diagnosed AML and comparison of Time
from Diagnosis to Treatment (TDT) according to these characteristics
Total
n=599
Age - years
Median (Inter-Quartile Range)
Range
TDT (in days)
Median
(Inter-Quartile Range)
P*
0.0004
58 (45-68)
16-83
≤ 60
358 (60)
7 (3-14)
> 60
241 (40)
9 (4-23)
n
324/275
8(4-16)/8(3-17)
0.5595
%
54/46
0.0001
Male/Female
ECOG performance status - n (%)
0
173 (29)
11 (6-22)
1
196 (33)
8 (4-16)
2
65 (11)
8 (3-16)
20 (3)
5.5 (2-15)
145 (24)
5 (2-11)
No
477 (80)
11.5 (5-21)
Yes
122 (20)
8 (3-15)
No
357 (60)
9 (5-21)
Yes
151 (25)
6 (2-10)
91 (15)
5 (2-13)
No
488 (82)
8 (4-16)
Yes
79 (13)
8 (5-16)
32 (5)
4.5 (2-15.5)
3-4
Unknown
Secondary AML - n (%)
0.0037
Extramedullary involvement - n (%)
Unknown
0.0001
Infection at diagnosis - n (%)
Unknown
0.2325
Leukostasis - n (%)
No
562 (94)
8 (4-18)
Yes
21 (4)
1 (1-2)
Unknown
16 (3)
2 (1-6)
0.0001
White blood cell count - G/L
Median (Inter-Quartile Range)
10.1 (3.0-41.8)
Range
0.3-433
≤ 50
466 (78)
9 (5-20)
> 50
133 (22)
2 (1-4)
< 20 G/L
55 (9)
7 (3-12)
≥ 20 G/L
536 (90)
8 (4-17)
8 (1)
13 (4.5-29)
> 4 g/L
243 (41)
7 (3-15)
1.5 – 4 g/L
225 (38)
9 (5-18)
0.0001
Platelet count - n (%)
Unknown
0.2146
Fibrinogen - n (%)
< 1.5 g/L
Unknown
18 (3)
2.5 (1-4)
113 (19)
7 (4-21)
0.0001
Cytogenetics
Favorable - n (%)
61 (10)
6 (2-10)
Intermediate- n (%)
394 (66)
8 (3-16)
Adverse - n (%)
144 (24)
9 (5-20.5)
Favorable - n (%)
126 (21)
6 (3-10)
Intermediate-I - n (%)
168 (28)
8 (2-18)
0.0014
European LeukemiaNet
0.0001
16
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Intermediate-II - n (%)
161 (27)
9 (4-18)
Adverse - n (%)
144 (24)
9 (5-20.5)
TDT: time from diagnosis to treatment; Total percentages differ from 100% because of rounding.
* Mann-Whitney’s test for factors with 2 levels or Kruskall-Wallis’s test if more than 2 levels
17
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Table 2: Main causes leading to delay chemotherapy (TDT > 5 days)
Main cause
Total (n=378)
n (%)
Diagnosis out of Toulouse University
Hospital
93 (25)
Awaiting for cytogenetics
43 (11)
Diagnosis out of leukemia unit
44 (12)
Infection
28 (7)
Awaiting for complementary tests*
19 (5)
Comorbidities evaluation
10 (3)
Awaiting for central line
7 (2)
No symptom
3 (1)
AML-related initial complications**
8 (2)
Pregnancy/Post-partum
5 (1)
Patient choice
4 (1)
Clinical trial procedure
No identified cause
1 (0.3)
189 (50)
*Other than cytogenetics. **Other than infection.
Total percentage exceeds 100% because a subject may have several causes leading to delay
chemotherapy.
18
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Table 3: Univariate analysis for early death, response and overall survival
n=599
Early death
(n=58)
n (%)
Response CR/CRi
(n=432)
p*
n (%)
Overall survival
(months)
median
survival
p**
p*
TDT - days
1
63
11 (17.5)
39 (61.9)
12.0
2
52
7 (13.5)
40 (76.9)
18.2
3-4
65
4 (6.2)
50 (76.9)
§
0.4134
5-6
68
4 (5.9)
7-10
124
> 10
227
§
21.2
0.9048
0.1048
52 (76.5)
27.7
10 (8.1)
85 (68.5)
15.5
22 (9.7)
166 (73.1)
21.6
§
Age - years
≤ 60
358
23 (6.4)
> 60
241
35 (14.5)
157 (65.1)
12.1
35.7
275 (76.8)
0.0010
26.1
0.0018
<0.0001
ECOG performance status
0
173
7 (4.0)
144 (83.2)
1
196
14 (7.1)
145 (74.0)
2
65
9 (13.8)
41 (63.1)
12.3
3-4
20
6 (30.0)
12 (60.0)
6.9
477
36 (7.5)
0.0001
16.6
0.0002
0.0001
Secondary AML
De novo
Secondary
366 (76.7)
0.0005
122
22 (18.0)
23.0
<0.0001
66 (54.1)
<0.0001
8.6
Extramedullary involvement - n (%)
No
357
19 (5.3)
Yes
151
16 (10.6)
281 (78.7)
<0.0001
23.7
<0.0001
103 (68.2)
0.0004
13.5
Leukostasis - n (%)
No
562
44 (7.8)
Yes
21
10 (47.6)
416 (74.0)
<0.0001
19.7
<0.0001
6 (28.6)
<0.0001
1.0
White blood cell count
≤ 50 G/L
466
31 (6.7)
> 50 G/L
133
27 (20.3)
347 (74.5)
> 4 g/L
243
22 (9.1)
1.5 – 4 g/L
225
21 (9.3)
163 (72.4)
21.2
18
5 (27.8)
10 (55.6)
19.1
<0.0001
20.1
0.0166
85 (63.9)
0.0205
14.2
Fibrinogen - n (%)
< 1.5 g/L
175 (72.0)
0.1154
16.2
0.4325
0.0115
Cytogenetics
Favorable
61
2 (3.3)
Intermediate
394
46 (11.7)
58 (95.1)
Adverse
144
10 (6.9)
88 (61.1)
0.0527
286 (72.6)
NR
<0.0001
20.7
<0.0001
9.5
European LeukemiaNet
Favorable
126
8 (6.3)
114 (90.5)
NR
Intermediate-I
168
19 (11.3)
120 (71.4)
20.8
Intermediate-II
161
21 (13.0)
110 (68.3)
15.4
Adverse
144
10 (6.9)
88 (61.1)
9.5
0.1432
<0.0001
<0.0001
NR: not reached; TDT: time from diagnosis to treatment.
* χ2-test (or Fisher’s exact test in case of small expected numbers)
** Log-Rank test
19
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§
P-value for restricted cubic spline method
20
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Figure legends
Figure 1: Study profile
Between 2000 and 2009, 599 patients with non-promyelocytic AML were treated with intensive
chemotherapy within a TDT inferior to 90 days. Modalities of consolidation treatment and response
are detailed.
HDAC: High-dose Cytarabine; AutoSCT: autologous stem-cell transplantation; AlloSCT: allogeneic
stem-cell transplantation.
Figure 2: Estimated hazard ratio of death for each day delaying chemotherapy initiation
Figure 2A: RCS (Restricted Cubic Spline method) shows the non-adjusted hazard ratio of death for
each value of TDT as compared to day 6.
Note: For example, the non-adjusted hazard ratio of death for a TDT of 1 day is equal to 1.38 [95%CI:
1.03-1.86] as compared to day 6 according to RCS method.
The locations of the 4 knots used in the Restricted Cubic Spline method are 1, 5, 12 and 42 day
(corresponding respectively to the 5 th, 35th, 65th and 95th percentile of the TDT).22
Figure 2B: RCS (Restricted Cubic Spline method) shows the adjusted* estimated hazard ratio of
death for each value of TDT as compared to day 6.
*Adjusted for Age (Hazard Ratio=1.36 [95% confidence interval: 1.08-1.70] (p=0.008) for subjects >
60 vs ≤ 60 years), ECOG performance status (respectively HR=1.46 [95% CI: 1.12-1.91](p=0.006),
HR=1.76 [1.22-2.53] (p=0.002) and HR=1.73 [0.97-3.07] (p=0.062) for ECOG 1, 2, 3/4 vs 0), Secondary
AML (HR=1.51 [1.18-1.93] (p=0.001) as compared to de novo AML), White blood cell count (HR=1.59
[1.18-2.15] (p=0.002) for subjects > 50 G/L vs ≤ 50 G/L), European LeukemiaNet classification
(respectively HR=2.29 [1.61-3.24] (p<0.001), HR=2.79 [1.98-3.94] (p<0.001) and HR=3.86 [2.69-5.55]
(p<0.001) for Intermediate-I, Intermediate-II and Adverse vs Favorable) and Consolidation
21
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(respectively HR=0.47 [0.30-0.76] (p=0.002), HR=0.63 [0.45-0.88] (p=0.007) for autologous stem-cell
transplantation and allogeneic stem-cell transplantation vs high-dose cytarabine only).
Figure 3: Overall survival according to Time from Diagnosis to Treatment (with a cut-off of 5 days),
age, ECOG performance status, AML status (secondary vs de novo), White Blood Cell count and
European LeukemiaNet classification.
Figure 4: Estimated probability of early death for each day delaying chemotherapy initiation
The graph shows the estimated probability of early death for each value of TDT, adjusted* for the
mean of all other variables of the model . The locations of the 3 knots used in the Restricted Cubic
Spline method are 1, 8 and 32 day (corresponding respectively to the 10 th, 50th and 90th percentile of
the TDT).22
*Adjusted for Age (Odds Ratio=2.41 [95% confidence interval: 1.32-4.39] (p=0.004) for subjects > 60
≤ 60 years), ECOG performance status (respectively OR=1.87 [0.70-4.99](p=0.213), OR=3.23 [1.079.74] (p=0.037) and OR=8.40 [2.20-32.0] (p=0.002) for ECOG 1, 2, 3/4 vs 0), Secondary AML (OR=2.84
[1.48-5.46] (p=0.002) as compared to de novo AML), White blood cell count (OR=4.48 [2.11-9.52]
(p<0.001) for subjects > 50 G/L vs ≤ 50 G/L), European LeukemiaNet classification (respectively
OR=1.42 [0.56-3.62] (p=0.458), OR=1.83 [0.71-4.71] (p=0.208) and OR=0.78 [0.26-2.34] (p=0.659) for
Intermediate-I, Intermediate-II and Adverse vs Favorable).
Figure 5: Estimated probability of non complete response for each day delaying chemotherapy
initiation
The graphs (A), (B), (C) and (D) show the estimated adjusted probability of non complete response .
Interaction between TDT and age; and interaction between TDT and WBC being significant, analyses
were stratified from age (> 60 vs ≤ 60 years) and WBC (> 50 G/L vs ≤ 50 G/L).
22
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The graphs (A) and (B) show the estimated probability of non complete response in subjects with
white blood cell count ≤ 50 G/L for each value of TDT, adjusted** for the mean of all other
variables of the model in younger patients (≤ 60, n=276) (A) and older patients (> 60, n=190) (B) .
The locations of the 3 knots used in the Restricted Cubic Spline method are 3, 9 and 35 day
(corresponding respectively to the 10th, 50 th and 90th percentile of the TDT). 22
**Adjusted for ECOG performance status (respectively Odds Ratio=1.75 [95% confidence interval:
0.98-3.13](p=0.058), OR=2.81 [1.32-5.99] (p=0.007) and OR=4.64 [1.17-18.39] (p=0.029) for ECOG 1,
2, 3/4 vs 0), Secondary AML (OR=1.65 [0.99-2.74] (p=0.053) as compared to de novo AML), European
LeukemiaNet classification (respectively OR=2.06 [0.85-4.98] (p=0.107), OR=3.83 [1.64-8.94]
(p=0.002) and OR=4.70 [2.00-11.04] (p<0.001) for Intermediate-I, Intermediate-II and Adverse vs
Favorable) and the interaction between TDT and Age (> 60 vs ≤ 60).
The graphs (C) and (D) shows the estimated probability of non complete response in subjects with
white blood cell count > 50 G/L for each value of TDT, adjusted*** for the mean of all other
variables of the model in younger patients (≤ 60 years, n=82) (C) and older patients (> 60, n=51) (D).
The locations of the 3 knots used in the Restricted Cubic Spline method are 1, 2 and 10 day
(corresponding respectively to the 10 th, 50th and 90th percentile of TDT).22
***Adjusted for ECOG performance status (respectively Odds Ratio=4.55 [95% confidence interval :
0.56-36.7](p=0.155), OR=7.57 [0.76-74.9] (p=0.084) and OR=4.75 [0.33-68.7] (p=0.253) for ECOG 1, 2,
3/4 vs 0), Secondary AML (OR=20.57 [4.32-97.8] (p<0.001) as compared to de novo AML), European
LeukemiaNet classification (respectively OR=8.53 [2.17-33.5] (p=0.002), OR=3.04 [0.66-14.0]
(p=0.154) and OR=4.94 [0.83-29.6] (p=0.080) for Intermediate-I, Intermediate-II and Adverse vs
Favorable) and the interaction between TDT and Age (> 60 vs ≤ 60).
23
Figure 1
599 patients assessed
Median age, 58 years (IQR, 45-68)
Secondary AML, n=122 (20%)
Median TDT, 8 days (IQR, 4-16)
Median TDT, 9 days (IQR, 5-20) if WBC ≤ 50 G/L vs 2 days if WBC > 50 G/L (IQR, 1-4) (p<0.0001)
Median TDT, 7 days (IQR, 3-14) if age ≤ 60 years vs 9 days if age > 60 years (IQR, 4-23) (p<0.0004)
Median TDT, 7 days (IQR, 3-14) in 2000-2005 vs 9 days (IQR 5-19) in 2006-2009 (p<0.0001)
TDT > 5 days: n=378 (63%)
Induction
chemotherapy (100%)
Early Death
n=58 (10%)
Response
CR + CRi
n=432 (72%)
HDAC only
n=96
(22%)
AutoSCT
n=60
(14%)
AlloSCT
n=95
(22%)
Relapse
n=218 (51%)
Maintenance
n=132
(31%)
No treatment
n=49
(11%)
Figure 2
.5
1
1.5
2
A
RCS (p-value = 0.1048)
lower limit of the 95% CI
0
upper limit of the 95% CI
0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
TDT(days)
.5
1
1.5
2
B
RCS (p-value = 0.4095)
lower limit of the 95% CI
0
upper limit of the 95% CI
0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
TDT(days)
Figure 3
Age
Time from Diagnosis to Treatment
1.00
0.75
0.50
P log-rank<0.0001
0.00
0.00
0.25
0.50
P log-rank=0.8681
Kaplan-Meier survival estimates
0.25
Survival probability
0.75
1.00
Kaplan-Meier survival estimates
0
12
24
36
48
60 72 84
96
Analysis time (months)
108 120 132 144
0
12
24
36
48
TDT < = 5 days
TDT > 5 days
AML status (secondary vs de novo)
1.00
0.75
P log-rank<0.0001
0.50
0.50
Kaplan-Meier survival estimates
0.00
0.00
0.25
Survival probability
0.75
1.00
Kaplan-Meier survival estimates
0.25
108 120 132 144
Age < = 60 years
Age > 60 years
ECOG performance status
P log-rank=0.0001
60 72 84
96
Analysis time (months)
0
12
24
36
48
60 72 84 96
Analysis time (months)
0
108 120 132 144
12
24
36
48
European LeukemiaNet classification
Kaplan-Meier survival estimates
0.75
0.50
P log-rank<0.0001
0.00
0.00
0.25
0.50
Survival probability
0.75
1.00
Kaplan-Meier survival estimates
1.00
White Blood Cell count
0.25
108 120 132 144
AML = De novo
AML = Secondary
ECOG = 0
ECOG = 1
ECOG = 2
ECOG = 3/4
P log-rank=0.0205
60 72 84
96
Analysis time (months)
0
12
24
36
48
60 72 84
96
Analysis time (months)
WBC < = 50 G/L
WBC > 50 G/L
108 120 132 144
0
12
24
36
48
60 72 84 96
Analysis time (months)
108 120 132 144
ELN = Favorable
ELN = Intermediate-I
ELN = Intermediate-II
ELN = Adverse
Figure 4
Figure 5
A
B
WBC ≤ 50 G/L and ≤ 60 years
C
WBC ≤ 50 G/L and > 60 years
D
WBC > 50 G/L and ≤ 60 years
WBC > 50 G/L and > 60 years
From www.bloodjournal.org by guest on June 15, 2017. For personal use only.
Prepublished online January 30, 2013;
doi:10.1182/blood-2012-09-454553
Time from diagnosis to intensive chemotherapy initiation does not
adversely impact the outcome of patients with acute myeloid leukemia
Sarah Bertoli, Emilie Bérard, Françoise Huguet, Anne Huynh, Suzanne Tavitian, François Vergez, Sophie
Dobbelstein, Nicole Dastugue, Véronique Mansat-De Mas, Eric Delabesse, Eliane Duchayne, Cécile
Demur, Audrey Sarry, Valérie Lauwers-Cances, Guy Laurent, Michel Attal and Christian Récher
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