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CLINICAL TRIALS AND OBSERVATIONS
A dynamic prognostic model to predict survival in post–polycythemia
vera myelofibrosis
Francesco Passamonti,1 Elisa Rumi,1 Marianna Caramella,2 Chiara Elena,1 Luca Arcaini,1 Emanuela Boveri,3
Cecilia Del Curto,1 Daniela Pietra,1 Laura Vanelli,1 Paolo Bernasconi,1 Cristiana Pascutto,1 Mario Cazzola,1 Enrica Morra,2
and Mario Lazzarino1
1Department
of Hematology, Fondazione Istituto di ricovero e cura a carattere scientifico (IRCCS) Policlinico San Matteo, University of Pavia, Pavia;
of Hematology, Ospedale Niguarda Ca’ Granda, Milan; and 3Department of Surgical Pathology, Fondazione Istituto di Ricovero e Cura a Carattere
Scientifico (IRCCS) Policlinico San Matteo, University of Pavia, Pavia, Italy
2Department
Post–polycythemia vera myelofibrosis
(post-PV MF) is a late evolution of PV. In
647 patients with PV, we found that leukocytosis leukocyte count > (15 ⴛ 109/L) at
diagnosis is a risk factor for the evolution
of post-PV MF. In a series of 68 patients
who developed post-PV MF, median survival was 5.7 years. Hemoglobin level less
than 100 g/L (10 g/dL) at diagnosis of
post-PV MF was an independent risk factor
for survival. The course of post-PV MF, how-
ever, is a dynamic process that implies a
progressive worsening of clinical parameters. Using a multivariate Cox proportional
hazard regression with time-dependent
covariates, we found that a dynamic score
based on hemoglobin level less than
100 g/L (10 g/dL), platelet count less than
100 ⴛ 109/L, and leukocyte count more than
30 ⴛ 109/L is useful to predict survival at any
time from diagnosis of post-PV MF. The
resulting hazard ratio of the score was 4.2
(95% CI: 2.4-7.7; P < .001), meaning a 4.2fold worsening of survival for each risk
factor acquired during follow up. In conclusion, leukocytosis at diagnosis of PV is a
risk factor for evolution in post-PV MF. A
dynamic score based on hemoglobin level,
and platelet and leukocyte count predicts
survival at any time from diagnosis of
post-PV MF. (Blood. 2008;111:3383-3387)
© 2008 by The American Society of Hematology
Introduction
Post–polycythemia vera myelofibrosis (post-PV MF) is a recently named condition1 that represents the natural evolution of
patients with polycythemia vera (PV).2 The criteria proposed for
the diagnosis of post-PV MF1 set the time point of evolution
along the natural history of the disease. Patients’ survival after
transition to MF, as well as the prognostic factors for survival,
are not defined.
Post-PV MF is a delayed event in the course of PV. No risk
factors for this condition have been identified so far. In patients
with PV, the 15-year risk of evolution to myelofibrosis is estimated
at 6% and the incidence is 5.1 ⫻ 1000 person-years.3 A similar
figure is reported in young patients with PV.4 Patients with post-PV
MF have a high rate of detection of the JAK2 (V617F) mutation
ranging from 91%5 to 100%.6 Concerning the JAK2 (V617F)
mutation burden, patients with post-PV MF have the highest
proportion of mutant alleles in patients with chronic myeloproliferative disorders (CMDs).6 An abnormal stem cell trafficking has been
reported in patients with post-PV MF.7-9 JAK2 (V617F) may
activate circulating granulocytes, playing a role in the constitutive
mobilization of CD34⫹ cells into peripheral blood. This phenomenon is particularly evident in patients with PV and post-PV MF.6
Current treatments for patients with post-PV MF do not affect
survival and are considered palliative.10 Allogeneic hematopoietic
stem cell transplantation is the only curative treatment for post-PV
MF. Only a few patients, however, have been treated with fully
ablative11 or reduced-intensity conditioning allogeneic transplantation.12 Clinical trials on JAK2 inhibitors are still underway.13
In a cohort of 647 patients with PV, 68 developed post-PV
MF according to the criteria of the International Working Group
on Myelofibrosis Research and Treatment (IWG-MRT).1 The
aim of this study is to define survival of patients with post-PV
MF and to identify prognostic factors for survival. We developed a dynamic prognostic model useful to predict survival at
any time from diagnosis.
Methods
Patients
In 76 consecutive patients previously diagnosed as post-PV MF,
systematic revision of clinical and histopathological records identified
68 patients fitting diagnostic criteria for post-PV MF established by the
IWG-MRT.1 Patients were followed from 1982 to 2007 at the Division
of Hematology of the Fondazione Policlinico San Matteo, University of
Pavia, and at the Division of Hematology of the Niguarda Ca’ Granda
Hospital, Milan, Italy. Patients of the 2 institutions were well matched
with regard to baseline demographic and disease characteristics. The
diagnosis of PV and of primary myelofibrosis (PMF) was made in
accordance with the criteria in use at the time of first observation.14-16
The study was approved by the institutional ethics committee of Pavia,
and the procedures followed were in accordance with the Declaration of
Helsinki. Samples for molecular analysis were obtained after patients
provided written informed consent, also in accordance with the Declaration of Helsinki.
Submitted November 4, 2007; accepted January 3, 2008. Prepublished online
as Blood First Edition paper, January 10, 2008; DOI 10.1182/blood-2007-11121434.
payment. Therefore, and solely to indicate this fact, this article is hereby
marked ‘‘advertisement’’ in accordance with 18 USC section 1734.
The publication costs of this article were defrayed in part by page charge
© 2008 by The American Society of Hematology
BLOOD, 1 APRIL 2008 䡠 VOLUME 111, NUMBER 7
3383
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3384
BLOOD, 1 APRIL 2008 䡠 VOLUME 111, NUMBER 7
PASSAMONTI et al
JAK2 (V617F) mutational analysis
Granulocytes were obtained from the neutrophil fraction by osmotic lysis of
red cells. Genomic DNA was obtained using the Puregene Blood DNA
isolation kit (Gentra Systems, Minneapolis, MN). A quantitative real-time
polymerase chain reaction–based allelic discrimination assay was used to
detect the V617F mutation of JAK2 gene.17
Table 1. Demographic and hematologic characteristics at diagnosis
of 68 patients with post–polycythemia vera myelofibrosis
Characteristic
No.
No. of patients
68
Age at diagnosis, y† (range)
65 (44-81)
Male/female
45/23
WBC count, ⫻ 109/L,† (range)
Flow cytometric analysis of circulating CD34ⴙ cells
CD34⫹
Circulating
cells were enumerated by flow cytometry using a
single-platform assay as previously described,18 following the cell-gating
guidelines recommended by the International Society for Hematotherapy
and Graft Engineering (ISHAGE)19 and the subsequent modifications of the
European Working Group of Clinical Cell Analysis (EWGCCA).20 Daily
instrument quality control, including fluorescence standardization, linearity
assessment, and spectral compensation, was performed to ensure identical
operation from day to day.
Statistical analysis
The cumulative probability of survival was estimated using the KaplanMeier method. Comparison between survival curves was performed using
the Gehan-Wilcoxon test. Survival analysis was performed using Cox
models with time-dependent covariates to assess the effect of the variables
of interest on overall survival (OS). Cox regression models were also
applied to carry out multivariate survival analyses. Standardized mortality
ratios (SMRs) were calculated to compare the patients’ mortality with the
mortality of the general population in Italy. The Italian mortality rates by
age, sex, and calendar year were provided by the Istituto Nazionale di
Statistica (ISTAT; Rome, Italy). Statistical analyses were performed using
Microsoft Excel 2000 (Redmond, WA), Statistica 7.1 (Stat-Soft, Tulsa,
OK), and Stata 9.2 (StataCorp, College Station, TX).
Results
Disease information prior to post-PV MF
A total of 647 patients with PV were evaluated at the 2 institutions
between 1970 and 2007. The median interval between the
diagnosis of PV and that of post-PV MF was 13 years (range,
2.4-29.6 years). We found that the longer the follow-up of patients
with PV, the higher the risk of developing post-PV MF (P ⬍ .001).
During PV, myelosuppressive agents were given to 65 (96%) of
68 patients who developed post-PV MF and to 501 (86.4%) of
579 patients who did not, while the remaining patients received
phlebotomy alone. The rate of patients receiving myelosuppression
was significantly higher among those who developed post-PV MF
(P ⫽ .01). On the other hand, patients receiving myelosuppression
had a significantly longer follow-up than those treated with
phlebotomy alone (7.1 years and 2.9 years, respectively; P ⬍ .001).
To investigate potential risk factors of transformation in post-PV
MF present at diagnosis of PV, we evaluated the clinical features
at diagnosis in the whole cohort of patients (n ⫽ 647). Parameters taken into account were age, hemoglobin level, platelet
count, white blood cell count, spleen size (all considered as
continuous numeric variables), leukocytosis (white blood cell
count ⬎ 15 ⫻ 109/L), calendar year at diagnosis, and institutional
location. Univariate survival analysis showed that white blood cell
count as numeric variable (P ⬍ .001) and white blood cell count
more than 15 ⫻ 109/L (P ⫽ .002) were significant risk factors for
transformation in post-PV MF.
Clinical features at diagnosis of post-PV MF
Table 1 summarizes clinical and hematologic data at diagnosis
of 68 patients with post-PV MF. IWG-MRT criteria and patients’
12.2 (2.3-98)
Hemoglobin level, g/L,† (range)
123 (78-148)
PLT count, ⫻ 109/L,† (range)
369 (50-1827)
Spleen size, cm below left costal margin
7 (0-25)
Bone marrow findings
Marrow cellularity,† % (range)
Reticulin fibrosis, grade 2:grade 3
MK cluster, loose:dense
90 (70-100)
3:1
0.6:1
Marrow myeloblast,† % (range)
0 (0-5)
Lactate dehydrogenase, U/L,† (range), n ⫽ 41
837 (460-3151)
Circulating CD34⫹ cells/␮L,† (range), n ⫽ 39
44.3 (12.1-1005)
No. JAK2 (V617F) positive, (%), n ⫽ 27
Proportion of JAK2 (V617F) alleles,† % (range)
27 (100)
87 (10-100)
*Bone marrow karyotype (%)
Favorable
20 (80)
Unfavorable
5 (20)
CD34⫹
Normal range of circulating
cells: less than 10/␮L; normal range of LDH:
less than 450 mU/mL.
*Favorable indicates normal, 20q⫺; 13q⫺23; unfavorable, other than favorable.
†Data are medians.
distribution per single criterion are outlined in Table 2. Regarding spleen, one patient underwent splenectomy before diagnosis
of post-PV MF. Another patient with no spleen enlargement at
diagnosis of post-PV MF showed anemia and leukoerythroblastic peripheral picture in addition to required criteria. Among
47 patients studied for the JAK2 (V617F) mutation at different
intervals from diagnosis, all carried the mutation. In 27 patients
evaluated at diagnosis, 21 (78%) had more than 50% mutant
alleles. In all patients, the number of circulating CD34⫹ cells
and serum lactate dehydrogenase (LDH) level exceeded the
upper reference value (10 cells/␮L for CD34⫹ cells and
450 U/L for LDH).
Table 2. International Working Group for Myelofibrosis Research
and Treatment (IWG-MRT) criteria for the diagnosis of
post–polycythemia vera myelofibrosis (post-PV MF) and the
distribution of meeting criteria in 68 patients with post-PV MF
No. of patients (%)
IWG-MRT required criteria
1. Previous diagnosis of polycythemia vera (WHO criteria)
68 (100)
2. Bone marrow fibrosis grade 2-3 (on 0-3 scale)
68 (100)
IWG-MRT additional criteria (2 are required)
1. Anemia* or
Sustained loss of requirement of phlebotomy or
43 (63)
25 (37)
cytoreduction
2. Leukoerythroblastic peripheral blood picture
3. Increasing splenomegaly
68 (100)
66/67 (98)‡
Palpable spleen more than 5 cm from left costal margin
54 (82)
Appearance of a newly palpable splenomegaly
12 (18)
4. Development of more than 1 of the constitutional
26 (38)
symptoms†
*Defined as hemoglobin value less than 120 g/L (12 g/dL) for female and less
than 135 g/L (13.5 g/dL) for male.
†Defined as 10% or more weight loss in 6 months, night sweats, unexplained
fever (⬎37.5°C).
‡One patient underwent splenectomy before diagnosis, so the calculation was
provided on 67 patients.
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BLOOD, 1 APRIL 2008 䡠 VOLUME 111, NUMBER 7
Disease complications and outcome
Patients with post-PV MF were observed for 181 person-years of
follow up after diagnosis and received palliative treatments. During
follow-up, the incidence of thrombosis was 42 ⫻ 1000 personyears (95% CI: 19-93.5): 3 patients had deep venous thrombosis,
2 had stroke, and 1 had myocardial infarction. Two patients
had splenic infarction. The incidence of leukemia was
50 ⫻ 1000 person-years (95% CI: 26-115), and the 3-year leukemiafree survival was 82%. Univariate analysis performed on clinical
parameters at diagnosis of post-PV MF identified as significant risk
factors for leukemia the low platelet count (P ⫽ .041) and the high
circulating CD34⫹ cell count (P ⫽ .016). In a multivariate Cox
proportional hazard regression, only circulating CD34⫹ cell count
retained a significant impact on leukemia-free survival (P ⫽ .036).
The median survival of patients with post-PV MF was 5.7 years.
The standardized mortality ratio (SMR) was 6.5 (95% CI:
4.2-10.1), indicating a significantly higher mortality for patients
with post-PV MF in comparison with the general Italian population
matched for age, sex, and calendar year (P ⬍ .001). We compared
the survival of patients with post-PV MF (mortality: 11.1 per
100 person-years) with the survival of 291 patients with PMF
(mortality: 10.1 per 100 person-years). Gehan-Wilcoxon test
showed that survival of patients with post-PV MF was not
significantly different from that of patients with PMF (P ⫽ .32). In
addition, after adjustment for white blood cell count, hemoglobin
level, platelet count, spleen size, and age in a multivariate Cox
proportional hazard regression model, there was no difference in
survival between the 2 conditions.
Finally, to evaluate whether transformation to myelofibrosis
affects the overall survival of patients with PV, a Cox proportional
hazard regression model with transformation to myelofibrosis as
time-dependent covariate was applied to the whole series of PV
patients. We found that survival of patients with PV was significantly worsened after progression to post-PV MF (HR ⫽ 2.17;
95% CI: 1.27-3.72; P ⫽ .005). This finding retained statistical
significance also after adjustment for age, white blood cell count,
hemoglobin level, platelet count, and spleen size in a multivariate
Cox proportional hazard regression model.
Prognostic factors at diagnosis of post-PV MF
The parameters we evaluated at diagnosis of post-PV MF to
investigate potential predictors of survival were age, hemoglobin
level, platelet count, white blood cell count, spleen size, year
duration of PV, serum lactate dehydrogenase level, granulocyte
JAK2-V617F mutation burden, circulating CD34⫹ cells (all considered as continuous numeric variables), hemoglobin value less than
100 g/L (10 g/dL),21 white blood cell count less than 4 ⫻ 109/L,21
white blood cell count more than 30 ⫻ 109/L,21 platelet count less
than 100 ⫻ 109/L,22 and karyotype23 (according to the categorization in use for PMF). Univariate survival analysis showed that
hemoglobin value less than 100 g/L (10 g/dL; P ⬍ .001) and
circulating CD34⫹ cell count (P ⫽ .009) were significant risk
factors for survival. Multivariate Cox regression model including
the parameters available in all patients at diagnosis of post-PV MF
(hemoglobin value, white blood cell count, platelet count, spleen
size, age) indicated that only hemoglobin level less than 100 g/L
(10 g/dL) was an independent risk factor for survival (P ⬍ .001).
Using this hemoglobin level as cutoff, patients could be stratified
into 2 risk categories with significantly different survival: 6.6 years
for those with hemoglobin value 100 g/L (10 g/dL) or higher and
PROGNOSIS IN POST-PV MF
3385
1.9 years for those with hemoglobin value less than 100 g/L
(10 g/dL; P ⫽ .0001).
Time-dependent analysis of prognostic factors
Sixty-four patients with post-PV MF had longitudinal blood cell
count measurements at regular intervals from diagnosis. We
studied this cohort of patients to assess whether variation of
hematologic parameters during follow-up may further help in
predicting survival at any time from diagnosis. The acquisition of
the following parameters was studied: hemoglobin level less
than 100 g/L (10 g/dL),21 platelet count less than 100 ⫻ 109/L,22
and white blood cell count less than 4 ⫻ 109/L or more than
30 ⫻ 109/L.21 Modification of therapy was not involved in the
acquisition of risk factors. During follow-up of post-PV MF,
hemoglobin level dropped lower than 100 g/L (10 g/dL) in
17 (26%) patients, platelet count lower than 100 ⫻ 109/L in
23 (36%), and white blood cell count lower than 4 ⫻ 109/L
in 7 (11%) and higher than 30 ⫻ 109/L in 14 (22%).
As a first step, we evaluated univariate survival analysis with
Cox regression models using hemoglobin value less than 100 g/L
(10 g/dL), platelet count less than 100 ⫻ 109/L, white blood cell
count less than 4 ⫻ 109/L, and white blood cell count more than
30 ⫻ 109/L as time-dependent covariates. The HRs were 5.8 (95%
CI: 2.2-15.2; P ⬍ .001) for hemoglobin, 4.5 (95% CI: 1.67-12,
P ⫽ .003) for platelets, and 8.2 (95% CI: 3-22; P ⬍ .001) for white
blood cell count more than 30 ⫻ 109/L, while white blood cell
count less than 4 ⫻ 109/L did not significantly affect survival
(P ⫽ .115). After adjustment for age in a multivariate Cox proportional hazard regression with time-dependent covariates, hemoglobin value less than 100 g/L (10 g/dL), platelet count less than
100 ⫻ 109/L, and white blood cell count more than 30 ⫻ 109/L
retained statistical significance on survival.
So, we defined a dynamic scoring system based on these
3 independent risk factors. As the 95% CIs of the 3 HRs did not
differ, we assigned the same weight (presence ⫽ 1; absence ⫽ 0) to
the 3 factors. As a consequence, the resulting score can be easily
calculated by simply counting the number of risk factors acquired
at any time during follow-up. The lower risk group includes
patients who never acquire risk factors during follow-up (ie,
hemoglobin level ⱖ 100 g/L [10 g/dL], platelets ⱖ 100 ⫻ 109/L,
and white blood cells ⬍ 30 ⫻ 109/L). Conversely, higher risk
categories include patients with 1, 2, or 3 risk factors, respectively.
To assess the impact on survival of this dynamic scoring system,
we analyzed the score as a continuous time-dependent covariate in
a Cox survival regression model, obtaining an HR of 4.2 (95% CI:
2.4-7.7; P ⬍ .001). This implies a 4.2-fold increase of risk when
the patient acquires one risk factor at any time from the diagnosis of
post-PV MF. The time-dependent prognostic model retained statistical significance after adjustment for age (HR: 6.7, 95% CI:
3-14.7; P ⬍ .001). Figure 1 exemplifies the impact of this dynamic
prognostic model on survival, showing the estimated survival
curves for the resulting 4 risk groups according to the Cox
time-dependent model.
Discussion
In this study, we evaluated 68 patients who developed post-PV MF
in a cohort of 647 patients with PV. Diagnosis of post-PV MF is
based on distinctive criteria, recently proposed by the IWG-MRT.1
These criteria combine histopathologic (bone marrow fibrosis),
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3386
PASSAMONTI et al
Figure 1. Time-dependent survival estimation in post–polycythemia vera
myelofibrosis. Survival curves estimated from the Cox proportional hazard regression with time-dependent covariates. According to the model, each patient is initially
assigned to a risk group and followed in that group as long as no changes in risk
factors take place. The patient is reassigned to another risk group whenever further
risk factors are acquired. So, each patient may contribute with some observation time
to the estimate of survival in different risk groups. Therefore, the upper curve includes
patients who did not acquire any risk factors during the whole follow-up (ie,
hemoglobin level ⱖ 100 g/L [10 g/dL], platelet count ⱖ 100 ⫻ 109/L, or white blood
cell count ⬍ 30 ⫻ 109/L). The other curves include patients who acquired 1, 2, or 3
factors during follow-up.
clinical (splenomegaly, constitutional symptoms), and hematologic
findings (anemia, leukoerythroblastic peripheral blood picture).
In this series of 647 patients with PV, the analysis of risk factors
that may predict transformation to post-PV MF showed that the
presence of leukocytosis (white blood cell count ⬎ 15 ⫻ 109/L) at
diagnosis of PV significantly correlates with post-PV MF occurrence. A correlation between leukocytosis and risk of acute
leukemia has been recently reported in patients with PV.24 These
data indicate that PV patients with leukocytosis are at higher risk of
disease evolution. This suggests that in PV patients those with
leukocytosis are the most appropriate candidates for clinical trials
with JAK2 inhibitors.
A not-yet-defined issue in the natural history of PV concerns
whether the development of post-PV MF has adverse prognostic
implication on survival.2 Using a Cox proportional hazard regression model, with transformation to post-PV MF as time-dependent
covariate, our data indicate a worsening of overall survival of
patients with PV after fibrotic transformation.
Studying the 68 patients of this series who developed post-PV
MF, we found that all patients with available JAK2 (V617F) status
carried the mutation with a high mutational burden. In fact, 78% of
patients at diagnosis of post-PV MF had more than 50% mutant
alleles, as previously reported.6 In PMF, the rate of homozygosity
for JAK2 (V617F) has been recently reported to be 28%.25
Constitutive mobilization of CD34⫹ cells into peripheral blood
represents a frequent phenomenon in post-PV MF,7,18 and all
patients tested in this study had high circulating CD34⫹ cell count.
Serum LDH measurement has been recently introduced in the
proposed revision of WHO criteria for CMD as additional criterion
to diagnose PMF.1 All patients in this series with post-PV MF had
high levels of serum LDH, highlighting the clinical utility of this
parameter in these patients.
Regarding disease complications of patients with post-PV MF,
this study shows that thrombosis remains a relatively frequent
complication in PV patients also after transition to myelofibrosis.
Leukemia occurs with an incidence of 50 ⫻ 1000 person-years,
and circulating CD34⫹ cell count at diagnosis of post-PV MF may
BLOOD, 1 APRIL 2008 䡠 VOLUME 111, NUMBER 7
predict leukemia-free survival. The frequency of leukemic transformation in patients with post-PV MF seems higher than that
reported in patients with PMF.26
In this study, the median survival of patients with post-PV
MF was 5.7 years, slightly lower than that reported in a study
including patients with post-PV and post–essential thrombocythemia MF.23 To better stratify patients, we studied potential risk
factors for survival at diagnosis of post-PV MF. Using a
multivariate Cox proportional hazard regression, we found that
an hemoglobin level less than 100 g/L (10 g/dL) is an independent risk factor for survival. In fact, patients with hemoglobin
value of 100 g/L (10 g/dL) or more had a median survival of
6.6 years, while those with hemoglobin value less than 100 g/L
(10 g/dL) had a median survival of 1.9 years. The cutoff of
100 g/L (10 g/dL) for hemoglobin is also considered useful in
the risk stratification of patients with PMF.21-23,27-29 Another
common behavior between patients with post-PV MF and those
with PMF is survival, which we found to be similar in the
2 conditions. Regarding the adverse impact of unfavorable
karyotype on survival reported in a prior study,23 we did not find
a significant correlation in our series of patients with post-PV
MF. This may probably reflect the small number of patients with
unfavorable karyotype or the different patient population.
The course of post-PV MF is a dynamic process during which
progressive deterioration of clinical parameters occurs. This may
imply the acquisition of additional risk factors. In fact, hemoglobin
and platelets progressively tend to decrease, while leukocytes tend
either to increase or to decrease. On this ground, we developed a
time-dependent scoring system that can be used to predict survival
at any time after diagnosis. According to this model, patients are
classified into a risk group at diagnosis and remain in the same
group until the acquisition of new risk factors. At this time point,
patients enter a higher risk category. We provide evidence that a
dynamic scoring system based on hemoglobin level less than
100 g/L (10 g/dL), platelet count less than 100 ⫻ 109/L, and white
blood cell count more than 30 ⫻ 109/L is useful to predict survival
at any time from diagnosis. In fact, the score predicts a 4.2-fold
worsening of survival for each risk factor acquired at any time
during follow-up of post-PV MF. The survival curves resulting
from this dynamic model have to be interpreted differently from
traditional survival curves. In fact, the survival curves of the
dynamic model represent an estimated survival as long as the
patient remains in the same risk group. A more accurate prediction
of survival has potential clinical implications, as these patients are
JAK2 mutated and may be candidates to clinical trials with JAK2
inhibitors.
In conclusion, this study demonstrates that patients with PV
showing a white blood cell count more than 15 ⫻ 109/L at
diagnosis have higher risk of developing post-PV MF. When
patients with PV develop post-PV MF, a dynamic prognostic model
based on hemoglobin level, platelet count, and white blood cell
count may predict survival at any time after diagnosis.
Acknowledgments
This work was supported by grants from Fondazione Cariplo,
Milan, Italy; Associazione Italiana per la Ricerca sul Cancro
(AIRC), Milan, Italy; Fondazione Ferrata Storti, Pavia, Italy;
Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; and
Ministry of University and Research, Rome, Italy.
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BLOOD, 1 APRIL 2008 䡠 VOLUME 111, NUMBER 7
PROGNOSIS IN POST-PV MF
Authorship
Contribution: F.P. and M.L. conceived the study, collected, analyzed, and interpreted data, and wrote the paper; E.M. and M.
Cazzola analyzed and interpreted data; E.R. collected and analyzed
data; M. Caramella, C.E., L.A., and C.D. collected clinical data;
E.B. performed bone marrow evaluation; D.P. performed JAK2
3387
mutation analysis; L.V. performed CD34⫹ cell count; P.B. performed cytogenetic analysis; C.P. did statistical analyses.
Conflict-of-interest disclosure: The authors declare no competing financial interests.
Correspondence: Francesco Passamonti, Department of Hematology, Fondazione IRCCS Policlinico San Matteo, Viale Golgi 19,
27100 Pavia, Italy; e-mail: [email protected].
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From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
2008 111: 3383-3387
doi:10.1182/blood-2007-11-121434 originally published
online January 10, 2008
A dynamic prognostic model to predict survival in post−polycythemia
vera myelofibrosis
Francesco Passamonti, Elisa Rumi, Marianna Caramella, Chiara Elena, Luca Arcaini, Emanuela
Boveri, Cecilia Del Curto, Daniela Pietra, Laura Vanelli, Paolo Bernasconi, Cristiana Pascutto, Mario
Cazzola, Enrica Morra and Mario Lazzarino
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