Leukemia risk models in primary myelofibrosis: an International Working Group study.
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ABSTRACT: Primary myelofibrosis (PM) is a Philadelphia-negative clonal hematopoietic stem cell disorder characterized by intense reactive changes of bone marrow stroma with collagen fibrosis, osteosclerosis and angiogenesis. PM usually affects elderly people, and approximately half of the patients present JAK2V617F mutation. PM clinical course varies from 1 to 30 years, evolving from asymptomatic into progressive bone marrow failure, symptomatic splenomegaly or acute leukemia in 10-20 % of cases. PM risk stratification is based on parameters predicting survival, and several attempts have been made to identify clinical and laboratory features that could predict PM patient survival. This study applied five prognostic scores: Dupriez, Cervantes, Mayo, IPSS and DIPSS-Plus in 62 Brazilians patients from three centers, and compared their relevance and clinical usefulness considering the scores' parameters, fibrosis, JAK2V617F mutation, splenomegaly, hepatomegaly and treatment. According to the Cervantes, Dupriez and Mayo scores, most patients were stratified into low-risk group. However, when IPSS and DIPSS-Plus were applied, most patients were classified into an intermediate range, being low risk in only 11 and 13 % of patients, respectively. Overall survival at 4 years was 84 %. The Cervantes score was the only one that remained significantly associated with survival in a multivariate analysis. In conclusion, the Cervantes score remains important to the prognostication of PM.Medical Oncology 06/2013; 30(2):555. · 2.14 Impact Factor
1 Palumbo A, Rajkumar SV. Treatment of newly diagnosed myeloma. Leukemia
2009; 23: 449--456.
2 Reya T, Morrison SJ, Clarke MF, Weissman IL. Stem cells, cancer, and cancer stem
cells. Nature 2001; 414: 105--111.
3 Rasmussen T, Lodahl M, Hancke S, Johnsen HE. In multiple myeloma
clonotypic CD38- /CD19+ / CD27+ memory B cells recirculate through
bone marrow, peripheral blood and lymph nodes. Leuk Lymphoma 2004; 45:
4 Huff CA, Matsui W. Multiple myeloma cancer stem cells. J Clin Oncol 2008; 26:
5 Vanderkerken K, Asosingh K, Croucher P, Van Camp B. Multiple myeloma biology:
lessons from the 5TMM models. Immunol Rev 2003; 194: 196--206.
6 Oyajobi BO, Franchin G, Williams PJ, Pulkrabek D, Gupta A, Munoz S et al. Dual
effects of macrophage inflammatory protein-1alpha on osteolysis and tumor
burden in the murine 5TGM1 model of myeloma bone disease. Blood 2003; 102:
7 Fuhler GM, Baanstra M, Chesik D, Somasundaram R, Seckinger A, Hose D et al.
Bone marrow stromal cell interaction reduces syndecan-1 expression and induces
kinomic changes in myeloma cells. Exp Cell Res 2010; 316: 1816--1828.
8 Kalushkova A, Fryknas M, Lemaire M, Fristedt C, Agarwal P, Eriksson M et al.
Polycomb target genes are silenced in multiple myeloma. PLoS One 2010; 5: e11483.
9 Martin-Perez D, Piris MA, Sanchez-Beato M. Polycomb proteins in hematologic
malignancies. Blood 2010; 116: 5465--5475.
10 Yaccoby S, Epstein J. The proliferative potential of myeloma plasma cells manifest
in the SCID-hu host. Blood 1999; 94: 3576--3582.
11 Dongkyoon K, Weissman I. Enrichment of xenotransplantable clonal cells in
CD38high/CD138+cells of multiple myeloma patients. AACR 101st Annual
Meeting, Abstract 4315 2010.
12 Kelly PN, Dakic A, Adams JM, Nutt SL, Strasser A. Tumor growth need not be
driven by rare cancer stem cells. Science 2007; 317: 337.
13 Reid S, Yang S, Brown R, Kabani K, Aklilu E, Ho PJ et al. Characterisation and
relevance of CD138-negative plasma cells in plasma cell myeloma. Int J Lab
Hematol 2010; 32 (6 Part 1): e190--e196.
Leukemia risk models in primary myelofibrosis: an International
Working Group study
Leukemia (2012) 26, 1439--1441; doi:10.1038/leu.2011.374;
published online 13 January 2012
Overall survival in primary myelofibrosis (PMF) is assessed by
the International Prognostic Scoring System (IPSS),1at time of
diagnosis, or the dynamic IPSS (DIPSS)2or DIPSS-plus,3at any time
during the disease course, in the absence and presence of
cytogenetic information, respectively. DIPSS-plus is based on eight
risk factors: age465 years, constitutional symptoms, hemoglobin
o10g/dl, transfusion need, leukocyte count 425?109/l, platelet
count o100?109/l, circulating blasts X1% and unfavorable
karyotype. The latter includes complex karyotype or any one or
two abnormalities that include þ8, ?7/7q-, i(17q), ?5/5q-, 12p-,
inv(3) or 11q23 rearrangement.4In regards to leukemia-free
survival (LFS), recent studies have highlighted the prognostic
significance of monosomal karyotype (MK),5unfavorable karyo-
type,3,4,6circulating blasts X3%,7platelet count o100?109/l,3,7
transfusion need8,9and DIPSS.10Similarly, patients with PMF or
post-polycythemia vera/essential thrombocythemia myelofibrosis
face a higher risk of death and leukemic transformation (LT) in the
presence of chromosome 17 abnormalities, circulating blasts
X10% or platelets o50?109/l.11In the current study, multi-
variable and receiver operating characteristic (ROC) analyses were
applied to an institutional database of 884 karyotypically
annotated patients with PMF, in order to define karyotype-
dependent and karyotype-independent risk models for LFS. A
separate cohort of 525 patients from an international database2
was used to validate the karyotype-independent model.
The diagnoses of PMF and LT were according to the World Health
Organization criteria.12All statistical analyses considered clinical and
laboratory parameters obtained at the time of referral to the Mayo
Clinic. Variables considered in patients from the international
database were those obtained at the time of initial diagnosis. ROC
plots were prepared to determine the best discriminant levels for
continuous variables in predicting LT. The end point used in this
regard (that is, the binary outcome) was the occurrence or non-
occurrence of LT at 5 years after diagnosis.13In other words,
patients were classified as alive and leukemia-free/censored when
follow-up time was 45 years and as leukemia/uncensored for
patients known to have transformed into acute leukemia before
this time point. The performance of the selected cut-off values was
quantified by the area under the ROC curve (AUC). LFS was
calculated from the date of first referral to date of LT (uncensored)
or death/last contact (censored). LFS survival curves were prepared
by the Kaplan-Meier method and compared by the log-rank test.
Cox proportional hazard regression model was used for multi-
variable analysis. P-values o0.05 were considered significant. The
Stat View (SAS Institute, Cary, NC, USA) and JMP (SAS Institute)
statistical packages were used for all computations.
The current study included 884 patients with PMF seen at the
Mayo Clinic between 1977 and 2011. In this Mayo cohort, 517
patients were seen within the first year of their diagnosis. Table 1
depicts clinical and laboratory characteristics of the patients at
time of referral and incidences of events afterwards. DIPSS-plus3
risk distributions were B9% (84 patients) low, 15% (128 patients)
intermediate-1, 38% (332 patients) intermediate-2 and 38%
(340 patients) high. Cytogenetic information was available in all
884 patients and included normal (n¼516; 58%), favorable
(n¼239; 27%) and unfavorable (n¼129; 15%) karyotype.4
JAK2V617F, MPL and IDH mutation status was available in 514,
338 and 305 patients, respectively. The corresponding mutational
frequencies were 60%, 8% and 4%. To date, 564 (64%) deaths
have been recorded and median follow-up of living patients was
36 months (range, 0.1--296). There were a total of 60 documented
cases of LTs. Treatment was according to the treating physician’s
discretion and included observation alone, conventional drugs,
involved field irradiation, splenectomy (n¼164; 19%) and
allogeneic stem cell transplantation (n¼33; 4%).
Clinical and laboratory parameters obtained at time of referral
to the Mayo Clinic were systematically examined for their value in
predicting LT. These parameters included currently acknowledged
risk factors for overall survival in PMF.3In addition, on the basis of
recent relevant information, MK5and inv(3)/i(17q) abnormalities11
were considered separately from other unfavorable karyotype.
A 5-year LT ROC plots were constructed for circulating blast,
leukocyte and platelet counts. The respective AUC for the ROC
plots were 0.70, 0.71 and 0.55. Accordingly, we proceeded further
in determining the best cut-off levels for increased circulating
blast percentage and thrombocytopenia, which were 2% and
41?109/l, respectively (ROC plots using 3 instead of 5 years as the
end point yielded similar results). These two cut-off levels were
subsequently used in multivariable analyses that included the
DIPSS-plus risk factors including age 465 years, hemoglobin
o10g/dl, leukocyte count 425?109/l, presence of constitutional
symptoms, transfusion need and unfavorable karyotype.3As
mentioned above, unfavorable karyotype was treated as three
separate subcategories: MK, inv(3)/i(17q) abnormalities and other
Letters to the Editor
Leukemia (2012) 1402--1448
& 2012 Macmillan Publishers Limited
On multivariable analysis, the following were identified as
independent predictors of inferior LFS: MK (Hazard ratio (HR) 6.2,
95% confidence intervals (CI) 2.2--17.1; P¼0.0004), inv(3)/i(17q)
abnormalities (HR 7.6, 95% CI 1.8--33.3; P¼0.007), circulating blasts
X2% (HR 2.4, 95% CI 1.4--4.2; P¼0.002) and platelet count
p41?109/l (HR 2.6, 95% CI 1.3--5.1; P¼0.008). MK and inv(3)/
i(17q) abnormalities were subsequently consolidated into one very
high risk cytogenetic category (n¼27), with a corresponding HR of
6.6 (95% CI 2.7--16.0). HR-based risk scores were assigned to very
high risk karyotype (2 points), circulating blasts X2% (1 point) and
platelet count p50?109/l (1 point) to classify patients into low (no
adverse points; n¼522), intermediate (1 adverse point; n¼290)
and high risk (X2 adverse points; n¼72) groups; the correspond-
ing 3-year LT rates were 3%, 10% (HR 2.6; 95% CI 1.4--4.6;
P¼0.002) and 35% (HR 9.4, 95% CI 4.7--18.7; Po0.0001) (Figure 1).
None of the other covariates, including age 465 years,
hemoglobin o10g/dl, leukocyte count 425?109/l, presence of
constitutional symptoms, transfusion need or unfavorable karyo-
type other than MK or inv(3)/i(17q) abnormalities were indepen-
dently significant (P40.1 in all instances).
The karyotype-independent model was developed using the
aforementioned cut-off values for circulating blast percentage
(X2%; 1 adverse point) and platelet count (p50?109/l; 1 adverse
point); low-risk (no adverse points; n¼525), intermediate-risk
Clinic and stratified by the presence or absence of risk factors for leukemic transformation
Clinical and laboratory characteristics of 884 karyotypically annotated patients with primary myelofibrosis at the time of referral to the Mayo
Patients with PB
blasts X2% but
without very high
Patients with platelets
o50?109/l but without
very high risk karyotype or
PB blasts X2% (n¼46)
none of the
Age (years); median (range)
Age 465 years; n (%)
Males; n (%)
Hemoglobin, g/dl; median (range)
Hemoglobin o10g/dl; n (%)
Transfusion requiring; n (%)
WBC, ?109/l; median (range)
WBC 425?109/l; n (%)
WBC o4?109/l; n (%)
Platelets, ?109/l; median (range)
Platelets o100?109/l; n (%)
Platelets o50?109/l; n (%)
PB blast %; median (range)
PB blasts X1%; n (%)
DIPSS-plus risk group; n (%)
Constitutional symptoms; n (%)
JAK2V617F; n (%) (n evaluable¼514)
MPL mutation; n (%) (n evaluable¼338)
IDH mutation; n (%) (n evaluable¼305)
Deaths; n (%)
Leukemic transformations, n (%)
Abbreviations: DIPSS, Dynamic International Prognostic Scoring System-plus;3PB, peripheral blood; WBC, white blood cell count.aVery high risk karyotype
includes inv(3) and i(17q) abnormalities.bNone of the above includes patients without very high risk karyotype, PB blasts X2% or platelets o50?109/l.
High-risk; n=72, events 13
Intermediate-risk; n=290, events 23
Low-risk; n=522, events 24
by a karyotype-dependent risk model. Risk scores were assigned
to very high risk karyotype (2 points), peripheral blood blast
X2% (1 point) and platelet count p50? 109/l (1 point) to
classify patients into low (no adverse points; n¼522), intermediate
(1 adverse point; n¼290) and high risk (X2 adverse points;
n¼72) groups. Very high risk karyotype included MK, inv(3)
or i(17q) abnormalities.
LFS data of 884 Mayo Clinic patients with PMF stratified
Letters to the Editor
Leukemia (2012) 1402--1448
& 2012 Macmillan Publishers Limited
(1 adverse point; n¼311) and high-risk (2 adverse points; n¼48);
the corresponding 3-year LT rates were 3%, 12% (HR 3.1, 95% CI
1.8--5.4; Po0.0001) and 25% (HR 6.0, 95% CI 2.6--14.1; Po0.0001)
(Supplementary Figure 1). None of the other covariates, including
465 years, hemoglobin
425?109/l, presence of constitutional symptoms or red cell
transfusion need were independently significant (P40.1 in
all instances). The karyotype-independent model was validated
in a separate cohort of 525 PMF patients from an international
database,(10) using variables obtained at time of initial diagnosis
(Supplementary Table 1; Supplementary Figure 2).
Accurate disease prognostication in PMF is crucial for the
selection of patients in whom the risk associated with allogeneic
stem cell transplantation or participation in new drug trials is
justified. Moreover, the therapeutic implications of impending LT
are different from those of progressive disease characterized by
bone marrow failure and marked hepatosplenomegaly. In other
words, the need for allogeneic stem cell transplantation might be
more urgent in the presence of risk factors for LT whereas, in their
absence, it is reasonable to pursue investigational drug therapy
that targets specific disease complications, such as anemia or
splenomegaly.14We have previously reported that patients with
DIPSS high (HR 24.9) and intermediate-2 (7.8) risk disease were
more likely to undergo LT, compared with patients with low-risk
disease.10However, a more recent analysis suggested that some
but not all components of DIPSS or DIPSS-plus were indepen-
dently predictive of LT, and that the separate consideration of
certain risk factors neutralized the aggregate association between
DIPSS/DIPSS-plus and LT.3
Among the risk factors currently listed under IPSS/DIPSS/DIPSS-
plus, unfavorable karyotype,3,4,6platelet count o100?109/l3,7and
dently associated with LT. In addition, recent studies have suggested
additional value for MK,5PB blasts X3%7or X10%,11chromosome
17 abnormalities,11platelet count o50(ref. 11)or o150(ref. 15)?109/l
and leukocyte count 430?109/l.15The current study, representing
the largest karyotypically annotated study population in PMF
(n¼884), examined the prognostic contribution of each one of the
aforementioned risk factors to come up with both karyotype-
dependent (preferable if available) and karyotype-independent risk
models that are applicable at diagnosis or at the time of referral. The
study revealed that the detrimental effect of unfavorable karyotype
was mostly attributed to MK or inv(3)/i(17q) and that LT prediction
was enhanced by using different cut-off values for circulating blasts
and platelet counts. The current LT risk models complement DIPSS-
plus in the comprehensive prognostication of patients with PMF. At
the same time, it is underscored that additional studies with better
documentation of causes of death and implementation of statistical
methods that account for competing risk of death are needed to
validate and possibly improve upon the current risk models.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
Studies performed at the University of Florence and University of Pavia, related to
creation of the international database, were funded by a special Grant from ‘AIRC 5
per mille’ to the AGIMM group (AIRC-Gruppo Italiano Malattie Mileoproliferative); for a
complete list of AGIMM investigators see at http://www.progettoagimm.it.
A Tefferi1, A Pardanani1, N Gangat1, KH Begna1, CA Hanson2,
DL Van Dyke3, D Caramazza4, AM Vannucchi5, E Morra6,
M Cazzola7, A Pereira8, F Cervantes8and F Passamonti4
1Division of Hematology, Rochester, MN, USA;
2Division of Hematopathology, Rochester, MN, USA;
3Division of Cytogenetics, Mayo Clinic,
Rochester, MN, USA;
4Department of Internal Medicine, Division of Hematology,
Ospedale di Circolo e Fondazione Macchi, Varese, Italy;
5Section of Hematology, Department of Critical Care,
University of Florence, Florence, Italy;
6Division of Hematology, Ospedale Niguarda
Ca’ Granda, Milan, Italy;
7Department of Hematology Oncology, Fondazione Istituto
di Ricovero e Cura a Carattere Scientifico (IRCCS)
Policlinico S Matteo, University of Pavia, Pavia, Italy and
8Department of Hematology, Hospital Clı ´nic, Institut
d’Investigacions Biome `diques August Pi i Sunyer (IDIBAPS),
University of Barcelona, Barcelona, Spain
1 Cervantes F, Dupriez B, Pereira A, Passamonti F, Reilly JT, Morra E et al. New
prognostic scoring system for primary myelofibrosis based on a study of the
International Working Group for Myelofibrosis Research and Treatment. Blood
2009; 113: 2895--2901.
2 Passamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Pereira A et al. A
dynamic prognostic model to predict survival in primary myelofibrosis: a study by
the IWG-MRT (International Working Group for Myeloproliferative Neoplasms
Research and Treatment). Blood 2010; 115: 1703--1708.
3 Gangat N, Caramazza D, Vaidya R, George G, Begna K, Schwager S et al. DIPSS
plus: a refined Dynamic International Prognostic Scoring System for primary
myelofibrosis that incorporates prognostic information from karyotype, platelet
count, and transfusion status. J Clin Oncol 2011; 29: 392--397.
4 Caramazza D, Begna KH, Gangat N, Vaidya R, Siragusa S, Van Dyke DL et al. Refined
cytogenetic-risk categorization for overall and leukemia-free survival in primary
myelofibrosis: a single center study of 433 patients. Leukemia 2011; 25: 82--88.
5 Vaidya R, Caramazza D, Begna KH, Gangat N, Van Dyke DL, Hanson CA et al.
Monosomal karyotype in primary myelofibrosis is detrimental to both overall and
leukemia-free survival. Blood 2011; 117: 5612--5615.
6 Hidaka T, Shide K, Shimoda H, Kameda T, Toyama K, Katayose K et al. The impact
of cytogenetic abnormalities on the prognosis of primary myelofibrosis: a
prospective survey of 202 cases in Japan. Eur J Haematol 2009; 83: 328--333.
7 Huang J, Li CY, Mesa RA, Wu W, Hanson CA, Pardanani A et al. Risk factors for leukemic
transformation in patients with primary myelofibrosis. Cancer 2008; 112: 2726--2732.
8 Tefferi A, Mesa RA, Pardanani A, Hussein K, Schwager S, Hanson CA et al. Red
blood cell transfusion need at diagnosis adversely affects survival in primary
myelofibrosis-increased serum ferritin or transfusion load does not. Am J Hematol
2009; 84: 265--267.
9 Passamonti F, Rumi E, Elena C, Arcaini L, Merli M, Pascutto C et al. Incidence of
leukaemia in patients with primary myelofibrosis and RBC-transfusion-depen-
dence. Br J Haematol 2010; 150: 719--721.
10 Passamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Cazzola M et al.
Dynamic International Prognostic Scoring System (DIPSS) predicts progression to
acute myeloid leukemia in primary myelofibrosis. Blood 2010; 116: 2857--2858.
11 Tam CS, Kantarjian H, Cortes J, Lynn A, Pierce S, Zhou L et al. Dynamic model
for predicting death within 12 months in patients with primary or post-
polycythemia vera/essential thrombocythemia myelofibrosis. J Clin Oncol 2009;
12 Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A 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.
13 Tzankov A, Zlobec I, Went P, Robl H, Hoeller S, Dirnhofer S. Prognostic
immunophenotypic biomarker studies in diffuse large B cell lymphoma with
special emphasis on rational determination of cut-off scores. Leuk Lymphoma
2010; 51: 199--212.
14 Pardanani A, Vannucchi AM, Passamonti F, Cervantes F, Barbui T, Tefferi A. JAK
inhibitor therapy for myelofibrosis: critical assessment of value and limitations.
Leukemia 2011; 25: 218--225.
15 Morel P, Duhamel A, Hivert B, Stalniekiewicz L, Demory JL, Dupriez B.
Identification during the follow-up of time-dependent prognostic factors for
the competing risks of death and blast phase in primary myelofibrosis: a study of
172 patients. Blood 2010; 115: 4350--4355.
Supplementary Information accompanies the paper on the Leukemia website (http://www.nature.com/leu)
Letters to the Editor
Leukemia (2012) 1402--1448
& 2012 Macmillan Publishers Limited