Literature DB >> 35961958

Differential prognostic impact of cytopenic phenotype in prefibrotic vs overt primary myelofibrosis.

Giacomo Coltro1,2, Francesco Mannelli1,2, Giuseppe Gaetano Loscocco1,2, Carmela Mannarelli1,2, Giada Rotunno1,2, Chiara Maccari1,2, Fabiana Pancani1,2, Alessandro Atanasio1,2, Alessandro Maria Vannucchi3,4, Paola Guglielmelli1,2.   

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Year:  2022        PMID: 35961958      PMCID: PMC9374751          DOI: 10.1038/s41408-022-00713-6

Source DB:  PubMed          Journal:  Blood Cancer J        ISSN: 2044-5385            Impact factor:   9.812


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Dear Editor, Cytopenias are frequent and distinctive features of primary myelofibrosis (PMF). Anemia is the most common, has consistently been associated with shortened survival, and is an integral component of prognostic models (IPSS, DIPSS/-plus MIPSS70/-plus) [1-4]. Albeit less frequent, also thrombocytopenia (defined as a platelet count <100 × 109/L) was included in the DIPSS-plus and MIPSS70/-plus scores as independent predictor of reduced survival [3-7]. Conversely, leukopenia is the least frequent and has been inconsistently associated with inferior survival [8-10]. Overall, the balance between myeloproliferative and myelodysplastic traits in PMF results in two main clinical phenotypes that are characterized by distinct peripheral blood (PB) presentations: patients with features of myeloproliferation exhibit elevated cell counts, mainly leukocytes and platelets (proliferative phenotype), while patients exhibiting myelodysplastic traits present with cytopenias involving one or more hematopoietic lineages (cytopenic phenotype [CP]) [11, 12]. Although not strictly defined, the CP has been associated with poor prognosis, but cytopenias have been usually considered individually [12]. In the current study, we aimed at investigating the phenotypic and prognostic correlates of a CP in a large cohort of PMF patients, with a specific focus on the distinction between prefibrotic (pre-) and overt PMF. Cytopenias were defined as follows: leukopenia for leukocytes <4 × 109/L, sex-adjusted anemia for hemoglobin (Hb) <11 g/dL for male and <10 g/dL for female, and thrombocytopenia for platelets <100 × 109/L. A CP was defined by the presence of at least one cytopenia, whereas patients not included in the cytopenic group were considered as having a proliferative phenotype. Sex-adjusted anemia was further categorized as moderate (Hb 9–10.9/8–9.9 g/dL for male/female, respectively) and severe (Hb < 9/8 g/dL for male/female, respectively). Similarly, moderate and severe thrombocytopenia was defined by platelets 50–99 × 109/L and <50 × 109/L, respectively. Patients with severe anemia and/or thrombocytopenia were considered as having a severe CP. Details on methods are reported in Supplemental Information. A total of 431 patients with WHO-defined PMF were included in the study, 216 (50%) pre-PMF and 215 (50%) overt PMF. Patients’ characteristics according to PMF diagnosis are listed in Supplemental Table 1. In pre-PMF, leukopenia, sex-adjusted anemia and thrombocytopenia were found in 12 (6%), 40 (19%), and 18 (8%) patients, respectively. The corresponding figures in overt PMF were 29 (13%), 92 (43%), and 30 (14%), respectively (Fig. 1A). Overall, a CP was identified in 50 (23%) and 105 (49%) patients with pre- and overt PMF, respectively (P < 0.0001). Patients with a severe CP were 22 (10%) in pre-PMF and 42 (20%) in overt PMF (P < 0.0001), while the corresponding figures for the presence of ≥ 2 cytopenias were 15 (7%) and 39 (18%), respectively (P < 0.0001). Table 1 reports the comparison of proliferative versus cytopenic phenotypes in pre- and overt PMF, separately.
Fig. 1

Characteristics and outcomes of patients with prefibrotic and overt PMF according to disease phenotype (cytopenic vs proliferative).

A Bar graph reporting the distribution of peripheral blood cell counts in pre-PMF (top) and overt PMF (bottom). B Kaplan-Meier estimates of overall survival in patients with pre-PMF according to disease phenotype (cytopenic vs proliferative). C Competing risks-adjusted estimates of cumulative incidence of leukemic transformation in pre-PMF according to disease phenotype (cytopenic vs proliferative). D Competing risks-adjusted estimates of cumulative incidence of progression to overtly fibrotic phase in 139 pre-PMF patients according to disease phenotype (cytopenic vs proliferative). E. Kaplan-Meier estimates of overall survival in patients with overt PMF according to disease phenotype (cytopenic vs proliferative). F Competing risks-adjusted estimates of cumulative incidence of leukemic transformation in overt PMF according to disease phenotype (cytopenic vs proliferative). Abbreviations: CI confidence interval, CuI cumulative incidence, Hb hemoglobin, LT leukemic transformation, OS overall survival, Plt platelets, pre-PMF prefibrotic primary myelofibrosis, WBC white blood cells.

Table 1

Clinical and laboratory features of patients with WHO-defined prefibrotic and overt PMF stratified by the disease phenotype (cytopenic versus proliferative).

VariablePrefibrotic PMFOvert PMF
Proliferative pre-PMF n = 166 (77%)Cytopenic pre-PMF n = 50 (23%)Proliferative vs cytopenic pre-PMF P valueProliferative overt PMF n = 110 (51%)Cytopenic overt PMF n = 105 (49%)Proliferative vs cytopenic overt PMF P value
Clinical and demographicsMale sex; n (%)81 (49)37 (74)0.001776 (69)80 (76)0.24
Age at diagnosis, years; median (range)56 (18–90)68 (24–89)<0.000159 (21–83)67 (34-89)<0.0001
Peripheral CD34 + , %; mean (SD); evaluable = 138/1400.2 (1.1)0.7 (1.2)0.00151 (1.6)1.8 (3.7)0.0155
PB blasts, %; mean (SD); evaluable = 215/2080.2 (0.9)1.5 (3)<0.00010.7 (1.6)1.4 (3)0.18
LDH, U/L; median (range); evaluable = 158/156308 (127–2521)464 (146–2643)0.0030614 (194–1919)690 (130–2981)0.26
BM fibrosis grade 1 (pre-PMF)/3 (overt PMF); n (%); evaluable = 210/199116 (73)45 (90)0.010729 (29)42 (43)0.0373
Splenomegaly (>5 cm below the LCM); n (%); evaluable = 212/20767 (41)30 (61)0.013286 (80)76 (76)0.45
Hepatomegaly; n (%); evaluable = 205/20227 (17)22 (47)<0.000136 (34)42 (43)0.19
Constitutional symptoms; n (%); evaluable = 196/20227 (17)16 (43)0.000533 (32)44 (44)0.07
MPN driversJAK2 mutated; n (%); evaluable = 197/202118 (74)19 (50)0.003672 (69)57 (58)0.10
 JAK2V617F AB; median (range); evaluable = 131/12635 (1–100)43 (1–68)0.1144 (9–95)38 (5–100)0.0347
 JAK2V617F AB lower quartile; n (%); evaluable = 131/12636 (32)4 (21)0.338 (11)16 (29)0.0149
CALR mutated; n (%); evaluable = 196/19829 (18)4 (11)0.2824 (23)16 (17)0.26
MPL mutated; n (%); evaluable = 196/2008 (5)3 (8)0.503 (3)8 (8)0.11
Triple negative; n (%); evaluable = 196/1979 (6)1 (32)<0.00015 (5)15 (16)0.0115
Double mutated; n (%); evaluable = 195/1965 (3)1 (3)0.882 (2)1 (1)0.61
Myeloid neoplasm-associated genesASXL1 mutated; n (%); evaluable = 176/18217 (12)10 (28)0.020336 (38)38 (44)0.36
CBL mutated; n (%); evaluable = 156/1623 (2)2 (7)0.236 (7)7 (9)0.57
CSF3R mutated; n (%); evaluable=111/1051 (1)0 (0)0.711 (2)0 (0)0.38
CUX1 mutated; n (%); evaluable = 105/960 (0)1 (9)0.00330 (0)2 (5)0.11
DNMT3A mutated; n (%); evaluable = 156/1645 (4)3 (10)0.189 (10)3 (4)0.11
EZH2 mutated; n (%); evaluable = 176/1823 (2)1 (3)0.8216 (17)12 (14)0.61
IDH1/2 mutated; n (%); evaluable = 176/1820 (0)1 (3)0.056 (6)8 (9)0.44
KIT mutated; n (%); evaluable = 138/1403 (3)0 (0)0.440 (0)1 (2)0.27
NF-E2 mutated; n (%); evaluable = 132/1314 (4)1 (4)0.883 (4)3 (5)0.77
N/KRAS mutated; n (%); evaluable = 137/1392 (2)3 (13)0.00847 (9)13 (21)0.06
RUNX1 mutated; n (%); evaluable = 138/1390 (0)2 (9)0.00143 (4)3 (5)0.84
SETBP1 mutated; n (%); evaluable = 111/1050 (0)3 (23)<0.00011 (2)1 (2)0.86
SF3B1 mutated; n (%); evaluable = 137/1415 (4)1 (4)0.996 (8)6 (9)0.74
SH2B3/LNK mutated; n (%); evaluable = 136/1412 (2)2 (9)0.076 (8)1 (2)0.08
SRSF2 mutated; n (%); evaluable = 176/18210 (7)6 (17)0.089 (9)13 (15)0.24
TET2 mutated; n (%); evaluable = 157/16327 (21)7 (23)0.8014 (16)15 (19)0.59
TP53 mutated; n (%); evaluable = 139/1432 (2)2 (8)0.082 (3)3 (5)0.49
U2AF1 mutated; n (%); evaluable = 137/1410 (0)1 (4)0.02553 (4)10 (16)0.0165
ZRSR2 mutated; n (%); evaluable = 111/1058 (8)2 (15)0.392 (3)5 (11)0.13
HMR mutations; n (%); evaluable = 176/18224 (17)11 (31)0.0844 (46)49 (57)0.13
≥2 HMR mutations; n (%); evaluable = 176/1826 (4)6 (17)0.008621 (22)18 (21)0.88
CytogeneticsAbnormal karyotype; n (%); evaluable = 163/13623 (18)15 (44)0.001330 (38)19 (33)0.49
 Favorable karyotype; n (%)120 (93)22 (65)<0.000161 (78)44 (760.72
 Unfavorable karyotype; n (%)8 (6)4 (12)13 (17)9 (16)
 Very high-risk karyotype; n (%)1 (1)8 (24)4 (5)5 (9)
Prognostic stratificationIPSS risk stratification; evaluable = 193/195
 Low risk; n (%)84 (54)4 (11)<0.000134 (34)9 (9)<0.0001
 Intermediate-1 risk; n (%)54 (35)7 (19)37 (37)15 (16)
 Intermediate-2 risk; n (%)10 (6)9 (24)18 (18)31 (32)
 High risk; n (%)8 (5)17 (46)10 (10)41 (43)
DIPSS risk stratification; evaluable = 193/195
 Low risk; n (%)84 (54)4 (11)<0.000134 (34)9 (9)<0.0001
 Intermediate-1 risk; n (%)64 (41)10 (27)55 (56)21 (22)
 Intermediate-2 risk; n (%)8 (5)19 (51)10 (10)51 (53)
 High risk; n (%)0 (0)4 (11)0 (0)15 (16)
MIPSS70 risk stratification; evaluable = 172/171
 Low risk; n (%)96 (71)3 (8)<0.00018 (8)2 (3)0.0002
 Intermediate risk; n (%)33 (24)20 (56)59 (65)33 (41)
 High risk; n (%)7 (5)13 (36)24 (26)45 (56)
Deaths; n (%)40 (24)36 (72)<0.000154 (49)64 (61)0.08
Leukemic transformation; n (%)7 (4)13 (30)<0.000113 (12)15 (15)0.57

AB allele burden, BM bone marrow, DIPSS dynamic international prognostic score system, HMR high molecular risk, IPSS international prognostic score system, LCM left costal margin, LDH lactate dehydrogenase, MIPSS70 mutation-enhanced international prognostic scoring system, MPN myeloproliferative neoplasm, PB peripheral blood, PMF primary myelofibrosis, Pre-PMF prefibrotic-PMF, SD standard deviation, WHO world health organization.

Notes: ║HMR category is defined as the presence of at least one mutation in any of the following genes: ASXL1, EZH2, SRSF2, or IDH1/2. †≥2 HMR mutations indicates the presence of two or more mutated genes among ASXL1, EZH2, SRSF2, and IDH1/2 (two or more mutations in the same gene are counted as one). Evaluable patients for each variable are reported for prefibrotic/overt PMF, respectively.

Characteristics and outcomes of patients with prefibrotic and overt PMF according to disease phenotype (cytopenic vs proliferative).

A Bar graph reporting the distribution of peripheral blood cell counts in pre-PMF (top) and overt PMF (bottom). B Kaplan-Meier estimates of overall survival in patients with pre-PMF according to disease phenotype (cytopenic vs proliferative). C Competing risks-adjusted estimates of cumulative incidence of leukemic transformation in pre-PMF according to disease phenotype (cytopenic vs proliferative). D Competing risks-adjusted estimates of cumulative incidence of progression to overtly fibrotic phase in 139 pre-PMF patients according to disease phenotype (cytopenic vs proliferative). E. Kaplan-Meier estimates of overall survival in patients with overt PMF according to disease phenotype (cytopenic vs proliferative). F Competing risks-adjusted estimates of cumulative incidence of leukemic transformation in overt PMF according to disease phenotype (cytopenic vs proliferative). Abbreviations: CI confidence interval, CuI cumulative incidence, Hb hemoglobin, LT leukemic transformation, OS overall survival, Plt platelets, pre-PMF prefibrotic primary myelofibrosis, WBC white blood cells. Clinical and laboratory features of patients with WHO-defined prefibrotic and overt PMF stratified by the disease phenotype (cytopenic versus proliferative). AB allele burden, BM bone marrow, DIPSS dynamic international prognostic score system, HMR high molecular risk, IPSS international prognostic score system, LCM left costal margin, LDH lactate dehydrogenase, MIPSS70 mutation-enhanced international prognostic scoring system, MPN myeloproliferative neoplasm, PB peripheral blood, PMF primary myelofibrosis, Pre-PMF prefibrotic-PMF, SD standard deviation, WHO world health organization. Notes: ║HMR category is defined as the presence of at least one mutation in any of the following genes: ASXL1, EZH2, SRSF2, or IDH1/2. †≥2 HMR mutations indicates the presence of two or more mutated genes among ASXL1, EZH2, SRSF2, and IDH1/2 (two or more mutations in the same gene are counted as one). Evaluable patients for each variable are reported for prefibrotic/overt PMF, respectively.

Pre-PMF

In pre-PMF, patients with a CP were more likely to have male gender, older age, higher PB blasts and CD34 + cells, higher serum LDH, higher prevalence of splenomegaly, hepatomegaly, constitutional symptoms, and bone marrow (BM) fibrosis grade 1. Cytogenetic abnormalities and very high risk (VHR) karyotype were more frequent in the CP group. With regards to driver mutations, patients with CP were more likely to be JAK2-unmutated and triple negative, with no differences regarding JAK2 mutant burden. Among non-driver mutations, the cytopenic group was significantly enriched in mutations in ASXL1, N/KRAS, U2AF1, RUNX1, SETBP1, and CUX1, as well as ≥ 2 high molecular risk (HMR; i.e. ASXL1, EZH2, IDH1/2, SRSF2) mutations. There were no remarkable differences according to the number of cytopenias (not shown in detail). After a median follow-up of 76 (95% CI 59–95) months, 76 (35%) deaths were reported, with a median overall survival (OS) of 149 (95% CI 90–205) months. In univariate analysis, pre-PMF patients with CP had a remarkably inferior OS compared to their proliferative counterparts (HR 5.6, 95% CI 3.5–9, P <0.0001), with median of 36 (95% CI 26–60) and 193 (95% CI 130–232) months, respectively (Fig. 1B). The number of cytopenias (Supplemental Fig. 1A) and the severity of the CP (Supplemental Fig. 1B) were uninfluential. To dissect the contribution of individual cytopenias with other established prognostic factors, we conducted a multivariate Cox analysis that included leukopenia, severe/moderate anemia and thrombocytopenia, and the variables included in the MIPSS70 score. The final model identified both severe and moderate anemia, leukocytosis, constitutional symptoms and HMR category as independent predictors of inferior OS (Supplemental Table 2). At the last follow-up, 20 (10%) patients had transformed to acute leukemia. After competing risk analysis, the 5-year cumulative incidence (CuI) of leukemic transformation (LT) was significantly higher in patients with a CP compared to their proliferative counterparts (30%, 95% CI 16–45 and 5%, 95% CI 2–10, respectively; Grey test P <0.0001) (Fig. 1C). Neither the number nor the severity of cytopenias affected the rate of LT (Supplemental Fig. 1C, D). Finally, we aimed at assessing whether the risk of progression to overt PMF was affected by CP. A total of 139 (64%) pre-PMF patients were informative, based on the availability of clinical and/or histologic data defining the progression to overt PMF; of these, 32 (23%) progressed to overtly fibrotic phase. A CP was associated with a significantly shorter fibrotic progression-free survival (PFS; median 33 months, 95% CI 10-not reached) compared the proliferative counterpart (median 193 months, 95% CI 132-not reached) (HR 10.2, 95% CI 4–26.2, P <0.0001) (Supplemental Fig. 1E). The 5-year CuI of overt PMF progression, in a competing risk analysis, was significantly higher in pre-PMF patients with a CP compared to their proliferative counterparts (67%, 95% CI 26–89 and 15%, 95% CI 8–24, respectively; Grey test P <0.0001) (Fig. 1D). Of note, anemia and thrombocytopenia were significantly more prevalent among pre-PMF patients who progressed to overt-PMF within 5 years from diagnosis (respectively: 26% vs 3%, P <0.0001; 16% vs 0%, P <0.0001).

Overt PMF

A CP was associated with older age, higher CD34 + cell count, higher prevalence of BM fibrosis grade 3, lower JAK2 mutant burden, TN status, and U2AF1 mutations. Patients with ≥2 cytopenias were more likely to have karyotype abnormalities and mutations in CBL and U2AF1. After a median follow-up of 94 (95% CI 79–115) months, 118 (55%) deaths were reported, with a median OS of 65 (95% CI 54–87) months. The OS of patients with CP (median 54 months, 95% CI 44–72) was significantly shorter compared to the proliferative group (median 96 months, 95% CI 64–139) (HR 1.7, 95% CI 1.2–2.4, P = 0.0026) (Fig. 1E). Patients harboring ≥ 2 cytopenias had an inferior OS (median 43 months, 95% CI 19–55) compared to patients with one sole cytopenia (median 64 months, 95% CI 45–76) (HR 1.9, 95% CI 1.1–3.2, P = 0.0146) (Supplemental Fig. 2A). Remarkably, a severe CP was associated with significantly inferior OS compared to patients with not-severe cytopenias (HR 2.9, 95% CI 1.7–4.8, P <0.0001), with median of 28 (95% CI 19–47) and 72 (95% CI 52–91) months, respectively (Supplemental Fig. 2B). Upon multivariate Cox proportional hazards analysis, severe thrombocytopenia, severe anemia, PB blast count ≥ 2%, HMR category and ≥2 HMR mutated genes independently predicted for inferior OS (Supplemental Table 2); severe thrombocytopenia showed the highest HR (5.8, 95% CI 2.5–13.7). At last follow-up, a total of 28 (14%) patients transformed to acute leukemia. After competing risk analysis, the CuI of LT was not statistically different among cytopenic and proliferative patients, with 5-year rates of 15% (95% CI 8–23) and 12% (95% CI 6–20), respectively (Fig. 1F). The number and severity of cytopenias did not impact the CuI of LT (Supplemental Fig. 2C, D), although there was a trend for patients with severe compared to not-severe cytopenias (5-year CuI of LT 23%, 95% CI 10–38 and 10%, 95% CI 4–20, respectively; Grey test P = 0.0719). In summary, the current study provides a comprehensive analysis of the CP in a large cohort of WHO-defined pre- and overt PMF. We showed that cytopenic features, that are more common in overt than pre-PMF, are associated with distinct high-risk clinical and molecular features predominantly in pre-PMF. Of note, U2AF1 mutations emerged as a distinct abnormality of CP in both PMF subtypes, suggesting that they might contribute to ineffective hematopoiesis and reinforcing their adverse prognostic role [13, 14]. A CP was associated with inferior OS in both PMF subtypes, and with a higher risk of LT in pre-PMF. While in pre-PMF the adverse prognostic impact of a CP was independent of the number and severity of cytopenias, in overt PMF the impact on OS seemed to be affected mainly by the CP severity, with severe thrombocytopenia having the greatest impact. Finally, we highlighted that a CP is an important risk factor for fibrotic progression in patients with pre-PMF, particularly for those presenting with anemia and thrombocytopenia. Overall, our results further expand the characterization of the cytopenic features in PMF with novel insights as regards the distinction between pre- and overt PMF. Despite the limitations associated with its arbitrary definition, identification of the CP is straightforward, does not require invasive or advanced technologies and, above all, can be performed longitudinally. Cytopenia represents a significant challenge in the contemporary management of PMF. Currently, there are few agents aimed at treating cytopenic PMF, including immunomodulatory drugs, hypomethylating agents, and JAK inhibitors such as momelotinib and pacritinib, and development of new agents specifically tailored to this patient population remains an unmet need. The association with U2AF1 mutations may prompt the study of splicing modulators [14]. Supplemental Information
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1.  Leukemia risk models in primary myelofibrosis: an International Working Group study.

Authors:  A Tefferi; A Pardanani; N Gangat; K H Begna; C A Hanson; D L Van Dyke; D Caramazza; A M Vannucchi; E Morra; M Cazzola; A Pereira; F Cervantes; F Passamonti
Journal:  Leukemia       Date:  2012-01-13       Impact factor: 11.528

2.  Prognosis in transplant-eligible patients with agnogenic myeloid metaplasia: a simple CBC-based scoring system.

Authors:  David Dingli; Susan M Schwager; Ruben A Mesa; Chin Yang Li; Ayalew Tefferi
Journal:  Cancer       Date:  2006-02-01       Impact factor: 6.860

3.  Age and platelet count are IPSS-independent prognostic factors in young patients with primary myelofibrosis and complement IPSS in predicting very long or very short survival.

Authors:  Mrinal M Patnaik; Domenica Caramazza; Naseema Gangat; Curtis A Hanson; Animesh Pardanani; Ayalew Tefferi
Journal:  Eur J Haematol       Date:  2009-11-06       Impact factor: 2.997

4.  MIPSS70: Mutation-Enhanced International Prognostic Score System for Transplantation-Age Patients With Primary Myelofibrosis.

Authors:  Paola Guglielmelli; Terra L Lasho; Giada Rotunno; Mythri Mudireddy; Carmela Mannarelli; Maura Nicolosi; Annalisa Pacilli; Animesh Pardanani; Elisa Rumi; Vittorio Rosti; Curtis A Hanson; Francesco Mannelli; Rhett P Ketterling; Naseema Gangat; Alessandro Rambaldi; Francesco Passamonti; Giovanni Barosi; Tiziano Barbui; Mario Cazzola; Alessandro M Vannucchi; Ayalew Tefferi
Journal:  J Clin Oncol       Date:  2017-12-09       Impact factor: 44.544

5.  Prognostic factors in agnogenic myeloid metaplasia: a report on 195 cases with a new scoring system.

Authors:  B Dupriez; P Morel; J L Demory; J L Lai; M Simon; I Plantier; F Bauters
Journal:  Blood       Date:  1996-08-01       Impact factor: 22.113

6.  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).

Authors:  Francesco Passamonti; Francisco Cervantes; Alessandro Maria Vannucchi; Enrica Morra; Elisa Rumi; Arturo Pereira; Paola Guglielmelli; Ester Pungolino; Marianna Caramella; Margherita Maffioli; Cristiana Pascutto; Mario Lazzarino; Mario Cazzola; Ayalew Tefferi
Journal:  Blood       Date:  2009-12-14       Impact factor: 22.113

7.  New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment.

Authors:  Francisco Cervantes; Brigitte Dupriez; Arturo Pereira; Francesco Passamonti; John T Reilly; Enrica Morra; Alessandro M Vannucchi; Ruben A Mesa; Jean-Loup Demory; Giovanni Barosi; Elisa Rumi; Ayalew Tefferi
Journal:  Blood       Date:  2008-11-06       Impact factor: 22.113

8.  Dynamic model for predicting death within 12 months in patients with primary or post-polycythemia vera/essential thrombocythemia myelofibrosis.

Authors:  Constantine S Tam; Hagop Kantarjian; Jorge Cortes; Alice Lynn; Sherry Pierce; Lingsha Zhou; Michael J Keating; Deborah A Thomas; Srdan Verstovsek
Journal:  J Clin Oncol       Date:  2009-09-28       Impact factor: 44.544

Review 9.  The Myelodepletive Phenotype in Myelofibrosis: Clinical Relevance and Therapeutic Implication.

Authors:  Bridget K Marcellino; Srdan Verstovsek; John Mascarenhas
Journal:  Clin Lymphoma Myeloma Leuk       Date:  2020-02-26

10.  U2AF1 mutation promotes tumorigenicity through facilitating autophagy flux mediated by FOXO3a activation in myelodysplastic syndromes.

Authors:  Yuqian Zhu; Dandan Song; Juan Guo; Jiacheng Jin; Ying Tao; Zheng Zhang; Feng Xu; Qi He; Xiao Li; Chunkang Chang; Lingyun Wu
Journal:  Cell Death Dis       Date:  2021-06-28       Impact factor: 8.469

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