
==== Front
Curr Hematol Malig Rep
Curr Hematol Malig Rep
Current Hematologic Malignancy Reports
1558-8211
1558-822X
Springer US New York

39179882
739
10.1007/s11899-024-00739-6
Article
Prognostic and Predictive Models in Myelofibrosis
Mora Barbara 1
Bucelli Cristina 1
Cattaneo Daniele 12
Bellani Valentina 1
Versino Francesco 2
Barbullushi Kordelia 1
Fracchiolla Nicola 1
Iurlo Alessandra 1
Passamonti Francesco francesco.passamonti@unimi.it

12
1 https://ror.org/016zn0y21 grid.414818.0 0000 0004 1757 8749 Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Francesco Sforza, 35 – 20122, Milan, Italy
2 https://ror.org/00wjc7c48 grid.4708.b 0000 0004 1757 2822 Dipartimento Di Oncologia Ed Onco-Ematologia, Università Degli Studi Di Milano, Via Francesco Sforza, 35 - 20122, Milan, Italy
24 8 2024
24 8 2024
2024
19 5 223235
2 7 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Purpose of Review

Myelofibrosis (MF) includes prefibrotic primary MF (pre-PMF), overt-PMF and secondary MF (SMF). Median overall survival (OS) of pre-PMF, overt-PMF and SMF patients is around 14 years, seven and nine years, respectively. Main causes of mortality are non-clonal progression and transformation into blast phase.

Recent Findings

Discoveries on the impact of the biological architecture on OS have led to the design of integrated scores to predict survival in PMF. For SMF, OS estimates should be calculated by the specific MYSEC-PM (MYelofibrosis SECondary-prognostic model). Information on the prognostic role of the molecular landscape in SMF is accumulating. Crucial treatment decisions for MF patients could be now supported by multivariable predictive algorithms. OS should become a relevant endpoint of clinical trials.

Summary

Prognostic models guide prediction of OS and treatment planning in MF, therefore, their timely application is critical in the personalized approach of MF patients.

Keywords

Myelofibrosis
Prognosis
Next generation sequencing
Allogenic-stem cells transplant
JAK inhibitors
Università degli Studi di MilanoOpen access funding provided by Università degli Studi di Milano within the CRUI-CARE Agreement.

issue-copyright-statement© Springer Science+Business Media, LLC, part of Springer Nature 2024
==== Body
pmcIntroduction

Myelofibrosis (MF) is a BCR::ABL1-negative myeloproliferative neoplasm (MPN) characterized by splenomegaly, constitutional symptoms, heterogeneous blood cell alterations and bone marrow fibrosis (BMF). MF also presents an inherent tendency to evolve into blast phase (BP) [1, 2]. MF encompasses primary MF (PMF), which includes prefibrotic- (pre) and overt-PMF, and secondary MF (SMF), in case of a previous diagnosis of polycythemia vera (PV) or essential thrombocythemia (ET) [1–5].

MF is a rare neoplasm, with an incidence of 0.44/100000 patients per year in US by a recent report [6]. Median age at MF onset is in the seventh decade [6], but it could also affect younger patients, who need an accurate prognostic assessment for possible selection to allogeneic hematopoietic stem cells transplant (allo-SCT).

MF is characterized by phenotypic driver gene mutations involved in the downstream activation of the JAK-STAT pathway [1, 7]. Two-thirds of patients with PMF harbor JAK2V617F, 25% CALR, and 10% each MPL or no driver mutation (‘triple negative’ status, TN) [8]. Almost all post PV (PPV-) MF carry JAK2 mutations, while near half post ET (PET-) MF patients show JAK2V617F, 30% CALR and 5–10% MPL mutations or TN status [9]. CALR mutations are distinguished in type 1/type 1(-like) and type 2/type 2(-like), respectively a deletion of 52 base pairs (bp) and an insertion of five bp (or similar alterations). Of note, CALR and MPL mutations could be found in 30% of ET and MF cases with low (< 5%) JAK2V617F variant allele frequency (VAF), with “double mutated” subjects showing higher platelets vs those with just low JAK2V617F VAF [10].

Additional non-driver myeloid neoplasms-associated gene variants (M-GVs) have been identified in MF [8]. About 80% of PMF and 69% of SMF cases carry M-GVs, respectively [8, 11, 12]. Involved genes are related to epigenetic modifiers (DNMT3A, TET2 and ASXL1), splicing factors (SF3B1, SRSF2 and U2AF1), metabolic enzymes (IDH1 and IDH2), and tumor suppressors (TP53) [8, 11, 12]. Information on the prevalence and impact of M-GVs in MF is accumulating, due to the increasing diffusion of methods such as Next generation sequencing (NGS).

Patients affected by MF have a significantly reduced outcome, with a median OS of 14 years, seven and nine years in pre-PMF, overt-PMF and SMF, respectively [13–15]. Both in PMF and in SMF cohorts, non-clonal progression accounts for around one third of deaths [13, 14], including second malignancies [16], infections and cardiovascular events [2]. Evolution into BP occurs in 10–15% of MF cases, with a severely reduced OS [14, 17].

Nonetheless, in recent years improvement in prognosis has been registered. A retrospective study compared 844 MF patients by decade of presentation: 2000–2010 and 2011–2020 [18]. In the latter decade, reported median OS was significantly higher (63 vs 48 months), even in cases with unfavourable features [18]. This is due to a greater awareness of disease, a better insight on the biological background, the widespread use of JAK inhibitors (JAKis), improved supportive care, and a more accurate selection and management of candidates to allo-SCT [18–23].

On the contrary, the outcome of post-MF BP still remains dismal, representing an unmet clinical need. Risk factors for BP have been extensively investigated and are outside the scope of this review [24, 25]. Of note, our group recently described a wide cohort of PMF and SMF patients, confirming the predictive role of anemia, also while on JAKis treatment [25].

Conventional evaluation of prognosis in MF is based on symptoms, demographic and hematologic data [13, 26]. However, the increasing knowledge on the biological landscape has led to the design of integrated prognostic models, now of widespread use mainly in PMF. Unfortunately, real world (RW) data show that around 40% of MF patients still receive an inaccurate risk definition and one third of cases any categorization at all [27].

In this review, we will focus on the evolving paradigm of survival definition in PMF and SMF over the years. We will also underline the importance of a correct selection of potential candidates to allo-SCT. Then, recent insights on the outcome with JAKis and innovative drugs will be presented. All this information will guide treating physicians to a personalized approach of individuals affected by MF.

Primary Myelofibrosis: How to Make the Best Use of Multiple Prognostic Scores

The 2009 International Prognostic Scoring System (IPSS) represents still nowadays the most used prognostic score at time of PMF diagnosis [26]. Variables included are age > 65 years, hemoglobin (Hb) < 10 g/dL, leukocyte count > 25 × 10^9/L, circulating blasts ≥ 1%, and constitutional symptoms [26]. Every parameter has been scored one point [26]. Median OS of the four IPSS categories (low, intermediate-1, intermediate-2 and high risk) spans between 11.3 and 2.3 years [26].

In 2011, the Dynamic IPSS (DIPSS) has been developed to be applied at any time during follow-up [13]. DIPSS includes the same variables of IPSS, but the prognostic weight of anemia is higher (Table 1) [13]. Subjects are divided into four risk groups, with intermediate-2 and high risk categories having a median OS of less than five years (Table 1) [13]. Table 1 Prognostic models for patients with primary and secondary myelofibrosis

	DIPSS	DIPSS+	MIPSS-70	MIPSS-70+ version 2.0	MYSEC-PM	
Patients’ characteristics (score)	Age > 65 y (1)

Constitutional symptoms (1)

	Age > 65 y (1)

Constitutional

symptoms (1)

RBC transfusions

need (1)

	Constitutional

symptoms (1)

	Constitutional

symptoms (2)

	Age (0.15 × y)

Constitutional

symptoms (1)

	
Laboratory values (score)	Hb < 10 g/dl (2)

WBC > 25 × 10^9/l (1)

Blasts ≥ 1% (1)

	Hb < 10 g/dl (1)

WBC > 25 × 10^9/l (1)

Blasts ≥ 1% (1)

PLT < 100 × 10^9/l (1)

	Hb < 10 g/dl (1)

WBC > 25 × 10^9/l (2)

Blasts ≥ 2% (1)

PLT < 100 × 10^9/l (2)

	Severe anemia2 (2)

Moderate anemia3 (1)

Blasts ≥ 2% (1)

	Hb < 11 g/dl (2)

Blasts ≥ 3% (2)

PLT < 150 × 10^9/l (1)

	
Driver mutation

(score)

			Absence of type 1/like CALR (1)	Absence of type 1/like CALR (2)	Absence of CALR (2)	
Myeloid-gene variants

(score)

			1 HMR (1)

 ≥ 2 HMR (2)

	1 HMR included U2AF1Q157 (2)

 ≥ 2 HMR included U2AF1Q157 (3)

		
Karyotype

(score)

		Unfavourable1 (1)		Unfavourable4 (3)

Very high-risk5 (4)

		
Bone marrow (score)			BMF grade ≥ 2 (1)			
Risk (score),

median survival

	Low (0), NR

Int-1 (1–2), 14.2 y

Int-2 (3–4), 4 y

High (5–6), 1.5 y

	Low (0), 15.4 y

Int-1 (1), 6.5 y

Int-2 (2–3), 2.9 y

High (≥ 4), 1.3 y

	Low (0–1), NR

Int (2–4), 6.3 y

High (≥ 5), 3.1 y

	Very low (0), NR

Low (1–2), 16.4 y

Int (3–4), 7.7 y

High (5–8), 4.1 y

Very high (≥ 9), 1.8 y

	Low (< 11), NR

Int-1 (11–13), 9.3 y

Int-2 (14–15), 4.4 y

High (≥ 16), 2 y

	
DIPSS = Dynamic International Prognostic Scoring System; MIPSS = Molecular Enhanced International Prognostic Score System; MYSEC-PM = MYelofibrosis SECondary to polycythemia vera and essential thrombocythemia-Prognostic Model; y = years; RBC = red blood cells; Hb = hemoglobin; WBC = white blood cells; PLT = platelets; HMR = high molecular risk (one among ASXL1, EZH2, SRSF2, or IDH1/2); BMF = bone marrow fibrosis; NR = not reached; Int = intermediate

1 = complex karyotype or sole or two abnormalities including + 8, -7/7q-, i(17q), -5/5q-, 12p-, inv(3) or 11q23 rearrangement

2 = Hb < 8 g/dl in women, Hb < 9 g/dl in men

3 = Hb 8–9.9 g/dl in women, Hb 9–10.9 g/dl in men

4 = chromosomal abnormalities except “very high-risk” (see below) or sole 13q-, + 9, 20q-, chromosome 1 translocation/ duplication or sex chromosome alterations including -Y

5 = single/multiple abnormalities of -7, i(17q), inv(3)/3q21,12p-/12p11.2,11q-/11q23, + 21, or other autosomal trisomies except + 8/9

The DIPSS+ model is a revised version of the DIPSS [28], that considers also red blood cell (RBC) units need, platelet (PLT) count, and karyotype (Table 1) [28, 29]. Of note, only patients with overt-PMF were considered when the overmentioned scores were developed, and it has been shown that IPSS could not discriminate pre-PMF patients well [15, 30].

Among driver mutations, CALR type 1 has been associated with the most favorable outcome in PMF [15, 31]. As for M-GVs, abnormalities in ASXL1 are the most frequent (30% of patients) [32]. Together with ASXL1, M-GVs in SRSF2, EZH2, and IDH1/IDH2 were defined as high molecular risk (HMR) mutations, since they were correlated with reduced OS and increased risk of BP [32]. The impact of HMR alterations depends also on their number [15, 32, 33]. CALR type 1(-like) and HMR mutations have been integrated in the Mutation-enhanced IPSS-70 (MIPSS-70) model, developed for potential candidates to allo-SCT (subjects ≤ 70 years) (Table 1) [33]. In this cohort, 80% of patients showed CALR type 1 wild type, 31–41% and 8–9% at least one or more HMR alterations, respectively [33]. The MIPSS-70 includes also histological features, underlying the relevance of at least grade 2 BMF (overt-PMF) compared to less than grade 2 (pre-PMF) [33]. Median OS of the high risk MIPSS-70 group is below five years (Table 1) [33].

The MIPSS-70 was lately revised in the MIPSS-70+ model, that included information on unfavorable cytogenetics, the latter defined as any abnormal karyotype (AK), except for sole abnormalities of 20q-, 13q-, + 9, chromosome 1 translocation/duplication, -Y, or sex chromosome abnormality excluding -Y [33]. Of note, both MIPSS-70 and MIPSS-70+ scores appear also able to discriminate the mortality risk of patients above 70 years [33].

A further revision, the MIPSS-70+ version 2.0, encompasses U2AF1Q157 among HMR mutations, includes sex- and severity-adjusted anemia cut-offs and a so-called “very high” cytogenetic risk group (the latter detailed in Table 1) [34]. On the other side, information on BMF grade, leukocyte and PLT count has been omitted. Patients in the high and very-high risk MIPSS-70+ version 2.0 groups have an estimated OS below five years [34]. The Genetically Inspired Prognostic Scoring System (GIPSS) considers only cytogenetic and molecular information, as the absence of CALR type 1(-like) and the presence of ASXL1, SRSF2 or U2AF1Q157 mutations [35]. Predictive power of this model was suggested by the Authors to be comparable to that of MIPSS-70+ [35].

The updated National Comprehensive Cancer Network (NCCN) guidelines (version 1.2024) suggest applying in PMF the prognostic models reported in Table 1 [36], based on the type of available information: the MIPSS-70 or MIPSS-70+ version 2.0 for molecularly annotated cases, the DIPSS+ if absent molecular data but known karyotype, or the DIPSS if even cytogenetics is unavailable.

In the clinical practice, we calculate all the overmentioned scores (Table 1) at the same time [2]: DIPSS is easy and quick to calculate, but time-requiring data on BMF grade and M-GVs are particularly relevant. In our opinion, the high frequency of “dry tap” in PMF is the main limit to cytogenetics-based models, but this data might be obtained on peripheral blood.

To simultaneously calculate these models, a PMF-specific web calculator has been recently proposed by our group: https://pmfscorescalculator.com [2]. We are aware that this practice might lead to discordant mortality estimates among scores [2]: in such cases, we suggest a close follow-up of the patient, for detecting early signs of disease progression and possible indication to allo-SCT [2].

Besides the over mentioned well-structured models, several other factors have been correlated with outcome in PMF.

Among hematological variables, a “myelodepletive” phenotype (the presence of at least one cytopenia) was associated with a shorter OS in univariate analysis [37]. To overcome the poorly standardizable definition of circulating blasts by morphology, the application of flow cytometry seems to improve the accuracy of the MIPSS-70 [38].

An attempt was made to fit comorbidities into conventional models, but results are not definitive to date [39, 40].

Information on the prognostic impact of M-GVs is accumulating. The French group proposed a “NGS model” that distinguishes four genetic groups [41]: TP53, “High risk” (≥ 1 mutation in EZH2, CBL, U2AF1, SRSF2, IDH1 and IDH2), ASXL1-only and “Others” mutations. In this analysis, ASXL1 alterations were associated with an unfavorable outcome only if they co-occurred with TP53 or “High risk” M-GVs [41]. On the contrary, applying the same NGS categories to another independent cohort of PMF cases [42], those mutated for TP53 or for “High risk” genes displayed the worst OS, but also ASXL1 mutated-only group had a clearly reduced outcome with respect to the “Others” [42]. ASXL1 mutations co-occurred in two thirds of “High risk” cases and implied a worse OS [42]. A recent study by the Spanish group pointed out the independent relevance of ASXL1 VAF > 20%, more than gene mutation per se [43]. Alterations in RAS/MAPK pathway genes have been related with an unfavorable OS in overt-PMF [44, 45]. However, the integrity of the MIPSS-70 variants was not significantly upgraded by the inclusion of RAS/MAPK mutations, as of TP53 and RUNX1 alterations [45]. Besides, the low incidence of those M-GVs will require an external validation for confirming their negative impact [45]. Of note, ASXL, IDH1/2, N/KRAS, U2AF1 and CUX1 alterations are enriched within the overmentioned “myelodepletive” phenotype [37]. Very recently, a Spanish collaborative study has proposed to apply artificial intelligence (AI) methods for integrating NGS and clinical data to better define outcome [46].

From a biological point of view, levels of the neutrophil chemoattractant CXCL8 are increased in PMF and negatively correlate with OS [47]. An Italian collaborative group evaluated the expression of 201 genes in granulocytes of MF patients, identifying outcome-related transcripts [48]. Subjects with pre-PMF were characterized by a “low risk” gene espression (GE) signature, with more favourable OS and BP-free survival [48]. The same group demonstrated the increased expression profile of a set of circulating long non-coding RNAs (lncRNAs), that appeared to be evaluable biomarkers of unfavorable outcome [49]. In CD34 + hematopoietic stem/progenitor cells from MF, reactive oxygen species (ROS) levels correlate with shorter OS [50].

Secondary Myelofibrosis: How to Specifically Define Prognosis

In a recent meta-analysis of over 3.000 PV patients treated with hydroxyurea (HU), the rate of SMF was 0.9%, 5% and 33.7% at 1, 5 and 10 years, respectively [51]. Out of 576 ET subjects, 9.5% evolved into SMF after 15 years of follow up [17].

Median time to transformation into SMF seems to be related to the type of driver mutation [52]: in a multivariable model, patients with CALR mutated ET had a significantly longer time to progression compared to JAK2 mutated ET/PV and, even more, to TN cases [52].

Predictive factors for evolution of PV or ET cases to SMF have been extensively investigated [24]: clinical features, cytogenetic alterations, bone marrow (BM) characteristics, driver mutations type and VAF, M-GVs and dysregulation of biological pathways are involved. All this information could therefore lead to a personalized monitoring of PV and ET patients [24].

Among cytoreductive therapies, only some retrospective data suggested a protective role of interferons [53, 54]. More relevant appears the impact of long-term treatment with ruxolitinib (RUX) in PV cases resistant or intolerant to HU [55, 56]. Both in the prospective randomized phase 2 MAJIC-PV trial and in an Italian RW experience, the achievement of at least a partial molecular response (≥ 50% reduction in JAK2V617F VAF) was correlated to a significantly longer SMF-free survival [55, 56].

When a diagnosis of SMF is established [1], OS estimate could not be properly calculated by the prognostic models used for PMF [57, 58]. In 2014, an international study focused just on SMF cases, called the MYelofibrosis SECondary to PV and ET (MYSEC) project, was started [9].

The original database retrospectively included 685 PPV- and PET-MF cases annotated for driver mutations [9]. Median OS was 9.3 years for the whole dataset, with a borderline difference between the two subtypes (14.5 vs 8.1 years for PET- and PPV-MF) [9]. In a multivariable analysis, CALR mutated patients had a better outcome compared to JAK2V617F mutated SMF [9].

The MYSEC cohort, that represents to date the largest dataset of SMF patients, allowed to generate a specific clinical-molecular prognostic score, the MYSEC-Prognostic Model (MYSEC-PM) [14]. As reported in Table 1, the higher prognostic weight was assigned to anemia, increased blasts count and absence of CALR alterations [14]. Four MYSEC-PM risk categories were identified, with intermediate-2 and high risk cases having a median OS below five years [14]. The MYSEC-PM could be easily calculated by a nomogram depicted on the original paper and by an online application (https://mysec.shinyapps.io/prognostic_model/) [14]. Even though this score was established at time of SMF diagnosis, it has also been dynamically validated [59].

Other prognostic factors have been investigated in SMF.

Similar to PMF models, also the MYSEC-PM includes blast count by morphology as a variable [14]. Differently from PMF, integrating flow cytometry results did not outperform the standard MYSEC-PM counterpart [38]. In the MYSEC database, female patients showed a better OS, also considering age at SMF diagnosis [60]. This is in line with data on large cohorts of ET subjects [61], while the prognostic relevance of gender in PV is still a matter of debate [62].

The impact of BMF (grade 2 vs 3) has been investigated in a more recent subanalysis of the MYSEC cohort [63]: out of 805 SMF, 34% had a grade 3 BMF at evolution. In univariate analysis, this latter cohort had a significantly lower OS compared to patients with grade 2 BMF (7.4 vs 8.2 years), underlying the importance of performing a BM biopsy to confirm SMF [63].

Around one third of 376 cytogenetic-annotated MYSEC cases had an AK [64]. Those subjects had a significantly reduced outcome compared to normal karyotype (NK): the median OS was 6.1 vs 10.1 years [64]. Of note, patients with monosomal karyotype (MK), complex karyotype (CK) without MK and those with CK had an estimated OS below 3.5 years [64]. Integrating cytogenetics did not improve the prognostic power of the MYSEC-PM, nonetheless we suggest assessing it in case of suspected SMF evolution [64]. Recently, Shide et al. have applied the DIPSS+ model to a cohort of Japanese SMF patients, and they showed a better outcome prediction compared to the MYSEC-PM [65]. Of note, their study included just 183 cases [65].

As for M-GVs, information in SMF is accumulating. Looking at HMR, Rotunno et al. confirmed the unfavorable prognostic role only of SRSF2 in PET-MF [66]. Applying the over mentioned “NGS model” to 193 SMF cases, TP53 mutations conferred the worst outcome (median OS, 13 months), while the prognosis of ASXL1 mutated-only patients was similar to the “Others” and the “High-risk” groups (median OS of 141, 131 and 58 months, respectively) [41, 42]. ASXL1 mutations were detected in over half of “High-risk” subjects, without influencing their outcome [42]. Another group suggested that the performance of the MIPSS-70+ version 2.0 might be superior to the MYSEC-PM (C-index 0.79 vs 0.73), but only 155 SMF patients were included [67]. Besides, looking at OS estimates in that analysis, MIPSS-70+ version 2.0 recognized only three out of 58 patients with median OS below five years (so candidates for allo-SCT indication), finally limiting the usefulness of the model in the setting of SMF [67]. Loscocco et al. showed that alterations of the splicing factor SF3B1, found in 5% of 195 SMF patients, could be related to reduced OS [68].

Mora et al. reported the preliminary results of 639 NGS-annotated MYSEC cases [12]: around 69% of the cohort presented at least one M-GV. Among the latter, 31% and 18% showed two and at least three alterations [12]. The most frequent (≥ 10%) M-GVs interested ASXL1, TET2, DNMT3A and TP53 [12]. The number of M-GVs appeared to be prognostically relevant in univariate analysis: subjects without them had a median OS significantly longer than cases with any alteration (14.8 vs 11.8 years) [12]. Of note, patients with at least three M-GVs had a remarkably reduced outcome compared to those with at most two mutations (median OS, 8.6 vs 14.8 years) [12]. In our opinion, AI methods should be applied to identify the most significant variables for integrated models [69, 70].

From a biological point of view, the overmentioned “high risk” GE signatures were enriched in PPV/PET-MF cases [48]. Similar to PMF, a set of lncRNAs with unfavorable impact on outcome was more frequently expressed [49]. Besides, high plasma levels of ROS were found to be a surrogate of shorter OS [50].

Allogenic Hematopoietic Stem Cells Transplant: How to Select the Best Candidates

To date, allo-SCT is the only curative treatment for MF patients [71]. When evaluating possible candidates, patients’ age is not considered a limit per se [72]. More important is an accurate estimation of the outcome related not only to MF biology, but also to possible allo-SCT complications [73].

Very recently, updated recommendations by the European Society for Blood and Marrow Transplantation/European LeukemiaNet (EBMT/ELN) International Working Group were published, in light of contemporary management of MF patients [23]. It is acceptable to candidate fit subjects younger than 70 years, with an expected OS below five years, i.e., intermediate-2 and high risk DIPSS/MYSEC-PM or high risk MIPSS-70(+) [23]. Cases with intermediate-1 DIPSS or intermediate MIPPS-70(+) should be discussed, balancing patients’ preferences, available treatment alternatives, and other risk features, i.e., multi-hit TP53 mutations, that have been associated with increased risk of BP [23, 74]. DIPSS was also judged useful for defining the timing of allo-SCT [23].

Once a potential candidate has been selected through these criteria, two other scores should be applied at referral to allo-SCT, with the aim of predicting subsequent outcome [75, 76]. Gagelmann et al. described the Myelofibrosis Transplant Scoring System (MTSS), that considers driver mutation, ASXL1 variant, age, performance status, PLT and leukocyte count, and type of donor (Table 2) [75]. Of note, the MTSS was proposed and validated both in PMF and SMF, but the impact of ASXL1 in SMF is yet to be cleared. Table 2 Predictive models for allogenic hematopoietic stem cells transplant outcome in myelofibrosis

	MTSS	CIBMTR/EBMT	
Patients’ characteristics

(score)

	Age ≥ 57 y (1)

Karnofsky < 90% (1)

MMUD (2)

	Age > 50 y (1)

MMUD (2)

MUD (1)

	
Laboratory data

(score)

	WBC > 25 × 10^9/l (1)

PLT < 150 × 10^9/l (1)

	Hb < 10 g/dl (2)	
Driver mutation (score)	Absence of CALR/MPL (2)		
Myeloid-gene mutations (score)	ASXL1 (1)		
Risk category (score),

survival1

	Low (0–2), 90%

Int (3–4), 77%

High (5), 50%

Very high (6–9), 34%

	Low (0–2), 69%

Int (3–4), 51%

High (5), 34%

	
Risk category (score),

TRM

	Low (0–2), 10%

Int (3–4), 22%

High (5), 36%

Very high (6–9), 57%

	Progressively increasing with higher scores	
MTSS = Myelofibrosis Transplant Scoring System; CIBMTR = Center for International Blood and Marrow Transplant Research; EBMT = European Society for Blood and Marrow Transplantation; y = years; Hb = hemoglobin; WBC = white blood cells; PLT = platelets; MMUD = mismatched unrelated donor; MUD = matched unrelated donor; Int = intermediate; TRM = transplant related mortality

1 = 5-years survival for MTSS; 3-years survival for CIBMTR/EBMT

Within the MTSS, the median 5-year OS ranged between 90% and 34%, while in the same time frame allo-SCT related mortality (TRM) varied, inversely, from 10% to 57% [75]. Based on this data, the updated EBMT/ELN guidelines suggest considering low and some intermediate risk MTSS patients for allo-SCT [23]. Tamari et al. developed an easier model in a setting without molecular testing (Table 2) [76]: age, type of donor and Hb levels at time of allo-SCT influenced both the 3-year OS probability and TRM [76].

Impact of donor type in MF is well known: out of 233 cases, the 5-year OS after allo-SCT was 56% with matched sibling, 48% with matched unrelated, and 34% with partially matched/mismatched unrelated donors [71].

We are aligned with current EBMT/ELN guidelines indications [73], but we also believe that a more personalized selection will derive applying integrated statistical methods, to identify different clinical-genomic subgroups [69, 70].

JAK Inhibitors and Investigative Drugs: How to Read Data on Survival

Data on the impact of JAKis on outcome should be interpreted considering that OS did not represent the primary endpoint of related clinical trials, and that matched-controlled, or population-based studies have some limitations [2]. At present, most of the evidence concerns RUX [18–20, 24, 77].

Long-term pooled analysis of the COMFORT-I/II studies showed a 30%-reduction in risk of death in intermediate-2/high risk MF vs controls [20, 78, 79]. Moreover, 4-years OS was significantly longer (63% vs 57%) if RUX was started within one year from diagnosis compared to after the first 12 months, favouring an early initiation of treatment [80]. RW data with appropriate follow-up came from the ERNEST (European Registry for Myeloproliferative Neoplasms: Toward a Better Understanding of Epidemiology, Survival, and Treatment) project, where the outcome was significantly improved in patients treated with RUX compared to HU (median OS, 6.7 vs 5.1 years) [81]. This difference was even more evident in a propensity score-matching analysis, that anyway regarded only a small subgroup [81].

We previously reviewed factors impacting OS in RUX-treated patients [24]: baseline prognostic risk and blasts count, M-GVs, spleen response and RBC transfusions play a role [82–90]. More recently, Kuykendall et al. showed that changes in albumin levels are associated with OS [91].

Around half of patients discontinue RUX at 3 years, mostly for progression or intolerance, with a subsequent dismal outcome [92, 93]. To early identify subjects that could benefit from a prompt treatment shift, we investigated predictors of OS collected during the first six months of RUX [85]. This collaborative effort led to the design of a new prognostic model, named Response to Ruxolitinib After 6 Months (RR6, easily computable at http://www.rr6.eu/) [85]. This score can distinguish three categories with different OS after 6 months of RUX treatment based on the changes of RUX dose and of spleen length, and on the need of RBC units during the same period (Table 3) [85]. Based on the RR6 model, some intermediate risk cases and the high risk group (36% of the cohort, median OS of 33 months) might be candidate to a rapid shift to second line therapies, investigational trials or even to allo-SCT (Table 3) [85]. Table 3 The Response to Ruxolitinib After 6 Months (RR6) model

Variable	Points	
RUX dose < 20 mg BID at baseline, month 3, month 6	1	
 ≤ 30% spleen length reduction at month 3 and month 6	1.5	
RBC units need at month 3 and/or month 6	1	
RBC units need at baseline, month 3 and month 6	1.5	
Risk category, score (% of patients)	Overall survival, months	
Low, 0 (19%)	Not reached	
Intermediate, 1–2 (45%)	61	
High, ≥ 2.5 (36%)	33	
RUX = ruxolitinib; BID = every 12 h; RBC = red blood cells

Some speculations could be done also on other JAKis. Progression-free survival looked significantly prolonged with fedratinib vs placebo in the JAKARTA trial [21, 94]. In the SYMPLIFY-1 study, there was an association between RBC-transfusion independence (TI) at 24 weeks and improved 3-year OS with momelotinib (MMB), suggesting RBC-TI as a potential surrogate for disease modification with this JAKi [95].

In phase 2 studies, some investigative drugs (added-on to RUX or alone) seem to be associated with benefit on OS, especially in case of “biological responses” (i.e., reduction of driver genes VAF, BMF grade or circulating CD34 + cells) [96–100]. Of course, definitive conclusions could be drawn only by randomized trials, by a long follow-up and ideally considering as primary endpoint either OS or potential surrogate markers [99]. Interestingly, changes in BMF grade at 6 months in SIMPLIFY-1 patients treated either with RUX or MMB did not correlate with OS, suggesting that the potential “disease-modifying” effect of a class of agents could be related to its specific mechanism of action [101].

Conclusions

In the recent years, outcome of MF patients has improved, due to early diagnosis, use of JAKis and improved management of candidates to allo-SCT. Nonetheless, MF still remains a severe disease, that deserves an accurate prognostic definition.

The increased knowledge on the biological landscape of PMF has broadened the number of available survival models, that should be applied simultaneously for a more personalized definition of outcome, especially in younger patients.

The evidence that SMF is a specific entity has led to a more intensive monitoring of PV and ET cases for possible signs of progression. Moreover, we have now an ad hoc prognostic score, the MYSEC-PM, unanimously adopted by the NCCN and European guidelines. Integrated statistical methods will help to incorporate NGS results on SMF prognostication.

Fit MF patients with an estimated survival below five years are potential candidate to allo-SCT, but application of models such as the MTSS is required to predict post-transplant outcome and related complications.

Majority of MF patients are not suitable for allo-SCT and mostly receive JAKis. In RUX treated cases, the RR6 model is a useful tool to early identify subjects with reduced survival and that deserve a prompt treatment shift. There are some signs of survival benefit with RUX or innovative drugs in phase 2 studies, but we believe that more definitive evidence could be drawn only by designing trials with survival or its surrogate markers as primary endpoint.

Key References

Arber DA, Orazi A, Hasserjian R, Borowitz MJ, Calvo KR, Kvasnicka HS, et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data. Blood. 2022;140(11):1200-228.WHO 2022 classification of myeloid malignancies.

Barosi G, Mesa RA, Thiele J, Cervantes F, Campbell PJ, Versovsek S, et al. Proposed criteria for the diagnosis of post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a consensus statement from the International Working Group for Myelofibrosis Research and Treatment. Leukemia. 2008;22(2):437-38.International diagnostic criteria for secondary myelofibrosis.

Passamonti F, Mora B, Giorgino T, Guglielmelli P, Cazzola M, Maffioli M, et al. Driver mutations' effect in secondary myelofibrosis: an international multicenter study based on 781 patients. Leukemia. 2017;31(4):970-73.Distribution and correlations of driver mutations in the widest cohort of secondary myelofibrosis patients to date.

Luque Paz D, Kralovics R, Skoda RC. Genetic basis and molecular profiling in myeloproliferative neoplasms. Blood.2023;141(16):1909-921.Recent comprehensive review of genetic basis of myeloproliferative neoplasms.

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(9):1703-8.Dynamic prognostic model for primary myelofibrosis.

Passamonti F, Giorgino T, Mora B, Guglielmelli P, Rumi E, Maffioli M, et al. A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis. Leukemia. 2017;31(12):2726-31.Specific prognostic model for secondary myelofibrosis.

Guglielmelli P, Pacilli A, Rotunno G, Rumi E, Rosti V, Delaini F, et al. Presentation and outcome of patients with 2016 WHO diagnosis of prefibrotic and overt primary myelofibrosis. Blood. 2017;129(24):3227-36.Distinctions in presentation and survival between prefibrotic- and overt-primary myelofibrosis.

Tefferi A, Guglielmelli P, Larson DR, Finke C, Wassie EA, Pieri L, et al. Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myelofibrosis. Blood. 2014;124(16):2507-13.Description of long term events in myeloproliferative neoplasms.

Masarova L, Bose P, Pemmaraju N, Daver NG, Sasaki K, Chifotides HT, et al. Improved survival of patients with myelofibrosis in the last decade: Single-center experience. Cancer. 2022;128(8):1658-65.Evolution of outcome in myelofibrosis over years.

Verstovsek S, Parasuraman S, Yu J, Shah A, Kumar S, Xi A, et al. Real-world survival of US patients with intermediate- to high-risk myelofibrosis: impact of ruxolitinib approval. Ann Hematol. 2022;101(1):131-37.Impact of current myelofibrosis treatments on outcome in myelofibrosis.

Verstovsek S, Gotlib J, Mesa RA, Vannucchi AM, Kiladjian JJ, Cervantes F, et al. Long-term survival in patients treated with ruxolitinib for myelofibrosis: COMFORT-I and -II pooled analyses. J Hematol Oncol. 2017;10(1):156.Post-hoc analysis on survival of COMFORT studies.

Pardanani A, Tefferi A, Masszi T, Mishchenko E, Drummond M, Jourdan E, et al. Updated results of the placebo-controlled, phase III JAKARTA trial of fedratinib in patients with intermediate-2 or high-risk myelofibrosis. Br J Haematol. 2021;195(2):244-48.Results of fedratinib in patients with myelofibrosis naïve to treatment.

Kröger N, Bacigalupo A, Barbui T, Ditschkowski M, Gagelmann N, Griesshammer M, et al. Indication and management of allogeneic haematopoietic stem-cell transplantation in myelofibrosis: updated recommendations by the EBMT/ELN International Working Group. Lancet Haematol. 2024;11(1):e62-74.Updated international guidelines on allogeneic haematopoietic stem-cell transplantation in myelofibrosis.

Guglielmelli P, Lasho TL, Rotunno G, Mudireddy M, Mannarelli C, Nicolosi M, et al. MIPSS70: Mutation-Enhanced International Prognostic Score System for Transplantation-Age Patients With Primary Myelofibrosis. J Clin Oncol. 2018;36(4):310-18.Molecularly-annotated prognostic score for primary myelofibrosis patients potentially candidates to allogeneic haematopoietic stem-cell transplantation.

Tefferi A, Guglielmelli P, Lasho TL, Gangat N, Ketterling RP, Pardanani A, et al. MIPSS70+ Version 2.0: Mutation and Karyotype-Enhanced International Prognostic Scoring System for Primary Myelofibrosis. J Clin Oncol. 2018;36(17):1769-70.Integration of molecular and cytogenetic data in a prognostic score for primary myelofibrosis patients potentially candidates to allogeneic haematopoietic stem-cell transplantation.

Tefferi A, Guglielmelli P, Nicolosi M, Mannelli F, Mudireddy M, Bartalucci N, et al. GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis. Leukemia. 2018;32(7):1631-42.Prognostic score only based on biology for primary myelofibrosis.

Network NCC. Myeloproliferative neoplasms. 2024 [Available from https://www.nccn.org/professionals/physician_gls/pdf/mpn.pdf]Current NCCS guidelines for myelofibrosis.

Luque Paz D, Riou J, Verger E, Cassinat B, Chauveau A, Ianotto JC, et al. Genomic analysis of primary and secondary myelofibrosis redefines the prognostic impact of ASXL1 mutations: a FIM study. Blood Adv. 2021;5(5):1442-51.Analysis of a large cohort of myelofibrosis patients annotated for NGS.

Guglielmelli P, Coltro G, Mannelli F, Rotunno G, Loscocco GG, Mannarelli C, et al. ASXL1 mutations are prognostically significant in primary myelofibrosis, but not myelofibrosis following essential thrombocythemia or polycythemia vera. Blood Adv. 2022;6(9):2927-31.Discussion of the prognostic role of ASXL1 in primary and secondary myelofibrosis.

Harrison CN, Nangalia J, Boucher R, Jackson A, Yap C, O’Sullivan J, et al. Ruxolitinib Versus Best Available Therapy for Polycythemia Vera Intolerant or Resistant to Hydroxycarbamide in a Randomized Trial. J Clin Oncol. 2023;41(19):3534-44.Prospective randomized trial of ruxolitinib compared to best available therapy in patients with polycythemia vera after hydroxycarbamide.

Mora B, Giorgino T, Guglielmelli P, Rumi E, Maffioli M, Rambaldi A, et al. Value of cytogenetic abnormalities in post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a study of the MYSEC project. Haematologica. 2018;103(9):e392-94.Description of cytogenetic alterations in a large cohort of secondary myelofibrosis.

Gupta V, Malone AK, Hari PN, Woo Ahn K, Hu ZH, Gale RP, et al. Reduced-intensity hematopoietic cell transplantation for patients with primary myelofibrosis: a cohort analysis from the center for international blood and marrow transplant research. Biol Blood Marrow Transplant. 2014;20(1):89-97.Outcome of reduced-intensity hematopoietic cell transplantation in primary myelofibrosis.

Passamonti F. Stem cell transplant in MF: it's time to personalize. Blood. 2019;133(20):2118-20.Discussion on the indications and guidance on selection of myelofibrosis patients for stem cell transplant.

Gagelmann N, Ditschkowski M, Bogdanov R, Bredin S, Robin M, Cassinat B, et al. Comprehensive clinical-molecular transplant scoring system for myelofibrosis undergoing stem cell transplantation. Blood. 2019;133(20):2233-42.Integrated prognostic score for selection of myelofibrosis patients for stem cell transplant.

Tamari R, McLornan DP, Ahn KW, Estrada-Merly N, Hernández-Boluda JC, Giralt S, et al. A simple prognostic system in patients with myelofibrosis undergoing allogeneic stem cell transplantation: a CIBMTR/EBMT analysis. Blood Adv. 2023;7(15):3993-4002.Semplified prognostic score for selection of myelofibrosis patients for stem cell transplant.

Guglielmelli P, Ghirardi A, Carobbio A, Masciulli A, Maccari C, Mora B, et al. Impact of ruxolitinib on survival of patients with myelofibrosis in the real world: update of the ERNEST Study. Blood Adv. 2022;6(2):373-75.Real world data on survival of myelofibrosis patients treated with ruxolitinib or hydroxycarbamide.

Maffioli M, Mora B, Ball S, Iurlo A, Elli EM, Finazzi MC, et al. A prognostic model to predict survival after 6 months of ruxolitinib in patients with myelofibrosis. Blood Adv. 2022;6(6):1855-64.Prognostic score for evaluating survival after 6 months of ruxolitinib.

Kuykendall AT, Shah S, Talati C, Al Ali N, Sweet K, Padron E, et al. Between a rux and a hard place: evaluating salvage treatment and outcomes in myelofibrosis after ruxolitinib discontinuation. Ann Hematol. 2018;97(3):435-41.Evaluation of incidence and reasons of ruxolitinib discontinuation and its outcome.

Pemmaraju N, Garcia JS, Potluri J, Harb JG, Sun Y, Jung P, et al. Addition of navitoclax to ongoing ruxolitinib treatment in patients with myelofibrosis (REFINE): a post-hoc analysis of molecular biomarkers in a phase 2 study. Lancet Haematol. 2022;9(6):e434–44.Post-hoc analysis of impact of changes in molecular biomarkers on outcome of patients treated with ruxolitinib and navitoclax.

Mascarenhas J, Komrokji RS, Palandri F, Martino B, Niederwueser D, Reiter A, et al. Randomized, single-blind, multicenter phase II study of two doses of Imetelstat in relapsed or refractory myelofibrosis. J Clin Oncol. 2021;39(26):2881–892.Results of imetelstat in relapsed/refractory myelofibrosis patients.

Pemmaraju N, Verstovsek S, Mesa R, Gupta V, Garcia JS, Scandura JM, et al. Defining disease modification in myelofibrosis in the era of targeted therapy. Cancer. 2022;128(13):2420-32.Definition of disease modification in myelofibrosis in the contemporary era.

Acknowledgements

The study has been supported by Ministero della Salute, Rome, Italy, (Finalizzata 2018, NET-2018-12365935, personalized medicine program on myeloid neoplasms: characterization of the patient’s genome for clinical decision making and systematic collection of real world data to improve quality of health care). FP has been supported by by grants from Fondazione Matarelli, Milan, Italy.

Author Contributions

BM and FP contributed to the conception of the work and wrote the manuscript; all Authors contributed to revise the manuscript critically for important intellectual content and approved the final version of the manuscript.

Funding

Open access funding provided by Università degli Studi di Milano within the CRUI-CARE Agreement.

Data Availability

No datasets were generated or analysed during the current study.

Declarations

Competing Interests

The authors do not have existing conflicts. B.M. received honoraria during the last two years for lectures from Novartis. C.B. received honoraria during the last two years from Incyte, Novartis, and Pfizer. A.I. received honoraria during the last two years for lectures from Incyte, Novartis, Bristol-Myers Squibb, GSK, Pfizer, AOP Health and for advisory boards from Incyte, Novartis, Bristol-Myers Squibb, AOP Health. F.P. received honoraria during the last two years for lectures from Novartis, Bristol-Myers Squibb, Abbvie, GSK, Janssen, AOP Orphan and for advisory boards from Novartis, Bristol-Myers Squibb/ Celgene, GSK, Abbvie, AOP Orphan, Janssen, Karyiopharma, Kyowa Kirin and MEI, Sumitomo, Kartos.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. Arber DA Orazi A Hasserjian R Borowitz MJ Calvo KR Kvasnicka HS International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data Blood 2022 140 11 1200 1228 10.1182/blood.2022015850 35767897
Arber DA, Orazi A, Hasserjian R, Borowitz MJ, Calvo KR, Kvasnicka HS, et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data. Blood. 2022;140(11):1200–28.35767897
2. Passamonti F Mora B Myelofibrosis Blood 2023 141 16 1954 1970 10.1182/blood.2022017423 36416738
Passamonti F, Mora B. Myelofibrosis. Blood. 2023;141(16):1954–70.36416738
3. Barosi G Mesa RA Thiele J Cervantes F Campbell PJ Versovsek S Proposed criteria for the diagnosis of post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a consensus statement from the International Working Group for Myelofibrosis Research and Treatment Leukemia 2008 22 2 437 438 10.1038/sj.leu.2404914 17728787
Barosi G, Mesa RA, Thiele J, Cervantes F, Campbell PJ, Versovsek S, et al. Proposed criteria for the diagnosis of post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a consensus statement from the International Working Group for Myelofibrosis Research and Treatment. Leukemia. 2008;22(2):437–8.17728787
4. Passamonti F Rumi E Pungolino E Malabarba L Bertazzoni P Valentini M Life expectancy and prognostic factors for survival in patients with polycythemia vera and essential thrombocythemia Am J Med 2004 117 10 755 761 10.1016/j.amjmed.2004.06.032 15541325
Passamonti F, Rumi E, Pungolino E, Malabarba L, Bertazzoni P, Valentini M, et al. Life expectancy and prognostic factors for survival in patients with polycythemia vera and essential thrombocythemia. Am J Med. 2004;117(10):755–61.15541325
5. Mesa RA Verstovsek S Cervantes F Barosi G Reilly JT Dupriez B International Working Group for Myelofibrosis Research and Treatment (IWG-MRT). Primary myelofibrosis (PMF), post polycythemia vera myelofibrosis (post-PV MF), post essential thrombocythemia myelofibrosis (post-ET MF), blast phase PMF (PMF-BP): consensus on terminology by the international working group for myelofibrosis research and treatment (IWG-MRT) Leuk Res 2007 31 6 737 40 10.1016/j.leukres.2006.12.002 17210175
Mesa RA, Verstovsek S, Cervantes F, Barosi G, Reilly JT, Dupriez B, et al. International Working Group for Myelofibrosis Research and Treatment (IWG-MRT). Primary myelofibrosis (PMF), post polycythemia vera myelofibrosis (post-PV MF), post essential thrombocythemia myelofibrosis (post-ET MF), blast phase PMF (PMF-BP): consensus on terminology by the international working group for myelofibrosis research and treatment (IWG-MRT). Leuk Res. 2007;31(6):737–40.17210175
6. Verstovsek S Yu J Scherber RM Verma S Dieyi C Chen CC Changes in the incidence and overall survival of patients with myeloproliferative neoplasms between 2002 and 2016 in the United States Leuk Lymphoma 2022 63 3 694 702 10.1080/10428194.2021.1992756 34689695
Verstovsek S, Yu J, Scherber RM, Verma S, Dieyi C, Chen CC, et al. Changes in the incidence and overall survival of patients with myeloproliferative neoplasms between 2002 and 2016 in the United States. Leuk Lymphoma. 2022;63(3):694–702.34689695
7. O’Shea JJ Schwartz DM Villarino AV Gadina M McInnes IB Laurence A The JAK-STAT pathway: impact on human disease and therapeutic intervention Annu Rev Med 2015 66 311 28 10.1146/annurev-med-051113-024537 25587654
O’Shea JJ, Schwartz DM, Villarino AV, Gadina M, McInnes IB, Laurence A. The JAK-STAT pathway: impact on human disease and therapeutic intervention. Annu Rev Med. 2015;66:311–28.25587654
8. Passamonti F Mora B Maffioli M New molecular genetics in the diagnosis and treatment of myeloproliferative neoplasms Curr Opin Hematol 2016 23 2 137 143 10.1097/MOH.0000000000000218 26825696
Passamonti F, Mora B, Maffioli M. New molecular genetics in the diagnosis and treatment of myeloproliferative neoplasms. Curr Opin Hematol. 2016;23(2):137–43.26825696
9. Passamonti F Mora B Giorgino T Guglielmelli P Cazzola M Maffioli M Driver mutations' effect in secondary myelofibrosis: an international multicenter study based on 781 patients Leukemia 2017 31 4 970 973 10.1038/leu.2016.351 27885272
Passamonti F, Mora B, Giorgino T, Guglielmelli P, Cazzola M, Maffioli M, et al. Driver mutations’ effect in secondary myelofibrosis: an international multicenter study based on 781 patients. Leukemia. 2017;31(4):970–3.27885272
10. Mora B Siracusa C Rumi E Maffioli M Casetti IC Barraco D Platelet count predicts driver mutations' co-occurrence in low JAK2 mutated essential thrombocythemia and myelofibrosis Leukemia 2021 35 5 1490 1493 10.1038/s41375-020-01053-9 33051550
Mora B, Siracusa C, Rumi E, Maffioli M, Casetti IC, Barraco D, et al. Platelet count predicts driver mutations’ co-occurrence in low JAK2 mutated essential thrombocythemia and myelofibrosis. Leukemia. 2021;35(5):1490–3.33051550
11. Luque Paz D Kralovics R Skoda RC Genetic basis and molecular profiling in myeloproliferative neoplasms Blood 2023 141 16 1909 1921 10.1182/blood.2022017578 36347013
Luque Paz D, Kralovics R, Skoda RC. Genetic basis and molecular profiling in myeloproliferative neoplasms. Blood. 2023;141(16):1909–21.36347013
12. Mora B Guglielmelli P Kuykendall A Maffioli M Rotunno G Komrokji RS Myeloid neoplasms-associated gene mutations in 639 patients with post-polyccythemia vera and post-essential thrombocythemia myelofibrosis: a study of the MYSEC cohort. Abstract from the 2022 Italian Society of Hematology (SIE) Congress HemaSphere 2022 6 885 86 10.1097/01.HS9.0000846848.27311.c7
Mora B, Guglielmelli P, Kuykendall A, Maffioli M, Rotunno G, Komrokji RS, et al. Myeloid neoplasms-associated gene mutations in 639 patients with post-polyccythemia vera and post-essential thrombocythemia myelofibrosis: a study of the MYSEC cohort. Abstract from the 2022 Italian Society of Hematology (SIE) Congress. HemaSphere. 2022;6:885–6.
13. Passamonti F Cervantes F Vannucchi AM Morra E Rumi E Pereira A 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 9 1703 1708 10.1182/blood-2009-09-245837 20008785
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(9):1703–8.20008785
14. Passamonti F Giorgino T Mora B Guglielmelli P Rumi E Maffioli M A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis Leukemia 2017 31 12 2726 2731 10.1038/leu.2017.169 28561069
Passamonti F, Giorgino T, Mora B, Guglielmelli P, Rumi E, Maffioli M, et al. A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis. Leukemia. 2017;31(12):2726–31.28561069
15. Guglielmelli P Pacilli A Rotunno G Rumi E Rosti V Delaini F Presentation and outcome of patients with 2016 WHO diagnosis of prefibrotic and overt primary myelofibrosis Blood 2017 129 24 3227 3236 10.1182/blood-2017-01-761999 28351937
Guglielmelli P, Pacilli A, Rotunno G, Rumi E, Rosti V, Delaini F, et al. Presentation and outcome of patients with 2016 WHO diagnosis of prefibrotic and overt primary myelofibrosis. Blood. 2017;129(24):3227–36.28351937
16. Mora B Rumi E Guglielmelli P Barraco D Maffioli M Rambaldi A Second primary malignancies in postpolycythemia vera and postessential thrombocythemia myelofibrosis: A study on 2233 patients Cancer Med 2019 8 9 4089 4092 10.1002/cam4.2107 31173472
Mora B, Rumi E, Guglielmelli P, Barraco D, Maffioli M, Rambaldi A, et al. Second primary malignancies in postpolycythemia vera and postessential thrombocythemia myelofibrosis: A study on 2233 patients. Cancer Med. 2019;8(9):4089–92.31173472
17. Tefferi A Guglielmelli P Larson DR Finke C Wassie EA Pieri L Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myelofibrosis Blood 2014 124 16 2507 2513 10.1182/blood-2014-05-579136 25037629
Tefferi A, Guglielmelli P, Larson DR, Finke C, Wassie EA, Pieri L, et al. Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myelofibrosis. Blood. 2014;124(16):2507–13.25037629
18. Masarova L Bose P Pemmaraju N Daver NG Sasaki K Chifotides HT Improved survival of patients with myelofibrosis in the last decade: Single-center experience Cancer 2022 128 8 1658 1665 10.1002/cncr.34103 35077575
Masarova L, Bose P, Pemmaraju N, Daver NG, Sasaki K, Chifotides HT, et al. Improved survival of patients with myelofibrosis in the last decade: Single-center experience. Cancer. 2022;128(8):1658–65.35077575
19. Verstovsek S Parasuraman S Yu J Shah A Kumar S Xi A Real-world survival of US patients with intermediate- to high-risk myelofibrosis: impact of ruxolitinib approval Ann Hematol 2022 101 1 131 137 10.1007/s00277-021-04682-x 34625831
Verstovsek S, Parasuraman S, Yu J, Shah A, Kumar S, Xi A, et al. Real-world survival of US patients with intermediate- to high-risk myelofibrosis: impact of ruxolitinib approval. Ann Hematol. 2022;101(1):131–7.34625831
20. Verstovsek S Gotlib J Mesa RA Vannucchi AM Kiladjian JJ Cervantes F Long-term survival in patients treated with ruxolitinib for myelofibrosis: COMFORT-I and -II pooled analyses J Hematol Oncol 2017 10 1 156 10.1186/s13045-017-0527-7 28962635
Verstovsek S, Gotlib J, Mesa RA, Vannucchi AM, Kiladjian JJ, Cervantes F, et al. Long-term survival in patients treated with ruxolitinib for myelofibrosis: COMFORT-I and -II pooled analyses. J Hematol Oncol. 2017;10(1):156.28962635
21. Pardanani A Tefferi A Masszi T Mishchenko E Drummond M Jourdan E Updated results of the placebo-controlled, phase III JAKARTA trial of fedratinib in patients with intermediate-2 or high-risk myelofibrosis Br J Haematol 2021 195 2 244 248 10.1111/bjh.17727 34331348
Pardanani A, Tefferi A, Masszi T, Mishchenko E, Drummond M, Jourdan E, et al. Updated results of the placebo-controlled, phase III JAKARTA trial of fedratinib in patients with intermediate-2 or high-risk myelofibrosis. Br J Haematol. 2021;195(2):244–8.34331348
22. Kunte S Rybicki L Viswabandya A Tamari R Bashey A Keyzner A Allogeneic blood or marrow transplantation with haploidentical donor and post-transplantation cyclophosphamide in patients with myelofibrosis: a multicenter study Leukemia 2022 36 3 856 864 10.1038/s41375-021-01449-1 34663912
Kunte S, Rybicki L, Viswabandya A, Tamari R, Bashey A, Keyzner A, et al. Allogeneic blood or marrow transplantation with haploidentical donor and post-transplantation cyclophosphamide in patients with myelofibrosis: a multicenter study. Leukemia. 2022;36(3):856–64.34663912
23. Kröger N Bacigalupo A Barbui T Ditschkowski M Gagelmann N Griesshammer M Indication and management of allogeneic haematopoietic stem-cell transplantation in myelofibrosis: updated recommendations by the EBMT/ELN International Working Group Lancet Haematol 2024 11 1 e62 74 10.1016/S2352-3026(23)00305-8 38061384
Kröger N, Bacigalupo A, Barbui T, Ditschkowski M, Gagelmann N, Griesshammer M, et al. Indication and management of allogeneic haematopoietic stem-cell transplantation in myelofibrosis: updated recommendations by the EBMT/ELN International Working Group. Lancet Haematol. 2024;11(1):e62-74.38061384
24. Mora B Passamonti F Towards a Personalized Definition of Prognosis in Philadelphia-Negative Myeloproliferative Neoplasms Curr Hematol Malig Rep 2022 17 5 127 139 10.1007/s11899-022-00672-6 36048275
Mora B, Passamonti F. Towards a Personalized Definition of Prognosis in Philadelphia-Negative Myeloproliferative Neoplasms. Curr Hematol Malig Rep. 2022;17(5):127–39.36048275
25. Mora B Maffioli M Rumi E Guglielmelli P Caramella M Kuykendall A Incidence of blast phase in myelofibrosis according to anemia severity EJHaem 2023 4 3 679 689 10.1002/jha2.745 37601878
Mora B, Maffioli M, Rumi E, Guglielmelli P, Caramella M, Kuykendall A, et al. Incidence of blast phase in myelofibrosis according to anemia severity. EJHaem. 2023;4(3):679–89.37601878
26. Cervantes F Dupriez B Pereira A Passamonti F Reilly JT Morra E New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment Blood 2009 113 13 2895 2901 10.1182/blood-2008-07-170449 18988864
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(13):2895–901.18988864
27. Verstovsek S Yu J Kish JK Paranagama D Kaufman J Myerscough C Real-world risk assessment and treatment initiation among patients with myelofibrosis at community oncology practices in the United States Ann Hematol 2020 99 11 2555 2564 10.1007/s00277-020-04055-w 32382773
Verstovsek S, Yu J, Kish JK, Paranagama D, Kaufman J, Myerscough C, et al. Real-world risk assessment and treatment initiation among patients with myelofibrosis at community oncology practices in the United States. Ann Hematol. 2020;99(11):2555–64.32382773
28. Gangat N Caramazza D Vaidya R George G Begna K Schwager S 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 4 392 397 10.1200/JCO.2010.32.2446 21149668
Gangat N, Caramazza D, Vaidya R, George G, Begna K, Schwager S. 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(4):392–7.21149668
29. Caramazza D Begna KH Gangat N Vaidya R Siragusa S Van Dyke DL Refined cytogenetic-risk categorization for overall and leukemia-free survival in primary myelofibrosis: A single center study of 433 patients Leukemia 2011 25 1 82 88 10.1038/leu.2010.234 20944670
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(1):82–8.20944670
30. Bose P Management of Patients with Early Myelofibrosis: A Discussion of Best Practices Curr Hematol Malig Rep 2024 19 3 111 119 10.1007/s11899-024-00729-8 38441783
Bose P. Management of Patients with Early Myelofibrosis: A Discussion of Best Practices. Curr Hematol Malig Rep. 2024;19(3):111–9.38441783
31. Tefferi A Lasho TL Finke CM Knudson RA Ketterling R Hanson CH CALR vs JAK2 vs MPL-mutated or triple-negative myelofibrosis: clinical, cytogenetic and molecular comparisons Leukemia 2014 28 7 1472 1477 10.1038/leu.2014.3 24402162
Tefferi A, Lasho TL, Finke CM, Knudson RA, Ketterling R, Hanson CH, et al. CALR vs JAK2 vs MPL-mutated or triple-negative myelofibrosis: clinical, cytogenetic and molecular comparisons. Leukemia. 2014;28(7):1472–7.24402162
32. Vannucchi AM Lasho TL Guglielmelli P Biamonte F Pardanani A Pereira A Mutations and prognosis in primary myelofibrosis Leukemia 2013 27 9 1861 1869 10.1038/leu.2013.119 23619563
Vannucchi AM, Lasho TL, Guglielmelli P, Biamonte F, Pardanani A, Pereira A, et al. Mutations and prognosis in primary myelofibrosis. Leukemia. 2013;27(9):1861–9.23619563
33. Guglielmelli P Lasho TL Rotunno G Mudireddy M Mannarelli C Nicolosi M MIPSS70: Mutation-Enhanced International Prognostic Score System for Transplantation-Age Patients With Primary Myelofibrosis J Clin Oncol 2018 36 4 310 318 10.1200/JCO.2017.76.4886 29226763
Guglielmelli P, Lasho TL, Rotunno G, Mudireddy M, Mannarelli C, Nicolosi M, et al. MIPSS70: Mutation-Enhanced International Prognostic Score System for Transplantation-Age Patients With Primary Myelofibrosis. J Clin Oncol. 2018;36(4):310–8.29226763
34. Tefferi A Guglielmelli P Lasho TL Gangat N Ketterling RP Pardanani A MIPSS70+ Version 2.0: Mutation and Karyotype-Enhanced International Prognostic Scoring System for Primary Myelofibrosis J Clin Oncol 2018 36 17 1769 70 10.1200/JCO.2018.78.9867 29708808
Tefferi A, Guglielmelli P, Lasho TL, Gangat N, Ketterling RP, Pardanani A, et al. MIPSS70+ Version 2.0: Mutation and Karyotype-Enhanced International Prognostic Scoring System for Primary Myelofibrosis. J Clin Oncol. 2018;36(17):1769–70.29708808
35. Tefferi A Guglielmelli P Nicolosi M Mannelli F Mudireddy M Bartalucci N GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis Leukemia 2018 32 7 1631 1642 10.1038/s41375-018-0107-z 29654267
Tefferi A, Guglielmelli P, Nicolosi M, Mannelli F, Mudireddy M, Bartalucci N, et al. GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis. Leukemia. 2018;32(7):1631–42.29654267
36. Network NCC. Myeloproliferative neoplasms. 2024 [Available from https://www.nccn.org/professionals/physician_gls/pdf/mpn.pdf]. Accessed 1 May 2024.
37. Coltro G Mannelli F Loscocco GG Mannarelli C Rotunno G Maccari C Differential prognostic impact of cytopenic phenotype in prefibrotic vs overt primary myelofibrosis Blood Cancer J 2022 12 8 116 10.1038/s41408-022-00713-6 35961958
Coltro G, Mannelli F, Loscocco GG, Mannarelli C, Rotunno G, Maccari C, et al. Differential prognostic impact of cytopenic phenotype in prefibrotic vs overt primary myelofibrosis. Blood Cancer J. 2022;12(8):116.35961958
38. Mannelli F Bencini S Coltro G Loscocco GG Peruzzi B Rotunno G Integration of multiparameter flow cytometry score improves prognostic stratification provided by standard models in primary myelofibrosis Am J Hematol 2022 97 7 846 855 10.1002/ajh.26548 35338671
Mannelli F, Bencini S, Coltro G, Loscocco GG, Peruzzi B, Rotunno G, et al. Integration of multiparameter flow cytometry score improves prognostic stratification provided by standard models in primary myelofibrosis. Am J Hematol. 2022;97(7):846–55.35338671
39. Bankar A Alibhai S Smith E Yang D Malik S Cheung V Association of frailty with clinical outcomes in myelofibrosis: a retrospective cohort study Br J Haematol 2021 194 3 557 567 10.1111/bjh.17617 34131896
Bankar A, Alibhai S, Smith E, Yang D, Malik S, Cheung V, et al. Association of frailty with clinical outcomes in myelofibrosis: a retrospective cohort study. Br J Haematol. 2021;194(3):557–67.34131896
40. Sochacki AL Bejan CA Zhao S Patel A Kishtagari A Spaulding TP Patient-specific comorbidities as prognostic variables for survival in myelofibrosis Blood Adv 2023 7 5 756 767 10.1182/bloodadvances.2021006318 35420683
Sochacki AL, Bejan CA, Zhao S, Patel A, Kishtagari A, Spaulding TP, et al. Patient-specific comorbidities as prognostic variables for survival in myelofibrosis. Blood Adv. 2023;7(5):756–67.35420683
41. Luque Paz D Riou J Verger E Cassinat B Chauveau A Ianotto JC Genomic analysis of primary and secondary myelofibrosis redefines the prognostic impact of ASXL1 mutations: a FIM study Blood Adv 2021 5 5 1442 1451 10.1182/bloodadvances.2020003444 33666653
Luque Paz D, Riou J, Verger E, Cassinat B, Chauveau A, Ianotto JC, et al. Genomic analysis of primary and secondary myelofibrosis redefines the prognostic impact of ASXL1 mutations: a FIM study. Blood Adv. 2021;5(5):1442–51.33666653
42. Guglielmelli P Coltro G Mannelli F Rotunno G Loscocco GG Mannarelli C ASXL1 mutations are prognostically significant in primary myelofibrosis, but not myelofibrosis following essential thrombocythemia or polycythemia vera Blood Adv 2022 6 9 2927 2931 10.1182/bloodadvances.2021006350 35020812
Guglielmelli P, Coltro G, Mannelli F, Rotunno G, Loscocco GG, Mannarelli C, et al. ASXL1 mutations are prognostically significant in primary myelofibrosis, but not myelofibrosis following essential thrombocythemia or polycythemia vera. Blood Adv. 2022;6(9):2927–31.35020812
43. Hernández-Sánchez A Villaverde-Ramiro Á Arellano-Rodrigo E Garrote M Martín I Mosquera-Orgueira A The prognostic impact of non-driver gene mutations and variant allele frequency in primary myelofibrosis Am J Hematol 2024 99 4 755 758 10.1002/ajh.27203 38291566
Hernández-Sánchez A, Villaverde-Ramiro Á, Arellano-Rodrigo E, Garrote M, Martín I, Mosquera-Orgueira A, et al. The prognostic impact of non-driver gene mutations and variant allele frequency in primary myelofibrosis. Am J Hematol. 2024;99(4):755–8.38291566
44. Coltro G Rotunno G Mannelli L Mannarelli C Fiaccabrino S Romagnoli S RAS/CBL mutations predict resistance to JAK inhibitors in myelofibrosis and are associated with poor prognostic features Blood Adv 2020 4 15 3677 3687 10.1182/bloodadvances.2020002175 32777067
Coltro G, Rotunno G, Mannelli L, Mannarelli C, Fiaccabrino S, Romagnoli S, et al. RAS/CBL mutations predict resistance to JAK inhibitors in myelofibrosis and are associated with poor prognostic features. Blood Adv. 2020;4(15):3677–87.32777067
45. Loscocco GG Rotunno G Mannelli F Coltro G Gesullo F Pancani F The prognostic contribution of CBL, NRAS, KRAS, RUNX1, and TP53 mutations to mutation-enhanced international prognostic score systems (MIPSS70/plus/plus v2.0) for primary myelofibrosis Am J Hematol 2024 99 1 68 78 10.1002/ajh.27136 37846894
Loscocco GG, Rotunno G, Mannelli F, Coltro G, Gesullo F, Pancani F, et al. The prognostic contribution of CBL, NRAS, KRAS, RUNX1, and TP53 mutations to mutation-enhanced international prognostic score systems (MIPSS70/plus/plus v2.0) for primary myelofibrosis. Am J Hematol. 2024;99(1):68–78.37846894
46. Mosquera-Orgueira A Arellano-Rodrigo E Garrote M Martín I Pérez-Encinas M Gómez-Casares MT Integrating AIPSS-MF and molecular predictors: A comparative analysis of prognostic models for myelofibrosis Hemasphere 2024 8 3 e60 10.1002/hem3.60 38510992
Mosquera-Orgueira A, Arellano-Rodrigo E, Garrote M, Martín I, Pérez-Encinas M, Gómez-Casares MT, et al. Integrating AIPSS-MF and molecular predictors: A comparative analysis of prognostic models for myelofibrosis. Hemasphere. 2024;8(3):e60.38510992
47. Vermeersch G, Proost P, Struyf S, Gouwy M, Devos T. CXCL8 and its cognate receptors CXCR1/CXCR2 in primary myelofibrosis. Haematologica. 2024 Feb 29. Online ahead of print. 10.3324/haematol.2023.284921
48. Rontauroli S Castellano S Guglielmelli P Zini R Bianchi E Genovese E Gene expression profile correlates with molecular and clinical features in patients with myelofibrosis Blood Adv 2021 5 5 1452 1462 10.1182/bloodadvances.2020003614 33666652
Rontauroli S, Castellano S, Guglielmelli P, Zini R, Bianchi E, Genovese E, et al. Gene expression profile correlates with molecular and clinical features in patients with myelofibrosis. Blood Adv. 2021;5(5):1452–62.33666652
49. Fantini S Rontauroli S Sartini S Mirabile M Bianchi E Badii F Increased Plasma Levels of lncRNAs LINC01268, GAS5 and MALAT1 Correlate with Negative Prognostic Factors in Myelofibrosis Cancers (Basel) 2021 13 19 4744 10.3390/cancers13194744 34638230
Fantini S, Rontauroli S, Sartini S, Mirabile M, Bianchi E, Badii F, et al. Increased Plasma Levels of lncRNAs LINC01268, GAS5 and MALAT1 Correlate with Negative Prognostic Factors in Myelofibrosis. Cancers (Basel). 2021;13(19):4744.34638230
50. Genovese E Mirabile M Rontauroli S Sartini S Fantini S Tavernari L The Response to Oxidative Damage Correlates with Driver Mutations and Clinical Outcome in Patients with Myelofibrosis Antioxidants (Basel) 2022 11 1 113 10.3390/antiox11010113 35052617
Genovese E, Mirabile M, Rontauroli S, Sartini S, Fantini S, Tavernari L, et al. The Response to Oxidative Damage Correlates with Driver Mutations and Clinical Outcome in Patients with Myelofibrosis. Antioxidants (Basel). 2022;11(1):113.35052617
51. Ferrari A Carobbio A Masciulli A Ghirardi A Finazzi G De Stefano V Clinical outcomes under hydroxyurea treatment in polycythemia vera: a systematic review and meta-analysis Haematologica 2019 104 12 2391 2399 10.3324/haematol.2019.221234 31123026
Ferrari A, Carobbio A, Masciulli A, Ghirardi A, Finazzi G, De Stefano V, et al. Clinical outcomes under hydroxyurea treatment in polycythemia vera: a systematic review and meta-analysis. Haematologica. 2019;104(12):2391–9.31123026
52. Mora B Giorgino T Guglielmelli P Rumi E Maffioli M Rambaldi A Phenotype variability of patients with post polycythemia vera and post essential thrombocythemia myelofibrosis is associated with the time to progression from polycythemia vera and essential thrombocythemia Leuk Res 2018 69 100 102 10.1016/j.leukres.2018.04.012 29734070
Mora B, Giorgino T, Guglielmelli P, Rumi E, Maffioli M, Rambaldi A, et al. Phenotype variability of patients with post polycythemia vera and post essential thrombocythemia myelofibrosis is associated with the time to progression from polycythemia vera and essential thrombocythemia. Leuk Res. 2018;69:100–2.29734070
53. Abu-Zeinah G Krichevsky S Cruz T Hoberman G Jaber D Savage N Interferon-alpha for treating polycythemia vera yields improved myelofibrosis-free and overall survival Leukemia 2021 35 9 2592 2601 10.1038/s41375-021-01183-8 33654206
Abu-Zeinah G, Krichevsky S, Cruz T, Hoberman G, Jaber D, Savage N, et al. Interferon-alpha for treating polycythemia vera yields improved myelofibrosis-free and overall survival. Leukemia. 2021;35(9):2592–601.33654206
54. Beauverd Y, Ianotto J-C, Thaw KH, Sobas M, Sadjadian P, Curto-Garcia N, et al. Impact of Cytoreductive Drugs upon Outcomes in a Contemporary Cohort of Adolescent and Young Adults with Essential Thrombocythemia and Polycythemia Vera. Abstract from the 2023 American Society of Hematology (ASH) Congress. Blood. 2023;142(Supplement 1):748.
55. Harrison CN Nangalia J Boucher R Jackson A Yap C O’Sullivan J Ruxolitinib Versus Best Available Therapy for Polycythemia Vera Intolerant or Resistant to Hydroxycarbamide in a Randomized Trial J Clin Oncol 2023 41 19 3534 3544 10.1200/JCO.22.01935 37126762
Harrison CN, Nangalia J, Boucher R, Jackson A, Yap C, O’Sullivan J, et al. Ruxolitinib Versus Best Available Therapy for Polycythemia Vera Intolerant or Resistant to Hydroxycarbamide in a Randomized Trial. J Clin Oncol. 2023;41(19):3534–44.37126762
56. Guglielmelli P Mora B Gesullo F Mannelli F Loscocco GG Signori L Clinical impact of mutated JAK2 allele burden reduction in polycythemia vera and essential thrombocythemia Am J Hematol. 2024 99 8 1550 59 10.1002/ajh.27400 38841874
Guglielmelli P, Mora B, Gesullo F, Mannelli F, Loscocco GG, Signori L, et al. Clinical impact of mutated JAK2 allele burden reduction in polycythemia vera and essential thrombocythemia. Am J Hematol. 2024;99(8):1550–9.38841874
57. Masarova L Bose P Daver N Pemmaraju N Newberry KJ Manshouri T Patients with post-essential thrombocythemia and post-polycythemia vera differ from patients with primary myelofibrosis Leuk Res 2017 59 110 116 10.1016/j.leukres.2017.06.001 28601551
Masarova L, Bose P, Daver N, Pemmaraju N, Newberry KJ, Manshouri T, et al. Patients with post-essential thrombocythemia and post-polycythemia vera differ from patients with primary myelofibrosis. Leuk Res. 2017;59:110–6.28601551
58. Tefferi A Saeed L Hanson CA Ketterling RP Pardanani A Gangat N Application of current prognostic models for primary myelofibrosis in the setting of post-polycythemia vera or post-essential thrombocythemia myelofibrosis Leukemia 2017 31 12 2851 2852 10.1038/leu.2017.268 28819279
Tefferi A, Saeed L, Hanson CA, Ketterling RP, Pardanani A, Gangat N. Application of current prognostic models for primary myelofibrosis in the setting of post-polycythemia vera or post-essential thrombocythemia myelofibrosis. Leukemia. 2017;31(12):2851–2.28819279
59. Palandri F Palumbo GA Iurlo A Polverelli N Benevolo G Breccia M Differences in presenting features, outcome and prognostic models in patients with primary myelofibrosis and post-polycythemia vera and/or post-essential thrombocythemia myelofibrosis treated with ruxolitinib. New perspective of the MYSEC-PM in a large multicenter study Semin Hematol 2018 55 4 248 255 10.1053/j.seminhematol.2018.05.013 30502854
Palandri F, Palumbo GA, Iurlo A, Polverelli N, Benevolo G, Breccia M, et al. Differences in presenting features, outcome and prognostic models in patients with primary myelofibrosis and post-polycythemia vera and/or post-essential thrombocythemia myelofibrosis treated with ruxolitinib. New perspective of the MYSEC-PM in a large multicenter study. Semin Hematol. 2018;55(4):248–55.30502854
60. Barraco D Mora B Guglielmelli P Rumi E Maffioli M Rambaldi A Gender effect on phenotype and genotype in patients with post-polycythemia vera and post-essential thrombocythemia myelofibrosis: results from the MYSEC project Blood Cancer J 2018 8 10 89 10.1038/s41408-018-0128-x 30291232
Barraco D, Mora B, Guglielmelli P, Rumi E, Maffioli M, Rambaldi A, et al. Gender effect on phenotype and genotype in patients with post-polycythemia vera and post-essential thrombocythemia myelofibrosis: results from the MYSEC project. Blood Cancer J. 2018;8(10):89.30291232
61. Passamonti F Rumi E Pungolino E Malabarba L Bertazzoni P Valentini M Life expectancy and prognostic factors for survival in patients with polycythemia vera and essential thrombocythemia Am J Med 2004 117 10 755 761 10.1016/j.amjmed.2004.06.032 15541325
Passamonti F, Rumi E, Pungolino E, Malabarba L, Bertazzoni P, Valentini M, et al. Life expectancy and prognostic factors for survival in patients with polycythemia vera and essential thrombocythemia. Am J Med. 2004;117(10):755–61.15541325
62. Palandri F Mora B Gangat N Catani L Is there a gender effect in polycythemia vera? Ann Hematol 2021 100 1 11 25 10.1007/s00277-020-04287-w 33006021
Palandri F, Mora B, Gangat N, Catani L. Is there a gender effect in polycythemia vera? Ann Hematol. 2021;100(1):11–25.33006021
63. Mora B Guglielmelli P Rumi E Maffioli M Barraco D Rambaldi A Impact of bone marrow fibrosis grade in post-polycythemia vera and post-essential thrombocythemia myelofibrosis: A study of the MYSEC group Am J Hematol 2020 95 1 E1 E3 10.1002/ajh.25644 31588594
Mora B, Guglielmelli P, Rumi E, Maffioli M, Barraco D, Rambaldi A, et al. Impact of bone marrow fibrosis grade in post-polycythemia vera and post-essential thrombocythemia myelofibrosis: A study of the MYSEC group. Am J Hematol. 2020;95(1):E1–3.31588594
64. Mora B Giorgino T Guglielmelli P Rumi E Maffioli M Rambaldi A Value of cytogenetic abnormalities in post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a study of the MYSEC project Haematologica 2018 103 9 e392 e394 10.3324/haematol.2017.185751 29622658
Mora B, Giorgino T, Guglielmelli P, Rumi E, Maffioli M, Rambaldi A, et al. Value of cytogenetic abnormalities in post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a study of the MYSEC project. Haematologica. 2018;103(9):e392–4.29622658
65. Shide K Takenaka K Kitanaka A Numata A Kameda T Yamauchi T Nationwide prospective survey of secondary myelofibrosis in Japan: superiority of DIPSS-plus to MYSEC-PM as a survival risk model Blood Cancer J 2023 13 1 110 10.1038/s41408-023-00869-9 37463903
Shide K, Takenaka K, Kitanaka A, Numata A, Kameda T, Yamauchi T, et al. Nationwide prospective survey of secondary myelofibrosis in Japan: superiority of DIPSS-plus to MYSEC-PM as a survival risk model. Blood Cancer J. 2023;13(1):110.37463903
66. Rotunno G Pacilli A Artusi V Rumi E Maffioli M Delaini F Epidemiology and clinical relevance of mutations in postpolycythemia vera and postessential thrombocythemia myelofibrosis: A study on 359 patients of the AGIMM group Am J Hematol 2016 91 7 681 686 10.1002/ajh.24377 27037840
Rotunno G, Pacilli A, Artusi V, Rumi E, Maffioli M, Delaini F, et al. Epidemiology and clinical relevance of mutations in postpolycythemia vera and postessential thrombocythemia myelofibrosis: A study on 359 patients of the AGIMM group. Am J Hematol. 2016;91(7):681–6.27037840
67. Guerra M Pasquer H Daltro de Oliveira R Soret-Dulphy J Maslah N Zhao LP Comparative clinical and molecular landscape of primary and secondary myelofibrosis: Superior performance of MIPSS70+ v2.0 over MYSEC-PM Am J Hematol 2024 99 4 741 44 10.1002/ajh.27226 38279562
Guerra M, Pasquer H, Daltro de Oliveira R, Soret-Dulphy J, Maslah N, Zhao LP, et al. Comparative clinical and molecular landscape of primary and secondary myelofibrosis: Superior performance of MIPSS70+ v2.0 over MYSEC-PM. Am J Hematol. 2024;99(4):741–4.38279562
68. Loscocco GG Guglielmelli P Mannelli F Mora B Mannarelli C Rotunno G SF3B1 mutations in primary and secondary myelofibrosis: Clinical, molecular and prognostic correlates Am J Hematol 2022 97 9 E347 E349 10.1002/ajh.26648 35796725
Loscocco GG, Guglielmelli P, Mannelli F, Mora B, Mannarelli C, Rotunno G, et al. SF3B1 mutations in primary and secondary myelofibrosis: Clinical, molecular and prognostic correlates. Am J Hematol. 2022;97(9):E347–9.35796725
69. Passamonti F Corrao G Castellani G Mora B Maggioni G Gale RP The future of research in hematology: Integration of conventional studies with real-world data and artificial intelligence Blood Rev 2022 54 100914 10.1016/j.blre.2021.100914 34996639
Passamonti F, Corrao G, Castellani G, Mora B, Maggioni G, Gale RP, et al. The future of research in hematology: Integration of conventional studies with real-world data and artificial intelligence. Blood Rev. 2022;54:100914.34996639
70. Passamonti F Corrao G Castellani G Mora B Maggioni G Della Porta MG Using real-world evidence in haematology Best Pract Res Clin Haematol 2024 37 1 101536 10.1016/j.beha.2024.101536 38490764
Passamonti F, Corrao G, Castellani G, Mora B, Maggioni G, Della Porta MG, et al. Using real-world evidence in haematology. Best Pract Res Clin Haematol. 2024;37(1):101536.38490764
71. Gupta V Malone AK Hari PN Woo Ahn K Hu ZH Gale RP Reduced-intensity hematopoietic cell transplantation for patients with primary myelofibrosis: a cohort analysis from the center for international blood and marrow transplant research Biol Blood Marrow Transplant 2014 20 1 89 97 10.1016/j.bbmt.2013.10.018 24161923
Gupta V, Malone AK, Hari PN, Woo Ahn K, Hu ZH, Gale RP, et al. Reduced-intensity hematopoietic cell transplantation for patients with primary myelofibrosis: a cohort analysis from the center for international blood and marrow transplant research. Biol Blood Marrow Transplant. 2014;20(1):89–97.24161923
72. Hernández-Boluda J-C Pereira A Kröger N Cornelissen JJ Finke J Beelen D Allogeneic hematopoietic cell transplation in older myelofibrosis patients: A study of the chronic malignancies working party of EBMT and the Spanish Myelofibrosis Registry Am J Hematol 2021 96 10 1186 1194 10.1002/ajh.26279 34152630
Hernández-Boluda J-C, Pereira A, Kröger N, Cornelissen JJ, Finke J, Beelen D, et al. Allogeneic hematopoietic cell transplation in older myelofibrosis patients: A study of the chronic malignancies working party of EBMT and the Spanish Myelofibrosis Registry. Am J Hematol. 2021;96(10):1186–94.34152630
73. Passamonti F Stem cell transplant in MF: it's time to personalize Blood 2019 133 20 2118 2120 10.1182/blood-2019-03-900860 31097535
Passamonti F. Stem cell transplant in MF: it’s time to personalize. Blood. 2019;133(20):2118–20.31097535
74. Gagelmann N Badbaran A Salit RB Schroeder T Gurnari C Pagliuca S Impact of TP53 on outcome of patients with myelofibrosis undergoing hematopoietic stem cell transplantation Blood 2023 141 23 2901 2911 36940410
Gagelmann N, Badbaran A, Salit RB, Schroeder T, Gurnari C, Pagliuca S, et al. Impact of TP53 on outcome of patients with myelofibrosis undergoing hematopoietic stem cell transplantation. Blood. 2023;141(23):2901–11.36940410
75. Gagelmann N Ditschkowski M Bogdanov R Bredin S Robin M Cassinat B Comprehensive clinical-molecular transplant scoring system for myelofibrosis undergoing stem cell transplantation Blood 2019 133 20 2233 2242 10.1182/blood-2018-12-890889 30760453
Gagelmann N, Ditschkowski M, Bogdanov R, Bredin S, Robin M, Cassinat B, et al. Comprehensive clinical-molecular transplant scoring system for myelofibrosis undergoing stem cell transplantation. Blood. 2019;133(20):2233–42.30760453
76. Tamari R McLornan DP Ahn KW Estrada-Merly N Hernández-Boluda JC Giralt S A simple prognostic system in patients with myelofibrosis undergoing allogeneic stem cell transplantation: a CIBMTR/EBMT analysis Blood Adv 2023 7 15 3993 4002 10.1182/bloodadvances.2023009886 37134306
Tamari R, McLornan DP, Ahn KW, Estrada-Merly N, Hernández-Boluda JC, Giralt S, et al. A simple prognostic system in patients with myelofibrosis undergoing allogeneic stem cell transplantation: a CIBMTR/EBMT analysis. Blood Adv. 2023;7(15):3993–4002.37134306
77. Passamonti F Maffioli M Cervantes F Vannucchi AM Morra E Barbui T Impact of ruxolitinib on the natural history of primary myelofibrosis: a comparison of the DIPSS and the COMFORT-2 cohorts Blood 2014 123 12 1833 1835 10.1182/blood-2013-12-544411 24443442
Passamonti F, Maffioli M, Cervantes F, Vannucchi AM, Morra E, Barbui T, et al. Impact of ruxolitinib on the natural history of primary myelofibrosis: a comparison of the DIPSS and the COMFORT-2 cohorts. Blood. 2014;123(12):1833–5.24443442
78. Verstovsek S Mesa RA Gotlib J Levy RS Gupta V DiPersio JF A Double-Blind, Placebo-Controlled Trial of Ruxolitinib for Myelofibrosis N Engl J Med 2012 366 9 799 807 10.1056/NEJMoa1110557 22375971
Verstovsek S, Mesa RA, Gotlib J, Levy RS, Gupta V, DiPersio JF, et al. A Double-Blind, Placebo-Controlled Trial of Ruxolitinib for Myelofibrosis. N Engl J Med. 2012;366(9):799–807.22375971
79. Harrison C Kiladjian J-J Al-Ali HK Gisslinger H Waltzman R Stalbovskaya V JAK Inhibition with Ruxolitinib versus Best Available Therapy for Myelofibrosis N Engl J Med 2012 366 9 799 807 10.1056/NEJMoa1110556 22375971
Harrison C, Kiladjian J-J, Al-Ali HK, Gisslinger H, Waltzman R, Stalbovskaya V, et al. JAK Inhibition with Ruxolitinib versus Best Available Therapy for Myelofibrosis. N Engl J Med. 2012;366(9):799–807.22375971
80. Verstovsek S Kiladjian JJ Vannucchi AM Mesa RA Squier P Hamer-Maansson JE Early intervention in myelofibrosis and impact on outcomes: A pooled analysis of the COMFORT-I and COMFORT-II studies Cancer 2023 129 11 1681 1690 10.1002/cncr.34707 36840971
Verstovsek S, Kiladjian JJ, Vannucchi AM, Mesa RA, Squier P, Hamer-Maansson JE, et al. Early intervention in myelofibrosis and impact on outcomes: A pooled analysis of the COMFORT-I and COMFORT-II studies. Cancer. 2023;129(11):1681–90.36840971
81. Guglielmelli P Ghirardi A Carobbio A Masciulli A Maccari C Mora B Impact of ruxolitinib on survival of patients with myelofibrosis in the real world: update of the ERNEST Study Blood Adv 2022 6 2 373 375 10.1182/bloodadvances.2021006006 34753179
Guglielmelli P, Ghirardi A, Carobbio A, Masciulli A, Maccari C, Mora B, et al. Impact of ruxolitinib on survival of patients with myelofibrosis in the real world: update of the ERNEST Study. Blood Adv. 2022;6(2):373–5.34753179
82. Vannucchi AM Kantarjian HM Kiladjian JJ Gotlib J Cervantes F Mesa RA A pooled analysis of overall survival in COMFORT-I and COMFORT-II, 2 randomized phase III trials of ruxolitinib for the treatment of myelofibrosis Haematologica 2015 100 9 1139 1145 10.3324/haematol.2014.119545 26069290
Vannucchi AM, Kantarjian HM, Kiladjian JJ, Gotlib J, Cervantes F, Mesa RA, et al. A pooled analysis of overall survival in COMFORT-I and COMFORT-II, 2 randomized phase III trials of ruxolitinib for the treatment of myelofibrosis. Haematologica. 2015;100(9):1139–45.26069290
83. Palandri F Palumbo GA Bonifacio M Breccia M Latagliata R Martino B Durability of spleen response affects the outcome of ruxolitinib-treated patients with myelofibrosis: Results from a multicentre study on 284 patients Leuk Res 2018 74 86 88 10.1016/j.leukres.2018.10.001 30321784
Palandri F, Palumbo GA, Bonifacio M, Breccia M, Latagliata R, Martino B, et al. Durability of spleen response affects the outcome of ruxolitinib-treated patients with myelofibrosis: Results from a multicentre study on 284 patients. Leuk Res. 2018;74:86–8.30321784
84. Al-Ali HK Stalbovskaya V Gopalakrishna P Perez-Ronco J Foltz L Impact of ruxolitinib treatment on the hemoglobin dynamics and the negative prognosis of anemia in patients with myelofibrosis Leuk Lymphoma 2016 57 10 2464 2547 10.3109/10428194.2016.1146950 26916563
Al-Ali HK, Stalbovskaya V, Gopalakrishna P, Perez-Ronco J, Foltz L. Impact of ruxolitinib treatment on the hemoglobin dynamics and the negative prognosis of anemia in patients with myelofibrosis. Leuk Lymphoma. 2016;57(10):2464–547.26916563
85. Maffioli M Mora B Ball S Iurlo A Elli EM Finazzi MC A prognostic model to predict survival after 6 months of ruxolitinib in patients with myelofibrosis Blood Adv 2022 6 6 1855 1864 10.1182/bloodadvances.2021006889 35130339
Maffioli M, Mora B, Ball S, Iurlo A, Elli EM, Finazzi MC, et al. A prognostic model to predict survival after 6 months of ruxolitinib in patients with myelofibrosis. Blood Adv. 2022;6(6):1855–64.35130339
86. Palandri F Bartoletti D Iurlo A Bonifacio M Abruzzese E Caocci G Peripheral blasts are associated with responses to ruxolitinib and outcomes in patients with chronic-phase myelofibrosis Cancer 2022 128 13 2449 2454 10.1002/cncr.34216 35363892
Palandri F, Bartoletti D, Iurlo A, Bonifacio M, Abruzzese E, Caocci G, et al. Peripheral blasts are associated with responses to ruxolitinib and outcomes in patients with chronic-phase myelofibrosis. Cancer. 2022;128(13):2449–54.35363892
87. Masarova L Bose P Pemmaraju N Daver N Zhou L Pierce S Clinical Significance of Bone Marrow Blast Percentage in Patients With Myelofibrosis and the Effect of Ruxolitinib Therapy Clin Lymphoma Myeloma Leuk 2021 21 5 318 327 10.1016/j.clml.2020.12.024 33551345
Masarova L, Bose P, Pemmaraju N, Daver N, Zhou L, Pierce S, et al. Clinical Significance of Bone Marrow Blast Percentage in Patients With Myelofibrosis and the Effect of Ruxolitinib Therapy. Clin Lymphoma Myeloma Leuk. 2021;21(5):318–27.33551345
88. Passamonti F Heidel FH Parikh RC Ajmera M Tang D Nadal JA Real-world clinical outcomes of patients with myelofibrosis treated with ruxolitinib: a medical record review Future Oncol 2022 18 18 2217 2231 10.2217/fon-2021-1358 35388710
Passamonti F, Heidel FH, Parikh RC, Ajmera M, Tang D, Nadal JA, et al. Real-world clinical outcomes of patients with myelofibrosis treated with ruxolitinib: a medical record review. Future Oncol. 2022;18(18):2217–31.35388710
89. Patel KP Newberry KJ Luthra R Jabbour E Pierce S Cortes J Correlation of mutation profile and response in patients with myelofibrosis treated with ruxolitinib Blood 2015 126 6 790 797 10.1182/blood-2015-03-633404 26124496
Patel KP, Newberry KJ, Luthra R, Jabbour E, Pierce S, Cortes J, et al. Correlation of mutation profile and response in patients with myelofibrosis treated with ruxolitinib. Blood. 2015;126(6):790–7.26124496
90. Spiegel JY McNamara C Kennedy JA Panzarella T Arruda A Stockley T Impact of genomic alterations on outcomes in myelofibrosis patients undergoing JAK1/2 inhibitor therapy Blood Adv 2017 1 20 1729 1738 10.1182/bloodadvances.2017009530 29296819
Spiegel JY, McNamara C, Kennedy JA, Panzarella T, Arruda A, Stockley T, et al. Impact of genomic alterations on outcomes in myelofibrosis patients undergoing JAK1/2 inhibitor therapy. Blood Adv. 2017;1(20):1729–38.29296819
91. Kuykendall AT Ball S Mora B Mo Q Al Ali N Maffioli M Investigation of Serum Albumin as a Dynamic Treatment-Specific Surrogate for Outcomes in Patients With Myelofibrosis Treated With Ruxolitinib JCO Precis Oncol 2024 8 e2300593 10.1200/PO.23.00593 38484210
Kuykendall AT, Ball S, Mora B, Mo Q, Al Ali N, Maffioli M, et al. Investigation of Serum Albumin as a Dynamic Treatment-Specific Surrogate for Outcomes in Patients With Myelofibrosis Treated With Ruxolitinib. JCO Precis Oncol. 2024Mar;8:e2300593.38484210
92. Palandri F Breccia M Bonifacio M Polverelli N Elli EM Benevolo G Life after ruxolitinib: Reasons for discontinuation, impact of disease phase, and outcomes in 218 patients with myelofibrosis Cancer 2020 126 6 1243 1252 10.1002/cncr.32664 31860137
Palandri F, Breccia M, Bonifacio M, Polverelli N, Elli EM, Benevolo G, et al. Life after ruxolitinib: Reasons for discontinuation, impact of disease phase, and outcomes in 218 patients with myelofibrosis. Cancer. 2020;126(6):1243–52.31860137
93. Kuykendall AT Shah S Talati C Al Ali N Sweet K Padron E Between a rux and a hard place: evaluating salvage treatment and outcomes in myelofibrosis after ruxolitinib discontinuation Ann Hematol 2018 97 3 435 441 10.1007/s00277-017-3194-4 29189896
Kuykendall AT, Shah S, Talati C, Al Ali N, Sweet K, Padron E, et al. Between a rux and a hard place: evaluating salvage treatment and outcomes in myelofibrosis after ruxolitinib discontinuation. Ann Hematol. 2018;97(3):435–41.29189896
94. Harrison C, Kiladjian J-J, Verstovsek S, Vannucchi AM, Mesa R, Reiter A, et al. Overall and progression-free survival in patients treated with fedratinib as first-line myelofibrosis (MF) therapy and after prior ruxolitinib (RUX): results from the JAKARTA and JAKARTA2 trials. Abstract from the 2021 European Hematology Association (EHA) Congress. HemaSphere. 2021;5 Abstract S203. 10.1016/S2152-2650(21)01822-X
95. Mesa R Harrison C Oh ST Gerds AT Gupta V Catalano J Overall survival in the SIMPLIFY-1 and SIMPLIFY-2 phase 3 trials of momelotinib in patients with myelofibrosis Leukemia 2022 36 9 2261 2268 10.1038/s41375-022-01637-7 35869266
Mesa R, Harrison C, Oh ST, Gerds AT, Gupta V, Catalano J, et al. Overall survival in the SIMPLIFY-1 and SIMPLIFY-2 phase 3 trials of momelotinib in patients with myelofibrosis. Leukemia. 2022;36(9):2261–8.35869266
96. Pemmaraju N Garcia JS Potluri J Harb JG Sun Y Jung P Addition of navitoclax to ongoing ruxolitinib treatment in patients with myelofibrosis (REFINE): a post-hoc analysis of molecular biomarkers in a phase 2 study Lancet Haematol 2022 9 6 e434 e444 10.1016/S2352-3026(22)00116-8 35576960
Pemmaraju N, Garcia JS, Potluri J, Harb JG, Sun Y, Jung P, et al. Addition of navitoclax to ongoing ruxolitinib treatment in patients with myelofibrosis (REFINE): a post-hoc analysis of molecular biomarkers in a phase 2 study. Lancet Haematol. 2022;9(6):e434–44.35576960
97. Mascarenhas J Komrokji RS Palandri F Martino B Niederwueser D Reiter A Randomized, single-blind, multicenter phase II study of two doses of Imetelstat in relapsed or refractory myelofibrosis J Clin Oncol 2021 39 26 2881 2892 10.1200/JCO.20.02864 34138638
Mascarenhas J, Komrokji RS, Palandri F, Martino B, Niederwueser D, Reiter A, et al. Randomized, single-blind, multicenter phase II study of two doses of Imetelstat in relapsed or refractory myelofibrosis. J Clin Oncol. 2021;39(26):2881–92.34138638
98. Vachhani P Perkins A Mascarenhas J Al-Ali HK Kiladjian JJ Cerquozzi S Disease-modifying activity of navtemadlin (nvtm) correlated with survival outcomes in janus kinase inhibitor (jaki) relapsed or refractory (r/r) myelofibrosis (mf) patients (pts) HemaSphere 2023 7 S3 pe05521ca 10.1097/01.HS9.0000967768.05521.ca
Vachhani P, Perkins A, Mascarenhas J, Al-Ali HK, Kiladjian JJ, Cerquozzi S, et al. Disease-modifying activity of navtemadlin (nvtm) correlated with survival outcomes in janus kinase inhibitor (jaki) relapsed or refractory (r/r) myelofibrosis (mf) patients (pts). HemaSphere. 2023;7(S3):pe05521ca.
99. Rampal R, Vannucchi AM, Gupta V, Oh ST, Kuykendall A, Mesa R, et al. Pelabresib Plus Ruxolitinib Combination Therapy in JAK Inhibitor–Naïve Patients With Myelofibrosis in the MANIFEST-2 Study: Preliminary Evidence of Bone Marrow Recovery. Abstract from the 2024 European Hematology Association (EHA) Congress. Abstract S220.
100. Pemmaraju N Verstovsek S Mesa R Gupta V Garcia JS Scandura JM Defining disease modification in myelofibrosis in the era of targeted therapy Cancer 2022 128 13 2420 2432 10.1002/cncr.34205 35499819
Pemmaraju N, Verstovsek S, Mesa R, Gupta V, Garcia JS, Scandura JM, et al. Defining disease modification in myelofibrosis in the era of targeted therapy. Cancer. 2022;128(13):2420–32.35499819
101. Oh ST Verstovsek S Gupta V Platzbecker U Devos T Kiladjjian JJ Changes in bone marrow fibrosis during momelotinib or ruxolitinib therapy do not correlate with efficacy outcomes in patients with myelofibrosis EJHaem 2024 5 1 105 116 10.1002/jha2.854 38406514
Oh ST, Verstovsek S, Gupta V, Platzbecker U, Devos T, Kiladjjian JJ, et al. Changes in bone marrow fibrosis during momelotinib or ruxolitinib therapy do not correlate with efficacy outcomes in patients with myelofibrosis. EJHaem. 2024;5(1):105–16.38406514
