SOHO State of the Art Updates and Next Questions | Predictive Markers for Ruxolitinib in Myelofibrosis.

Authors

Francesca Palandri, Filippo Branzanti

Published in

Clinical lymphoma, myeloma & leukemia. Jul 24, 2026. Epub Jul 24, 2026.

Abstract

Myelofibrosis (MF) is a biologically heterogeneous myeloproliferative neoplasm characterized by constitutive activation of the JAK-STAT pathway, progressive marrow fibrosis, cytopenias, splenomegaly, and systemic inflammation. Ruxolitinib, a JAK1/JAK2 inhibitor, remains the standard frontline therapy for intermediate- and high-risk MF, providing significant improvements in splenomegaly, constitutional symptoms, and survival. However, responses are highly variable, and a substantial proportion of patients experience suboptimal benefit, early discontinuation, or disease progression, underscoring the need for reliable predictors of treatment outcome. This review summarizes current evidence on clinical, molecular, cytogenetic, and dynamic predictors of ruxolitinib response in MF. Clinical variables, including cytopenic phenotype, peripheral blasts, baseline spleen size, symptom burden, prognostic risk category, timing of treatment initiation, and dose intensity, consistently influence treatment efficacy and durability. Notably, inadequate dose intensity emerges as the most relevant modifiable determinant of response. Molecular profiling further refines risk stratification: high-molecular-risk mutations, increased mutational burden, RAS/CBL pathway alterations, and adverse cytogenetics are associated with inferior outcomes, while driver mutation status alone has limited predictive value. The emergence of dynamic prognostic models such as RR6, iRR6, and STR-PM has enabled the integration of early treatment-related variables, including spleen response, transfusion dependence, and dose intensity, to identify patients at higher risk of treatment failure. These tools represent a shift from static baseline prognostication toward adaptive, response-oriented management. Emerging approaches integrating multi-omics profiling, circulating biomarkers, and artificial intelligence are warranted to further improve individualized decision-making among the expanding JAK inhibitor-based strategies in MF.

PMID:
42586899
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.

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