April, 22, 2025
Author(s): Claire Harrison, MD, FRCP, FRCPath
Fact checked by: Ashling Wahner ,Courtney Flaherty
Claire Harrison, MD, FRCP, FRCPath, a professor of myeloproliferative neoplasms, a consultant, and a clinical director at Guy’s and St. Thomas’ Hospital, discussed the general treatment algorithm for myelofibrosis management, as well as how certain mutations affect patient prognosis and treatment decision-making.
Myelofibrosis is a heterogeneous myeloproliferative neoplasm with significant variability in clinical presentation and disease trajectory, Harrison began. Accurate diagnosis is the foundational step, necessitating careful review of histopathology, peripheral blood findings, bone marrow morphology, and molecular genetics—even in patients who have been referred from other institutions, she stated. Key diagnostic indicators include the presence of splenomegaly and constitutional symptoms, as well as driver mutations, such as JAK2, CALR, and MPL, which support a diagnosis of myeloproliferative neoplasm, Harrison detailed.
Furthermore, assessment of patient-specific factors is essential to inform therapeutic strategy, she continued. This includes evaluating comorbid conditions that may limit treatment options and determining the dominant clinical manifestations of each patient’s disease, Harrison noted. Patient education plays a critical role in this step, with efforts made by oncologists to ensure patient comprehension of the diagnosis—often explicitly referring to myelofibrosis as a “blood cancer”—and to connect patients with advocacy resources when appropriate, she explained.
Prognostication in myelofibrosis incorporates multiple validated models, with modern tools integrating both clinical and molecular data, Harrison said. Driver mutations aid diagnostic classification; however, the absence of these mutations in triple-negative cases warrants expanded next-generation sequencing to identify alternative pathogenic mutations, according to Harrison. The presence of high molecular risk mutations—including ASXL1, IDH1/2, SRSF2, U2AF1, TP53, RUNX1, and NRAS—portends a poorer prognosis and should influence risk stratification and treatment planning, Harrison concluded.