Новая молекулярная модель повышает точность прогноза выживаемости при вторичной миелофиброзе

A new prognostic model that incorporates molecular signatures effectively predicts survival outcomes among patients with secondary myelofibrosis (SMF), according to research published in Blood. The model — which builds on the currently used myelofibrosis secondary to polycythemia vera (PV) and essential thrombocythemia (ET) prognostic model (MYSEC-PM) — stratifies patients by whether they are positive for variants including a combination variant and ASXL1. Defined by the study authors as the MYSEC-molecular prognostic model (MYSEC-mPM), the new model outperforms the MYSEC-PM for prognostic stratification. Driver mutations such as JAK2 are known to play a role in MF etiology and development, but there is a lack of knowledge surrounding other cancer gene variants playing a role, and none are used in the widely adopted in the MYSEC-PM. For this study, researchers evaluated for prognostically relevant cancer gene variants in an effort to improve the predictive power of stratification models in a cohort of patients with SMF. The researchers used next-generation sequencing to evaluate cancer gene variant status and karyotype in 644 patients with SMF. In the overall cohort, 330 patients had had prior ET, 314 patients had had prior PV, the median age at SMF development was 64 years, 48.7% of patients were female sex, and 76.6% of patients had JAK2-mutated disease. Analysis showed that 66.6% of patients had at least 1 cancer gene variant; of these, ASXL1, TET2, and DNMT3A were the most frequently found. Notably, however, the presence of U2AF1, TP53, or SRSF2 (UTS), which was noted in 9.3% of patients, was linked with inferior survival outcomes (median overall survival, 4.1 years). Moreover, an ASXL1 mutation without UTS, which was found in 25.3% of patients, was linked with a median overall survival of 8.4 years. In conclusion, our study shows that genomic profiling could refine current risk stratification tools, allowing for enhanced clinical decision-making in SMF. Building on the MYSEC-PM to create the MYSEC-mPM, which includes the presence of UTS mutations or an ASXL1 mutation without UTS, the researchers allocated 582 patients with SMF into 1 of 4 categories: low-, intermediate-1-, intermediate-2-, and high-risk categories based on MYSEC-mPM score. The score better predicted outcomes than did the currently used MYSEC-PM. The authors further noted that a third model incorporating karyotype may be clinically relevant. “In conclusion, our study shows that genomic profiling could refine current risk stratification tools, allowing for enhanced clinical decision-making in SMF,” the study authors wrote in their report. Disclosures: This research was supported by the Ministero della Salute, Rome, Italy. Please see the original reference for a full list of disclosures. This article originally appeared on Hematology Advisor