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The current study validates the predictive performance of the BLAST and BLAST-Mol risk models in a large two-center international cohort with a total of 1101 patients with newly diagnosed CMML. Chronic myelomonocytic leukemia (CMML) is a myeloid neoplasm with overlapping features between myelodysplastic syndrome (MDS) and myeloproliferative neoplasms (MPN) 1. It has a variable clinical course, complicated by constitutional symptoms, progressive cytopenia or cytosis, and an inherent risk of transformation to acute myeloid leukemia (AML), also known as blast transformation (BT) 2. Several CMML survival risk models 3-5 have been developed over the years with the objective of guiding treatment decisions such as allogeneic stem cell transplant (ASCT) and facilitating patient selection for participation in clinical trials 6. The recently published BLAST clinical and BLAST molecular (BLAST-Mol) risk models incorporate clinical and molecular variables, respectively, for prediction of overall survival (OS), while the BLAST-BT risk model was predictive of BT-free survival (BTFS) 6. Similarly, the contemporary molecular CMML-specific prognostic scoring system (CPSS-mol) utilizes clinical variables including white blood cell count (WBC), bone marrow (BM) blasts, red cell transfusion dependency along with genetic variables like cytogenetics and mutations (ASXL1MUT, NRASMUT, SETBP1MUT, and RUNX1MUT) for stratification of patients into four risk groups with distinct OS and risk of BT 3. In the current study, the Mayo Clinic (USA) CMML cohort used in the aforementioned study was expanded from 457 to 600 patients and merged with an external cohort of 501 patients from the Humanitas Research Hospital (HRH; Italy) in order to validate the BLAST, BLAST-Mol, and BLAST-BT risk models. The retrospective study was conducted under an institutional review board approved minimal risk protocol. CMML diagnosis and sub-categorization were according to the International Consensus Classification 1, which included CMML-1 based on BM/peripheral blood (PB) blasts 65 years (median 29 vs. 40 months; p 65 years (HR 1.6, 95% CI 1.3–2.1; p 0.05 in all instances, Figure S2). The clinical management of CMML remains challenging. BT remains a frequent disease complication and leading cause of death 6, 7. Current drug therapy, typically with hydroxyurea or hypomethylating agents (HMAs), has not been shown to prevent BT or prolong OS 2, 8. ASCT is the only potential curative therapy; however, given its substantial treatment-associated morbidity and mortality, it is not a suitable option for all patients 2. Accurate risk prognostication of patients can guide treatment and ASCT decisions. The current study validates the predictive performance of the BLAST, BLAST-Mol, and BLAST-BT risk models in a large two-center international cohort of patients with CMML. The BLAST and BLAST-Mol model performance was superior to that of the widely utilized CPSS-mol risk stratification 3. Blast count based subclassification (CMML-1 vs. CMML-2) was first proposed in the 3rd edition of the WHO classification 9 and remains prognostically relevant 1, 10, with CMML-2 being associated with an adverse prognosis independent of BLAST-Mol, suggesting subtype-adjusted risk models for CMML-1 may improve clinical utility. Our observations also confirm the unfavorable prognostic impact of rare AML-like mutations (NPM1/FLT3/CEPBA) 11, 12 in CMML, particularly NPM1MUT, which remained independently significant and identifies a subgroup of patients with dismal prognosis warranting early ASCT consideration. In the current study, only 14 cases were informative cases for NPMMUT, but we observed clustering with DNMT3AMUT (71% vs. 29%, p < 0.01), and it was noted to be mutually exclusive of ASXL1MUT (0% vs. 100%, p < 0.01) and RUNX1MUT (0% vs. 100%, p = 0.02). These findings warrant investigation in a larger cohort. Interestingly, we found BLAST-Mol-independent adverse impact of U2AF1MUT, BCORMUT, and TP53MUT, which are already included in the BLAST-Mol molecular risk stratification 6, suggesting their negative impact may be underestimated in the current model. Previously, BCORMUT has been reported to be associated with CMML-2, but prognostic impact remained uncertain 13. Similarly, TP53MUT has been observed to be associated with CMML-2, therapy-related CMML, and HMA resistance 14, 15. TP53MUT, particularly multihit configuration, is associated with dismal OS and leukemia-free survival 14. Finally, our findings are consistent with a previous report from Xicoy et al. 16, who have previously shown the favorable prognosis of the SF3B1MUT in 491 patients with CMML. OS was significantly longer in patients with ring sideroblasts (RS)/SF3B1MUT (6.75 vs. 3.17 years for CMML without RS/ SF3B1MUT, p < 0.001). Similarly, cumulative incidence of BT was lower with CMML with RS/ SF3B1MUT (12% vs. 24%, p < 0.001) 16. Considering the complementary nature of the BLAST clinical and BLAST-Mol risk models, a stepwise approach to their use appears reasonable. Prognostication can begin with the clinically based BLAST model, which is readily applicable in most settings, and be refined by incorporating molecular risk through BLAST-Mol when available. Practically, molecular risk stratification can help identify BLAST low-risk patients who are re-stratified as BLAST-Mol intermediate or high risk and may warrant consideration of earlier ASCT. Conversely, BLAST intermediate-risk patients who are reclassified as low-risk by BLAST-Mol might benefit from the deferral of ASCT. These observations collectively validate the BLAST, BLAST-Mol, and BLAST-BT models and suggest the possibility of further enhancement of the BLAST-Mol model by the incorporation of independent prognostic relevance from additional mutations in the genetic risk stratification. S.F., M.Y., P.F., A.A., C.C., M.N., L.L., A.C., G.M., M.G.D.P., K.K.R., R.H., and A.T. were involved in study design, gathering, and analysis of data. N.G., A.A.M., A.P., M.M.P., and A.T. participated in patient care. S.F. and A.T. wrote the paper. The authors have nothing to report. A.A.M.: Research funding from Nssovartis, BMS, Solu Therapeutics, and Sanofi. N.G.: Advisory board to DISC Medicine and Agios. M.M.P.: Research funding from Kura Oncology, Stemline Therapeutics, Epigenetix, Solu Therapeutics, Polaris, and has served on the advisory board for AstraZeneca and SOBI Pharmaceuticals. The other authors declare no conflicts of interest. By email request to the corresponding author. Figure S1: Supporting Information. Figure S2: Supporting Information. Table S1: Supporting Information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Fathima et al. (Thu,) studied this question.