Multimodal and Data-Driven Assessment of Myeloid Neoplasms Refines Classification across Disease States

The World Health Organization fifth edition and International Consensus Classification for myeloid neoplasms both incorporate empirical numerical thresholds to morphologic and molecular features defining certain disease entities. However, the clinical implications of these thresholds remain unclear. We analyzed a large cohort (N = 6,976) of patients with myeloid neoplasms to evaluate the impact of proposed yet different numerical thresholds for variant allele frequency of genetic mutations or hematologic parameters set forth by the World Health Organization fifth edition and International Consensus Classification for classification of SF3B1-mutated myelodysplastic neoplasms, NPM1-mutated acute myeloid leukemia (AML), and oligomonocytic chronic myelomonocytic leukemia. Our analysis demonstrated that the clonal burden of SF3B1 mutation in myelodysplastic neoplasms informs classification and prognosis. Our findings support the notion that NPM1 mutation should be AML-defining regardless of blast percentage and highlight the adverse prognostic impact of the cumulative number of myelodysplasia-related mutations in NPM1-mutated AML. Finally, we provide evidence that integrating specific molecular signatures could improve the accuracy of oligomonocytic chronic myelomonocytic leukemia classification.

Using comprehensive clinical and molecular profiling, this study provides a data-driven approach for evaluating numerical thresholds of variant allele frequency or hematologic parameters (i.e., blast percentage and absolute monocyte count) included in current classification schemas across a spectrum of myeloid malignancies, enabling refinement of disease classification and prognostication.