Utilization of Next-Generation Sequencing (NGS) in Unexplained Cytopenia: Development and Validation of a Predictive Model to Guide Selective Use of Myeloid NGS

Next-generation sequencing (NGS) has improved diagnostic accuracy for myeloid neoplasms, but its clinical utility in assessing unexplained cytopenias remains uncertain. This study aimed to develop an evidence-based tool to guide the optimal and cost-effective use of NGS testing in patients with unexplained cytopenia. In this retrospective study, 524 patients with unexplained cytopenias were evaluated and divided into a clonal group with detected clonal mutations (CCUS and MDS, n=212) and a non-clonal group without detected clonal mutations (n = 312). Demographic, clinical, laboratory, and bone marrow data were analyzed using regression models to predict NGS-based clonal detection, and the model was validated in an independent cohort of 105 patients. Age > 61.4 years, male sex, mean corpuscular volume > 108.8 fL, absolute neutrophil count < 0.95 × 10 9 /L, and bone marrow hypercellularity were all identified as significant predictors of NGS positivity in this multivariate model. The model achieved a sensitivity of 92.9%, specificity of 41.5%, negative predictive value of 89.6%, and a positive predictive value of 52%. Performance in the validation cohort remained robust, with 90.5% sensitivity and 42.5% specificity, confirming the model's reproducibility. This study presents a predictive model that estimates an individual's risk of harboring detectable clonal mutations, supporting clinical decision-making and helping optimize the use of NGS testing, with the potential to contribute to cost savings.