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 in unexplained cytopenia. In this retrospective study, 524 patients with unexplained cytopenias were evaluated and divided into a clonal group with detected clonal mutations (myelodysplastic syndrome and clonal cytopenia of undetermined significance, n = 212) and a non-clonal group without detected clonal mutations (n = 312). Using logistic regression, demographic, clinical, laboratory, and bone marrow data were analyzed 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 >108.80 fL, absolute neutrophil count <0.95 × 10⁹/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 52.0%. Performance in the validation cohort remained robust, with 90.5% sensitivity and 42.5% specificity, supporting the model's reproducibility. This study presents a predictive model that estimates the risk for detectable clonal mutations, supporting clinical decision making and helping to optimize the use of NGS testing, with the potential to contribute to cost savings.