Derivation of a blood count-based machine learning model to prioritise sequencing for high-risk clonal haematopoiesis: a retrospective cohort study

Summary: Background: Clonal haematopoiesis is a precursor of myeloid neoplasia and common in older adults, Precursor risk stratification is critical to early cancer detection, guiding surveillance and prevention efforts to high-risk populations. Existing clonal haematopoiesis risk scores use molecular features to estimate risk of myeloid neoplasia, but only around 1% of adults with detectable clonal haematopoiesis are at high risk of myeloid neoplasia transformation. Moreover, sequencing based molecular diagnostics are expensive with limited global availability highlighting the need for pre-sequencing strategies which identify populations enriched for individuals with high-risk clonal haematopoiesis.