Search Summary Score: A Global Measure to Predict Matched Unrelated Stem Cell Donor Availability

Finding a suitably HLA-matched unrelated donor (URD) is essential for successful hematopoietic stem cell transplant (HSCT). Existing search productivity measures do not - or only partially - address real-world donor availability which can greatly affect a patient's transplant timeline.

This study aims to improve upon existing scores to provide a more accurate assessment of unrelated donor search productivity.

Search Summary Score (SSS) is a novel metric that integrates NMDP HapLogic^SM HLA match probabilities with individual Donor Readiness Scores (DRS), a machine-learning based estimate of donor availability. SSS provides a probabilistic, patient-specific summary of expected search outcomes across multiple match levels.

SSS was validated using 18 222 URD searches from 2021 to 2024, achieving superior predictive accuracy compared to NMDP Search Prognosis and 8/8 URD Search Prognosis (v1.0 and v2.0). For predicting 8/8 matches, SSS demonstrated an AUC of 0.962 and F1 score of 0.96. SSS utility is illustrated in examples of distinguishing clinically meaningful scenarios within the same Search Prognosis category.

SSS offers an interpretable, scalable, and globally applicable tool to assess matched donor availability at the initiation of search. By integrating both HLA compatibility and real-world donor readiness, SSS enhances clinical decision-making, promotes equity in donor access, and supports earlier planning for efficient selection of alternative graft sources.