Abstract
PURPOSE: Real-world data from electronic health records and next-generation sequencing are used to study treatment effectiveness in molecularly refined patient populations. Incomplete mortality data can overestimate survival rates in these studies. The National Death Index (NDI) is the gold standard for mortality data in the United States, but limited accessibility and reporting delays hinder timely research. External sources can supplement and improve mortality data capture. We evaluated a composite mortality variable against NDI records in a large real-world cohort of patients with advanced cancer. METHODS: Deidentified clinical and molecular data from patients with advanced solid tumors were linked with third-party mortality and claims data sets using deterministic tokenization. Vital status and death dates were harmonized across sources. Patient identifiers were submitted to NDI; true matches were deidentified and joined for analysis. Performance metrics were calculated using NDI as ground truth. Date agreement was assessed at 0-, ±15-, and ±30-day tolerances. Subgroup analyses and a cumulative case/dynamic control (CC/DC) approach were also performed. RESULTS: Among 17,597 patients, the composite mortality variable demonstrated 82% sensitivity and 95% specificity against NDI. The positive predictive value was 96%, and the negative predictive value was 77%. Exact date agreement was 86%, increasing to 94% within a ±15-day tolerance and 96% within a ±30-day tolerance. Incorporating third-party data substantially improved the sensitivity from 17% to 82%. With the CC/DC approach, the sensitivity was 96% at 6 months, 97% at 12 months, and 98% at 24 months, with specificity above 98% across these time frames. CONCLUSION: The composite mortality variable is a robust and reliable end point for real-world evidence analyses with high accuracy for identified deaths and appropriate censoring of patients lost to follow-up.