Validation analysis of a composite real-world mortality endpoint for patients with cancer in the United States.

Objective: We expanded the previous assessment of a mortality variable suited for real-world evidence-focused oncology research.

Data Source: We used a nationwide electronic health record (EHR)-derived de-identified database.

Data Collection: We included patients with at least 1 of 18 cancer types between January 1, 2011 and December 31, 2017. Patient-level structured data (EHRs, obituaries, and Social Security Death Index) and unstructured EHR data (abstracted) were linked to generate a composite mortality variable.

Study Design: We benchmarked sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and ±15-day agreement against the National Death Index (NDI). Real-world overall survival (rwOS) was estimated using the Kaplan-Meier method. We performed sensitivity analyses using a smaller patient cohort that underwent next-generation sequencing testing.

Principal Findings: Compared with the NDI across 18 cancer types (overall N = 160 436): sensitivity, 83.9%-91.5% (17/18 cancer types had sensitivity ≥85.0%); specificity, 93.5%-99.7%; PPV, 96.3%-98.3%; NPV, 75.0%-98.7%; ±15-day agreement, 95.6%-97.6%; and median rwOS estimates ranging from 2.8% to 12.7% greater. Sensitivity analysis results (n = 17 540) were consistent with the main analysis.

Conclusions: Across all cancer types analyzed, this composite mortality variable showed high sensitivity, specificity, PPV, NPV, and ±15-day agreement, and yielded median rwOS values modestly overestimated when compared to NDI-based results.