Concordance Indices for Risk Scores With Policy Evaluations
比较了不同一致性指数方法在卫生服务风险评分评估中的差异，通过肝移植患者数据说明在政策相关删失下需正确加权以避免偏差。
OBJECTIVE: To demonstrate the differences between concordance index (C-index) methodologies and clarify the appropriate usage for risk score evaluations in health services applications. STUDY SETTING AND DESIGN: We performed a methodological comparison of C-index metrics and illustrated the consequences of these differences through a study of liver failure patients. DATA SOURCES AND ANALYTIC SAMPLE: We analyzed secondary adult liver transplant registry data from the Organ Procurement and Transplantation Network (OPTN), including all waitlist registrations from 2002 to 2022. PRINCIPAL FINDINGS: The recommended concordance metric based on Gerds' weighting was higher for the original model for end-stage liver disease (MELD) than Harrell's C-Index, Uno's C-Index, and naïve binary outcome metrics (0.864 [95% confidence interval (CI): 0.840, 0.888] versus 0.854 [95% CI: 0.844, 0.864], 0.832 [95% CI: 0.819, 0.844], and 0.727 [95% CI: 0.715, 0.740]), and it did not increase after the latest MELD formula update (0.874 [95% CI: 0.859, 0.889] to 0.869 [95% CI: 0.853, 0.885]). CONCLUSIONS: The concordance indices that are often used in health services applications have important deficiencies under policy-related dependent censoring, and researchers must apply appropriate weighting schemes to avoid bias. The findings uncover new interpretations of past evaluation results that have shaped national liver transplant policies.