ArticleHealth services research2025
Concordance Indices for Risk Scores With Policy Evaluations.
Article in Health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Etiology- and age-specific timing of death by neurologic criteria evaluation and declaration in clinical practice.Critical care (London, England) · 2026Article
- Concordance Indices for Risk Scores With Policy Evaluations.Health services research · 2025Article
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Authors and funding
1 author.
Funding
Abstract
objectiveTo 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
designWe 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
findingsThe 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]).
conclusionsThe 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.
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Registered trials
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