Journal
BRIEFINGS IN BIOINFORMATICS
Volume 16, Issue 1, Pages 153-168Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbt059
Keywords
molecular markers; survival analysis; time-dependent AUC
Funding
- Deutsche Forschungsgemeinschaft [SCHM 2966/1-1]
- German Federal Ministry of Education and Research (BMBF) [PKB-01GS08, 0315894A]
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Recent developments in molecular biology have led to the massive discovery of new marker candidates for the prediction of patient survival. To evaluate the predictive value of these markers, statistical tools for measuring the performance of survival models are needed. We consider estimators of discrimination measures, which are a popular approach to evaluate survival predictions in biomarker studies. Estimators of discrimination measures are usually based on regularity assumptions such as the proportional hazards assumption. Based on two sets of molecular data and a simulation study, we show that violations of the regularity assumptions may lead to over-optimistic estimates of prediction accuracy and may therefore result in biased conclusions regarding the clinical utility of new biomarkers. In particular, we demonstrate that biased medical decision making is possible even if statistical checks indicate that all regularity assumptions are satisfied.
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