Calibrating parametric subject-specific risk estimation

• Published in: Biometrika Vol. 97; no. 2; pp. 389 - 404
• Main Authors: CAI, T., TIAN, L., UNO, HAJIME, SOLOMON, SCOTT D., WEI, L. J.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.06.2010; Biometrika Trust, University College London; Oxford University Press for Biometrika Trust; Oxford Publishing Limited (England)
• Series: Biometrika
• Subjects: Applications; Biology, psychology, social sciences; Cardiovascular diseases; Confidence interval; Consistent estimators; Cox model; Datasets; Estimating techniques; Estimators; Evidence-based medicine; Exact sciences and technology; General topics; Heart attacks; Interval estimators; Mathematics; Medical sciences; Modeling; Mortality; Myocardial infarction; Nonparametric functional estimation; Parameter estimation; Parametric inference; Parametric models; Point estimators; Probability and statistics; Risk assessment; Risk index; ROC analysis; Sciences and techniques of general use; Statistics; Studies; Survival analysis; Biometrics; Myocardial infarction; Parameter estimation; Conditional distribution; Non parametric estimation; Cardiovascular disease; Nonparametric functional estimation; Parametric model; Parametric method; Prevention; Medical science; Clinical trial; Mortality; ROC analysis; Statistical estimation; Parametric estimation; Risk index; Functional; Medicine; Statistical method; Survival analysis; Risk estimation; Cox model; Point estimation; Receiver operating characteristic curves; Cardiovascular diseases
• ISSN: 0006-3444; 1464-3510; 1464-3510
• DOI: 10.1093/biomet/asq012

For modern evidence-based medicine, decisions on disease prevention or management strategies are often guided by a risk index system. For each individual, the system uses his/her baseline information to estimate the risk of experiencing a future disease-related clinical event. Such a risk scoring scheme is usually derived from an overly simplified parametric model. To validate a model-based procedure, one may perform a standard global evaluation via, for instance, a receiver operating characteristic analysis. In this article, we propose a method to calibrate the risk index system at a subject level. Specifically, we developed point and interval estimation procedures for t-year mortality rates conditional on the estimated parametric risk score. The proposals are illustrated with a dataset from a large clinical trial with post-myocardial infarction patients.