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White, I.R.* ; Rapsomaniki, E.* ; Emerging Risk Factors Collaboration (Meisinger, C.)

Covariate-adjusted measures of discrimination for survival data.

Biom. J. 57, 592-613 (2015)
Verlagsversion Anhang Anhang DOI
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
MotivationDiscrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data. ObjectiveTo develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). MethodWe define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. ResultsThe proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices. ConclusionsThe proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter C-index ; D-index ; Discrimination; Predictive Ability Measures; Proportional Hazards Model; Risk-prediction; Roc Curve; Prognostic Models; Performance; Regression; Marker; Area; Reclassification
ISSN (print) / ISBN 0323-3847
e-ISSN 1521-4036
Zeitschrift Biometrical Journal
Quellenangaben Band: 57, Heft: 4, Seiten: 592-613 Artikelnummer: , Supplement: ,
Verlag Wiley
Verlagsort Weinheim
Begutachtungsstatus Peer reviewed