Journal article
Covariate-adjusted measures of discrimination for survival data
Biometrical journal, Vol.57(4), pp.592-613
07/2015
DOI: 10.1002/bimj.201400061
PMCID: PMC4666552
PMID: 25530064
Abstract
Discrimination 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.
To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s).
We 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.
The 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.
The proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.
Details
- Title: Subtitle
- Covariate-adjusted measures of discrimination for survival data
- Creators
- Ian R White - MRC Biostatistics UnitEleni Rapsomaniki - Farr InstituteEmerging Risk Factors Collaboration
- Contributors
- R B Wallace (Contributor) - University of Iowa, Internal Medicine
- Resource Type
- Journal article
- Publication Details
- Biometrical journal, Vol.57(4), pp.592-613
- DOI
- 10.1002/bimj.201400061
- PMID
- 25530064
- PMCID
- PMC4666552
- NLM abbreviation
- Biom J
- ISSN
- 0323-3847
- eISSN
- 1521-4036
- Grant note
- G19/35 / Medical Research Council MC_UU_12013/5 / Medical Research Council G0700463 / Medical Research Council UL1 TR001450 / NCATS NIH HHS RG/13/13/30194 / British Heart Foundation G0902037 / Medical Research Council G8802774 / Medical Research Council UL1 TR000062 / NCATS NIH HHS MR/L003120/1 / Medical Research Council MR/K013351/1 / Medical Research Council G0100222 / Medical Research Council G1000616 / Medical Research Council RG/08/014/24067 / British Heart Foundation RG/07/008/23674 / British Heart Foundation
- Language
- English
- Date published
- 07/2015
- Academic Unit
- Epidemiology; Injury Prevention Research Center; Internal Medicine
- Record Identifier
- 9984364449702771
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