Measures to assess the prognostic ability of the stratified Cox proportional hazards model

被引:31
|
作者
Danesh, J.
Di Angelantonio, E.
Kaptoge, S.
Lewington, S.
Lowe, G. D. O.
Sarwar, N.
Thompson, S. G.
Walker, M.
White, I. R.
Wood, A. M.
机构
[1] Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, Worts Causeway
[2] Copenhagen City Heart Study, Copenhagen
[3] Edinburgh Artery Study, Edinburgh Claudication Study, Edinburgh
[4] Honolulu Heart Program, Honolulu, HI
基金
英国医学研究理事会;
关键词
prediction; stratified survival analysis; explained variation; discrimination; concordance; BREAST-CANCER RISK; EXPLAINED VARIATION; PREDICTIVE ACCURACY; CARDIOVASCULAR RISK; REGRESSION-MODELS; DISCRIMINATION; VALIDATION; SIZE;
D O I
10.1002/sim.3378
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Many measures have been proposed to Summarize the prognostic ability of the Cox proportional hazards (CPH) survival model. although none is universally accepted for general use. By contrast, little work has been done to summarize the prognostic ability of the stratified CPH model; such measures would be useful in analyses of individual participant data froth multiple studies, data from multi-centre Studies, and in Single study analysis where stratification is used to avoid making assumptions of proportional hazards. We have chosen three measures developed for the unstratified CPH model (Schemper and Henderson's (sic)), Harrell's C-index and Royston and Satterbrei's (sic)), adapted them for use with the stratified CPH model and demonstrated how their values can be represented over time. Although each of these measures is promising in principle, we found the measure of explained variation (sic) very difficult to apply when data arc combined froth several studies with differing durations of participant follow-up. The two other measures considered, (sic) and the C-index, were more applicable under such circumstances. We illustrate the methods using individual participant data from several prospective epidemiological studies of chronic disease outcomes. Copyright (C) 2008 John Wiley & Sons, Ltd.
引用
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页码:389 / 411
页数:23
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