2005
DOI: 10.1198/000313005x70371
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Illustrating the Impact of a Time-Varying Covariate With an Extended Kaplan-Meier Estimator

Abstract: In clinical endpoint trials, the association between a baseline covariate and the risk of an endpoint is often measured by the hazard ratio as calculated by a Cox regression model, and illustrated by Kaplan-Meier curves comparing cohorts defined by levels of the covariate. The Cox regression model is easily extended to the case of time-varying covariates; however, there is no clear approach for similarly extending the standard KaplanMeier estimator. Various ad hoc procedures that have been used in the medical … Show more

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Cited by 202 publications
(213 citation statements)
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“…However, over time, SBP or HR as risk markers may vary and can place patients into different risk groups. Time varying statistical analyses have been used to analyze outcomes by Kaplan-Meier analyses for the shift of patients from one to another risk group, 31 an approach which was used to study the effects of SBP on clinical outcomes in the ONTARGET trial. 32 Herein, we have used multiple readings of HR and SBP for a given patient and averaged values when the number of visits exceeded 2 and determined mean SBP and mean HR over 10.7±2.2 visits.…”
Section: Discussionmentioning
confidence: 99%
“…However, over time, SBP or HR as risk markers may vary and can place patients into different risk groups. Time varying statistical analyses have been used to analyze outcomes by Kaplan-Meier analyses for the shift of patients from one to another risk group, 31 an approach which was used to study the effects of SBP on clinical outcomes in the ONTARGET trial. 32 Herein, we have used multiple readings of HR and SBP for a given patient and averaged values when the number of visits exceeded 2 and determined mean SBP and mean HR over 10.7±2.2 visits.…”
Section: Discussionmentioning
confidence: 99%
“…These factors are adjusted for in multivariable Cox proportional hazards models to estimate HRs and 95% CIs for the baseline and time-varying covariates (18). Extended Kaplan-Meier curves were used to illustrate the effect of time-varying covariates from proportional hazards models (19). The curves describe the survival experience of patients according to their repeated measurements of these biomarkers during the entire study (the values used for the timevarying covariate in the proportional hazards model collapsed into categories according to the median).…”
Section: Methodsmentioning
confidence: 99%
“…To illustrate the results of time-varying covariate analyses, new-onset AF rate over time was plotted as a function of changing in-treatment SBP group using a univariate modified Kaplan-Meier method, implemented in SAS Release 8.2 on the WIN_PRO platform. 33 Additional multivariable Cox analyses were performed in which hazard ratios for new-onset AF were calculated for 5-mm Hg decrements of in-treatment SBP, in which for each cutoff value AF risk was compared between patients with SBP at that level or lower and patients with SBP greater than that level. Adjusted hazard ratios were plotted versus in-treatment SBP.…”
Section: 28mentioning
confidence: 99%