Research article summary (published 28 Aug 2009):

The estimation of average hazard ratios by weighted Cox regression.

Full Abstract

Often the effect of at least one of the prognostic factors in a Cox regression model changes over time, which violates the proportional hazards assumption of this model. As a consequence, the average hazard ratio for such a prognostic factor is under- or overestimated. While there are several methods to appropriately cope with non-proportional hazards, in particular by including parameters for time-dependent effects, weighted estimation in Cox regression is a parsimonious alternative without additional parameters. The methodology, which extends the weighted k-sample logrank tests of the Tarone-Ware scheme to models with multiple, binary and continuous covariates, has been introduced in the nineties of the last century and is further developed and re-evaluated in this contribution. The notion of an average hazard ratio is defined and its connection to the effect size measure P(X

Author information

Author/s: Schemper, Michael (M); Wakounig, Samo (S); Heinze, Georg (G);

Affiliation: Section of Clinical Biometrics, Department for Medical Statistics and Informatics, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria. michael.schemper(-atsign-)meduniwien.ac.at

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Statistics in medicine (Stat Med), published in England. (Language: eng)

Reference: 2009-Aug; vol 28 (issue 19) : pp 2473-89

Dates: Created 2009/07/14; Completed 2009/10/01;

PMID: 19472308, status: MEDLINE (last retrieval date: 10/1/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Biometry Humans Kaplan-Meiers Estimate Lung Neoplasms - mortality; therapy

Monte Carlo Method Prognosis Proportional Hazards Models Survival Analysis

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