Testing the proportional hazards assumption in case-cohort analysis

BMC Medical Research Methodology

Howard D Strickler²  Herbert Yu³  Dominic Cirillo¹  Gloria YF Ho²  Sylvia Wassertheil-Smoller²  Thomas E Rohan²  Marc Gunter⁴  Xianhong Xie²  Xiaonan Xue² 

[1] Department of Internal Medicine, University of Iowa Health Care, Iowa, USA;Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, New York, USA;Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA;Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, United Kingdom

关键词: Cox models;    Case-cohort studies;    Schoenfeld residuals;    Proportional hazards;   

Others  :  1092329
DOI  :  10.1186/1471-2288-13-88

 received in 2013-04-19, accepted in 2013-07-05,  发布年份 2013

【 摘 要 】

Background

Case-cohort studies have become common in epidemiological studies of rare disease, with Cox regression models the principal method used in their analysis. However, no appropriate procedures to assess the assumption of proportional hazards of case-cohort Cox models have been proposed.

Methods

We extended the correlation test based on Schoenfeld residuals, an approach used to evaluate the proportionality of hazards in standard Cox models. Specifically, pseudolikelihood functions were used to define “case-cohort Schoenfeld residuals”, and then the correlation of these residuals with each of three functions of event time (i.e., the event time itself, rank order, Kaplan-Meier estimates) was determined. The performances of the proposed tests were examined using simulation studies. We then applied these methods to data from a previously published case-cohort investigation of the insulin/IGF-axis and colorectal cancer.

Results

Simulation studies showed that each of the three correlation tests accurately detected non-proportionality. Application of the proposed tests to the example case-cohort investigation dataset showed that the Cox proportional hazards assumption was not satisfied for certain exposure variables in that study, an issue we addressed through use of available, alternative analytical approaches.

Conclusions

The proposed correlation tests provide a simple and accurate approach for testing the proportional hazards assumption of Cox models in case-cohort analysis. Evaluation of the proportional hazards assumption is essential since its violation raises questions regarding the validity of Cox model results which, if unrecognized, could result in the publication of erroneous scientific findings.

【 授权许可】

   
2013 Xue et al.; licensee BioMed Central Ltd.

【 图 表 】

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