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Biostatistics Advance Access originally published online on February 14, 2006
Biostatistics 2006 7(4):515-529; doi:10.1093/biostatistics/kxj023
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© The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Attributable risk function in the proportional hazards model for censored time-to-event

Ying Qing Chen*

Program in Biostatistics, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA yqchen{at}scharp.org

Chengcheng Hu

Department of Biostatistics, Harvard University, Boston, MA 02115, USA

Yan Wang

Division of Biostatistics, School of Public Health, University of California, Berkeley, CA 94720, USA

* To whom correspondence should be addressed.

Time-to-event endpoints are often used in clinical and epidemiological studies to evaluate disease association with hazardous exposures. In the statistical literature of time-to-event analysis, such association is usually measured by the hazard ratio in the proportional hazards model. In public health, it is also of important interest to assess the excess risk attributable to an exposure in a given population. In this article, we extend the notion of ‘population attributable fraction’ for the binary outcomes to the attributable risk function for the event times in prospective studies. A simple estimator of the time-varying attributable risk function is proposed under the proportional hazards model. Its inference procedures are established. Monte-Carlo simulation studies are conducted to evaluate its validity and performance. The proposed methodology is motivated and demonstrated by the data collected in a multicenter acquired immunodeficiency syndrome (AIDS) cohort study to estimate the attributable risk of human immunodeficiency virus type 1 (HIV-1) infections due to several potential risk factors.

Keywords: Attributable fraction; Epidemiologic methods; HIV/AIDS prevention; Population etiologic fraction; Risk assessment


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