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On the use of biomarkers for environmental health research

Department of Biostatistics, Harvard School of Public Health, and Department of Biostatistical Science, Dana-Farber Cancer Institute, Boston, MA, USA, lryan{at}hsph.harvard.edu

Wenzheng Huang

Millennium Operations, New York, NY, USA

Sally W Thurston

Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA

Karl T Kelsey

Departments of Genetics and Complex Diseases and Environmental Health, Harvard School of Public Health, Boston, MA, USA

John K Wiencke

UCSF Comprehensive Cancer Center, San Francisco, CA, USA

David C Christiani

Departments of Genetics and Complex Diseases and Environmental Health, Harvard School of Public Health, Boston, MA, USA

This article discusses the growing interest in the use of biomarker data in environmental health research and considers some of the challenging statistical issues that arise. We specify a modeling framework that links environmental exposure, biomarkers and outcome, and discuss in conceptual terms how such a formulation could be used to inform dose response modeling for the purpose of quantitative risk assessment. We then analyse some biomarker data from a case-control study designed to elucidate the mechanisms of smoking induced lung cancer. Because of sample size limitations, we use a likelihood-based analysis which subsumes both cohort and case-control designs as special cases. Our analysis allows us to 1) investigate the extent to which the markers explain the pathway from exposure to outcome; 2) quantify the degree to which biomarker data can improve on predicting outcome over and above exposure; and 3) estimate the association among multiple markers.

Statistical Methods in Medical Research, Vol. 13, No. 3, 207-225 (2004)
DOI: 10.1191/0962280204sm364ra


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