Dr. Thomas is Professor of Preventive Medicine, Director of the Biostatistics Division, and Verna R. Richter Chair in Cancer Research at the University of Southern California Keck School of Medicine. He received his undergraduate degree from Haverford College, an M.S. in Mathematics from Stanford University, and a Ph.D. in Epidemiology and Biostatistics from McGill University in 1976.

His primary research interest has been in the development of statistical methods for cancer epidemiology, but he also has wide ranging interests in both environmental and genetic epidemiology. His statistical contributions include methods for analysis of nested case-control studies, approaches to modeling exposure-time-response relationships and interaction effects, exposure modeling and measurement error, and the use of Markov chain Monte Carlo (MCMC) methods and Generalized Estimating Equations (GEE) methods in genetics.

On the environmental side, he has been particularly active in radiation carcinogenesis, having collaborated on studies of cancer in residents downwind of the Nevada Test Site, uranium miners, medical irradiation, and the atomic bomb survivors. He was a member of President Clinton’s Advisory Committee on Human Radiation Experiments, as well as the National Academy of Sciences Committee on the Biological Effects of Ionizing Radiation (BEIR V), and radiation advisory committees for numerous other governmental agencies. Other environmental activities include studies of asbestos, malathion spraying in California, electromagnetic fields, and air pollution; he is Co-Director of the Southern California Environmental Research Center.

On the genetic side, Dr. Thomas has numerous publications in the area of statistical genetics and is collaborating on family studies of breast, ovarian, colon, prostate and other cancers, insulin dependent diabetes, systemic lupus erethematosis, and other diseases. He chairs organizing committees for the Genetic Analysis Workshop and the Informatics Consortium for the NCI Cooperative Family Registries for Breast and Colorectal Cancer, and is currently Past President of the International Genetic Epidemiology Society.

These three broad areas of interest make him uniquely qualified to address methodological challenges in studying gene-environment interactions.

CONTACT PUBLICATIONS GRANTS LINKS

CONTACT INFO:

1. Thomas DC, Pitkaniemi J, Langholz B, Tuomilehto-Wolf, E, Tuomilehto J, The DiMe Study Group. Variation in HLA-associated risks of childhood insulin dependent diabetes in the Finnish population: II. Haplotype effects. Genetic Epidemiology 1995; 12: 455-466.
2. Advisory Committee on Human Radiation Experiments. Research ethics and the medical profession: Report of the Advisory Committee on Human Radiation Experiments. Journal of the American Medical Association 1996; 276:403-409.
3. Gauderman WJ, Thomas DC. Analysis of gene-smoking interaction in lung cancer. Genetic Epidemiology 1997: 14: 199-214.
4. Thomas DC, Richardson S, Gauderman J, Pitkaniemi J. A Bayesian approach to multipoint mapping in nuclear families. Genetic Epidemiology 1997; 14:903-908.
5. Petersen G, Parmigianni G, Thomas D. Missense mutations in disease genes: A Bayesian approach to evaluate causality. American Journal of Human Genetics 1998; 62: 1516-1524.
6. Thomas DC. New approaches to the analysis of cohort studies. Epidemiologic Reviews 1998; 14:122-134.
7. Langholz B, Thomas D, Xiang A, Stram DO. Latency analysis in epidemiologic studies of occupational exposures: application to the Colorado plateau uranium miners cohort. American Journal of Industrial Medicine 1999; 35: 246-256.
8. Peters JM, Avol E, Navidi W, London SJ, Gauderman WJ, Lurman F, Linn WE, Margolis H, Rappaport E, Gong H, Thomas DC. A study of twelve southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity. American Journal of Respiratory and Critical Care Medicine 1999; 159: 760-767.
9. Peters JM, Avol E, Gauderman WJ, Linn WE, Navidi W, London SJ, Margolis H, Rappaport E, Vora H, Gong H, Thomas DC. A study of twelve southern California communities with differing levels and types of air pollution. I. Effects on pulmonary function. American Journal of Respiratory and Critical Care Medicine 1999; 159: 768-775.
10. Witte J, Gauderman WJ, Thomas DC. Asymptotic bias and efficiency in case-control studies of candidate genes and gene-environment interactions: Basic family designs. American Journal of Epidemiology1999; 149: 693-705.
11. Stram DO, Langholz B, Huberman M, Thomas DC. Correcting for exposure measurement error in a reanalysis of lung cancer mortality for the Colorado plateau uranium miners cohort. Health Physics 1999; 77: 265-275.
12. Bowman J, Thomas DC, Jiang F, Peters J. Residential magnetic fields predicted from wiring configurations: I. Exposure model. Bioelectromagnetics 1999: 399-413.
13. Thomas DC, Jiang F, Bowman J, Peters J. Residential magnetic fields predicted from wiring configurations: II. Relationships to childhood leukemia. Bioelectromagnetics 1999: 414-420
14. Thomas DC, Qian D, Gauderman WJ, Siegmund K, Morrison JL. A GEE approach to modeling disease concordance within sibships in relation to multiple markers and exposure factors. Genetic Epidemiology 1999, 17 (Suppl 1): S737-S742.
15. Langholz B, Zyogas A, Thomas DC, Faucett C, Huberman M, Goldstein L. Ascertainment bias in rate ratio estimation from case-sibling control studies of variable age-at-onset disease. Biometrics 1999; 55: 1129-1136.
16. Thomas DC. Design of gene characterization studies: an overview. Monogr Natl Cancer Inst 1999: 26: 17-23.
17. Thomas DC. Some contributions of statistics to environmental epidemiology. Journal of the American Statistical Association 2000; 95: 315-319.
18. Zeger SL, Thomas DC, Dominici F, Samet JM, Schwartz J, Dockery DW, Cohen AJ. Exposure measurement error in time-series studies of air pollution. Environmental Health Perspectives 2000: 108: 419-426.
19. Kraft P, Thomas DC. Bias and efficiency in family-matched gene-characterization studies: Conditional, prospective, retrospective, and joint likelihoods. American Journal of Human Genetics 2000; 66:1119-1131.

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