Many cancer-risk factor associations are known to be modified by aspects of time, including age at first exposure or age at risk, time since first exposure or since exposure ceased, duration of exposure, and calendar time. In addition, many exposures vary in intensity over time, raising the possibility that the pattern of exposure (ex.: whether intermittent or continuous, whether increasing or decreasing, etc.) might also modify cancer risks. All these aspects bear on the choice of a suitable index of exposure and risk model for epidemiologic analysis. Furthermore in some cases, time itself may be the object of inquiry, as in descriptions of the latent period and whether it is affected by the intensity of exposure. Despite considerable evidence of the importance of such time-related factors in cancer epidemiology, relatively little is known about appropriate methods of analysis and most published reports either ignore them or use rather simplistic models. To address these issues, a Symposium on Time-Related Factors in Cancer Epidemiology was recenty held and this proposal represents an outgrowth of ideas discussed there. As methodological contributions, we propose (1) to develop methods of constructing exposure indices for long-term exposure histories based on models of carcinogenesis and to study their performance using simulation; (2) to develop alternatives to the proportional hazards model, such as those in which exposure and time effects combine additively; (3) to develop simple methods for describing the evolution of risk over time and to explore their use in examining the fit of parametric models; and (4) to study the implications of time-related factors for the design of case-control studies. We will also apply the methods we have developed to a number of epidemiologic studies of cancer available to us, evaluating such factors as occupational exposures, hormonal and reproductive events, medical treatments, and lifestyle (smoking, sunlight, etc.).

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
3R01CA042949-01S1
Application #
3184707
Study Section
(SSS)
Project Start
1986-07-01
Project End
1989-11-30
Budget Start
1986-07-01
Budget End
1987-11-30
Support Year
1
Fiscal Year
1987
Total Cost
Indirect Cost
Name
University of Southern California
Department
Type
Schools of Medicine
DUNS #
041544081
City
Los Angeles
State
CA
Country
United States
Zip Code
90033
Rakovski, Cyril; Langholz, Bryan (2015) A post-hoc Unweighted Analysis of Counter-Matched Case-Control Data. Int J Biostat 11:223-32
Figueiredo, Jane C; Haile, Robert W; Bernstein, Leslie et al. (2010) Oral contraceptives and postmenopausal hormones and risk of contralateral breast cancer among BRCA1 and BRCA2 mutation carriers and noncarriers: the WECARE Study. Breast Cancer Res Treat 120:175-83
Gebregziabher, Mulugeta; Langholz, Bryan (2010) A semiparametric missing-data-induced intensity method for missing covariate data in individually matched case-control studies. Biometrics 66:845-54
Langholz, Bryan; Richardson, David (2009) Are nested case-control studies biased? Epidemiology 20:321-9
Langholz, Bryan; Thomas, Duncan C; Stovall, Marilyn et al. (2009) Statistical methods for analysis of radiation effects with tumor and dose location-specific information with application to the WECARE study of asynchronous contralateral breast cancer. Biometrics 65:599-608
Stovall, Marilyn; Smith, Susan A; Langholz, Bryan M et al. (2008) Dose to the contralateral breast from radiotherapy and risk of second primary breast cancer in the WECARE study. Int J Radiat Oncol Biol Phys 72:1021-30
Figueiredo, Jane C; Bernstein, Leslie; Capanu, Marinela et al. (2008) Oral contraceptives, postmenopausal hormones, and risk of asynchronous bilateral breast cancer: the WECARE Study Group. J Clin Oncol 26:1411-8
Berhane, Kiros; Hauptmann, Michael; Langholz, Bryan (2008) Using tensor product splines in modeling exposure-time-response relationships: application to the Colorado Plateau Uranium Miners cohort. Stat Med 27:5484-96
Bernstein, Jonine L; Langholz, Bryan; Haile, Robert W et al. (2004) Study design: evaluating gene-environment interactions in the etiology of breast cancer - the WECARE study. Breast Cancer Res 6:R199-214
Faucett, C L; Thomas, D C (1996) Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach. Stat Med 15:1663-85

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