The long-range aims of our research relate to the analysis of exposure- time-response relationships in epidemiologic studies, particularly those involving extended and time-varying exposure histories. Much of our work has also addressed the efficient design of sampling plans for nested case-control and case-cohort analyses of cohort studies. In this second continuation proposal, we are asking support to continue our work in this general area, with some changes in direction. Methods of exposure-time-response modeling: We plan to develop methods for describing exposure-response relationships for extended time- dependent exposure histories, taking into account the modifying effect of time-related variables such as age at exposure and latency. We will develop methods for fitting simple empirical models and stochastic models of carcinogenesis and pharmacodynamics, to epidemiologic data and for testing the goodness of fit. Alternative methods will be compared using computer simulation and applied to various data sets. Specific models would include the Armitage-Doll multistage and Moolgavkar-Knudson two- stage models, extensions of them for radiation carcinogenesis, and addition of simple kinetic models for tissue dose. We will explore the adequacy of certain approximations that are commonly used and compare the results with exact solutions, where available. Investigation of alternative approaches to the design and analysis of nested case-control and case-cohort studies: We propose to extend stratified and two-stage designs previously developed for unmatched case- control studies to matched designs. In the unmatched situation, it has been shown that great efficiency gains can be expected when assessing confounding and/or interactions. We will extend our previous work on nested case-control and case-cohort sampling to allow for stratified sampling. The basic idea in all of these designs is to improve the efficiency of the design by exploiting information on entry/exit times and covariates that is already available on the full cohort in selecting controls. The methods developed above will be illustrated by application to a number of data sets available to us. We are coinvestigators on a wide range of epidemiologic studies of cancer. A major substantive interest of the principal investigator is in the area of radiation carcinogenesis, and the above problems have arisen in a number of these studies, including the atomic bomb survivors, uranium miners, second cancers in radiotherapy patients, electromagnetic fields, and fallout from the Nevada Test Site. In addition, we plan to reanalyze data on lung cancer from several cohort and animal studies of smoking.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA042949-09
Application #
2091026
Study Section
Epidemiology and Disease Control Subcommittee 2 (EDC)
Project Start
1986-07-01
Project End
1996-06-30
Budget Start
1995-07-13
Budget End
1996-06-30
Support Year
9
Fiscal Year
1995
Total Cost
Indirect Cost
Name
University of Southern California
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
041544081
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
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; 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
Langholz, Bryan; Richardson, David (2009) Are nested case-control studies biased? Epidemiology 20:321-9
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
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
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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