As in our previous funding cycles, we propose to continue the development of two classes of statistical methods relevant to cancer epidemiology involving extended exposure histories and temporal modifying factors, one aim concerns design aspects of case-control and case-cohort studies and the other concerns the analysis of exposure-time response relationships. These two broad aims have remained unchanged since the beginning of the grant. But, as time has progressed, we have naturally narrowed our attention to particularly fruitful topics. Design and analysis methods for sampled cohort data: Much of our work in the last grant cycle was devoted to building a theoretical foundation for the analysis of a broad class of nested case-control study designs. This work has resulted in some important innovations both in the design and analysis of matched case-control and case-cohort studies. During this grant cycle, we intend to continue our work on these methods as well as extend them to unmatched case-control studies. Methods of exposure-time-response modeling: We have been developing 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. During this grant cycle, we intend to develop flexible, descriptive methods for visualizing time-modifying effects and develop methods to test the """"""""additivity of risk"""""""" assumption commonly made in models for latency.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA042949-16
Application #
6624655
Study Section
Special Emphasis Panel (ZRG1-SNEM-5 (01))
Program Officer
Erickson, Burdette (BUD) W
Project Start
1986-07-01
Project End
2004-08-31
Budget Start
2002-12-01
Budget End
2004-08-31
Support Year
16
Fiscal Year
2003
Total Cost
$341,330
Indirect Cost
Name
University of Southern California
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
072933393
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; 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
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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