During the first two years of our active CISNET project """"""""Survival Effects of Prostate Cancer Surveillance"""""""" a population model of prostate cancer incidence and mortality was developed and applied to analyze national population and cancer registry data. The new application will focus on using the model to understand, predict and optimize the population impact of cancer control processes in prostate cancer. Specifically, we will study the joint effect of progress in treatment of prostate cancer and dissemination of PSA on observed national incidence and mortality trends;make short- and long-term predictions of the trends;analyze racial disparities as they pertain to dissemination of PSA testing, natural history of prostate cancer, benign disorders in the prostate, dissemination of treatment, survival, incidence and mortality;assess the effect of misattribution bias on the patterns of prostate cancer mortality;evaluate the sensitivity of estimates of population impact of screening interventions and treatment on mortality;assess the impact of Transurethral Resection of the Prostate (TURP) on early detection of prostate cancer and population trends in the pre-PSA era;develop unbiased assessment of treatment effects from population data;translate the results of clinical and prevention trials, and retrospective analyses of clinical data in prostate cancer into the potential population impact of their dissemination;determine and evaluate optimal screening strategies and predict their effect on future national trends in prostate cancer incidence and mortality;develop a user-friendly interface for the model.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA097414-09
Application #
7679436
Study Section
Special Emphasis Panel (ZCA1-SRRB-K (M1))
Program Officer
Mariotto, Angela B
Project Start
2002-08-15
Project End
2010-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
9
Fiscal Year
2009
Total Cost
$299,885
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Wang, Shufang; Tsodikov, Alex (2010) A Self-consistency Approach to Multinomial Logit Model with Random Effects. J Stat Plan Inference 140:1939-1947
deVere White, Ralph W; Tsodikov, Alexander; Stapp, Eschelle C et al. (2010) Effects of a high dose, aglycone-rich soy extract on prostate-specific antigen and serum isoflavone concentrations in men with localized prostate cancer. Nutr Cancer 62:1036-43
Draisma, Gerrit; Etzioni, Ruth; Tsodikov, Alex et al. (2009) Lead time and overdiagnosis in prostate-specific antigen screening: importance of methods and context. J Natl Cancer Inst 101:374-83
Chefo, Solomon; Tsodikov, Alex (2009) Stage-specific cancer incidence: an artificially mixed multinomial logit model. Stat Med 28:2054-76
Laxman, Bharathi; Morris, David S; Yu, Jianjun et al. (2008) A first-generation multiplex biomarker analysis of urine for the early detection of prostate cancer. Cancer Res 68:645-9
Tsodikov, Alex; Chefo, Solomon (2008) Generalized Self-Consistency: Multinomial logit model and Poisson likelihood. J Stat Plan Inference 138:23802397
Tsodikov, A; Garibotti, G (2007) Profile information matrix for nonlinear transformation models. Lifetime Data Anal 13:139-59
Tsodikov, A; Szabo, A; Wegelin, J (2006) A population model of prostate cancer incidence. Stat Med 25:2846-66
Broet, Philippe; Tsodikov, Alexander; De Rycke, Yann et al. (2004) Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial. Lifetime Data Anal 10:103-20