Title: Incorporating survival data to case-control studies with incident and prevalent cases
Speaker: Soutrik Mandal, Division of Cancer Epidemiology and Genetics (National Cancer Institute | National Institutes of Health)
Date: September 29, 2020
Abstract: Typically, case-control studies only include incident cases to estimate odds-ratios for the association of risk factors with outcome from logistic regression models. Incorporating prevalent cases requires adjustment of the logistic model for the time between disease diagnosis and sampling, the backward time, to ensure unbiased odds-ratio estimates. To accommodate this survival bias in prevalent cases via backward time adjustment, one needs to estimate the distribution of time from disease onset to death. To relax parametric assumptions on this distribution, (needed when only backward times are available) we propose a computationally simple two-step procedure to incorporate additionally observed prospective survival time from all cases into the analysis of case-control studies with prevalent cases. We illustrate the proposed method through simulation studies and analyze the United States Radiologic Technologists Study to assess the association of SNPs in candidate genes with risk of breast cancer. Work done in collaboration with Jing Qin, Ruth Pfeiffer.