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JSM 2012 Online Program

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Activity Details

CE_19C Tue, 7/31/2012, 8:00 AM - 12:00 PM HQ-Indigo E
Design and Analysis of Biomarker Studies for Risk Prediction — Continuing Education Course
ASA , Biometrics Section
Instructor(s): Tianxi Cai, Harvard University, Yingye Zheng, Fred Hutchinson Cancer Research Center
An accurate and individualized outcome prediction promises to dramatically change clinical decision making in many branches of medicine, for example in early diagnosis of cancer and in selecting patient-specific treatments. But translating the promise into reality is not easy. Clinical evaluations, while remaining an essential basis for risk assessment, may not be sufficient for complex diseases. Improved prediction may be achieved by combining information from multiple markers based on emerging new technology such as gene expression profiling, protein mass spectrometry and proton emission tomography. Most marker tests are imperfect, and incorporate test results can have enormous consequences in both financial and human terms. Prior to incorporating a biomarker into standard clinical care, rigorous evaluation is required. Designing an rigorous study that efficiently uses available biologic specimens is critical. Compared to classical statistical methods for evaluating medical diagnostic test, there is relatively little literature devoted to statistical methods for marker development carried out in a prospective cohort study with censored failure time outcome. This short course will introduce recent statistical development for constructing and evaluating risk prediction model (markers) with censored data. While providing some mathematical details, we will emphasize the concepts, methods and their real world applications with the aim of both (i) offering an overview of the rapid developing area of risk prediction and biomarker evaluation; and (ii) in depths discussions on efficient design of biomarker and risk prediction studies. Prerequisite: Survival analysis

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