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Activity Number: 520 - Survival Analysis III
Type: Contributed
Date/Time: Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #328587 Presentation
Title: Analysis of Lethal Cancer Among a Cohort of Initially Disease-Free Women
Author(s): Bernard Rosner* and Elizabeth Poole
Companies: Harvard Medical School and Sanofi
Keywords: survival analysis; multiple event analysis; lethal cancer; 2-stage model

Pre-diagnosis factors may influence a cancer's likelihood to become fatal. Many methods have been used to evaluate associations with lethal cancer among a population that was initially disease-free, but each has limitations. We propose a novel 2-stage method for evaluating risk of lethal disease that separately estimates the association with cancer incidence and survival among cancer cases, then combines the two estimates into a single measure of association with lethal disease among disease-free individuals. We compared 5 methods to evaluate risk factors for lethal cancer: traditional time to event analysis using baseline covariates (TTE);time-to-event analysis with time-dependent covariates (TDC) updated until death;TDC where exposure is only updated until diagnosis (TDX);ordered multiple event analysis (Prentice-Williams-Peterson [PWP]);and our 2-stage model (2S) and applied them to Nurses' Health Study data. In simulations, the PWP model had the most bias and highest mean squared error, while the 2-stage model performed best. Our 2-stage model may be a useful tool for identifying pre-diagnosis factors that lead to more aggressive disease.

Authors who are presenting talks have a * after their name.

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