JSM 2005 - Toronto

Abstract #303631

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 512
Type: Contributed
Date/Time: Thursday, August 11, 2005 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #303631
Title: Estimating the Cumulative Incidence of a Competing Risk when Data Are Subject to Left-truncation
Author(s): Bingshu E. Chen*+ and Joan Kramer and Mark H. Greene and Philip S. Rosenberg
Companies: National Institutes of Health and National Institutes of Health and National Institutes of Health and National Cancer Institute
Address: 6120 Executive blvd, Rockville, MD, 20852, United States
Keywords: Competing risks ; Left-truncation ; Counting process ; Survival analysis ; BRCA1 mutations ; Breat/ovarian cancer
Abstract:

In many epidemiological studies, subjects may experience more than one type of outcome. When the occurrence of one type of event precludes another, the cumulative incidence curve provides a more reasonable description of the cause-specific failure probability than does the Kaplan-Meier estimator. In this study, we consider the competing risks in the setting of differential study entry times. We develop a nonparametric estimator of the cumulative incidence curve and obtain corresponding point-wise standard errors that take the delayed entry into account. We show that for two-sample problems, existing methods such as the Gray test and the Pepe-Mori test, remain valid when the data contain delayed entry times. Simulation studies were conducted to evaluate the finite sample properties of the proposed methods. We apply our methods to a recent prospective cohort study of hereditary breast and ovary cancer (HBOC) conducted at the National Cancer Institute. Our methods allow us to estimate the cumulative incidence (penetrance) of breast and ovary cancer, allowing for competing mortality, in women with BRCA1 mutations.

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Revised March 2005