JSM 2005 Online Program

Abstract #303607

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	72
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor:	Section on Statistics in Epidemiology
Abstract - #303607
Title:	Attributable Risk Estimation in Longitudinal Studies with Censoring
Author(s):	Cynthia S. Crowson*+ and Terry M. Therneau and Sherine E. Gabriel and W. Michael O'Fallon
Companies:	Mayo Clinic and Mayo Clinic and Mayo Clinic and Mayo Clinic
Address:	Harwick 7, Rochester, MN, 55905, United States
Keywords:	population attributable risk ; etiologic fraction
Abstract:	Population attributable risk (AR) or etiologic fraction is the proportion of a disease that could be prevented by elimination of a causal risk factor from the population. AR is an epidemiologic or public health measure, which conceptually combines the prevalence of a risk factor with the prognostic effect of the risk factor. In longitudinal studies, AR is a function of time because the prevalence of a risk factor changes over time, as does the prevalence of disease. In some instances, the elimination of a risk factor may significantly delay the onset of the disease, but may not change the lifetime risk. Estimating the full AR curve on some time scale of interest (age, time since event) is more informative than considering a single value. We estimate time-specific AR based on cumulative incidence adjusted for the competing risk of death. We use Cox models with time-dependent covariates to obtain AR estimates adjusted for confounders. This method can identify risk factors with the greatest potential for reducing disease burden. We will demonstrate the unique value of this approach with illustrative examples that arose from our studies of heart failure in rheumatoid arthritis.

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