This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Reprints and Permissions Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (3) Citing Articles via Google Scholar Google Scholar Articles by McMahon, P. M. Articles by Gazelle, G. S. Search for Related Content PubMed PubMed Citation Articles by McMahon, P. M. Articles by Gazelle, G. S. Social Bookmarking                   What's this?

Estimation of Mortality Rates for Disease Simulation Models Using Bayesian Evidence Synthesis

Institute for Technology Assessment, Massachusetts General Hospital, Boston, pamela{at}mgh-ita.org

Alan M. Zaslavsky, PhD

Department of Health Care Policy, Harvard Medical School, Boston

Milton C. Weinstein, PhD

Department of Health Policy and Management, Harvard School of Public Health, Boston

Karen M. Kuntz, ScD

Department of Health Policy and Management, Harvard School of Public Health, Boston

Jane C. Weeks, MD, MS

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston

G. Scott Gazelle, MD, MPH, PhD

Institute for Technology Assessment, Massachusetts General Hospital, Boston, Department of Health Policy and Management, Harvard School of Public Health, Boston

Purpose. The authors propose a Bayesian approach for estimating competing risks for inputs to disease simulation models. This approach is suggested when modeling a disease that causes a large proportion of all-cause mortality, particularly when mortality from the disease of interest and other-cause mortality are both affected by the same risk factor.

Methods. The authors demonstrate a Bayesian evidence synthesis by estimating other-cause mortality, stratified by smoking status, for use in a simulation model of lung cancer. National (US) survey data linked to death registries (National Health Interview Survey [NHIS]—Multiple Cause of Death files) were used to fit cause-specific hazard models for 3 causes of death (lung cancer, heart disease, and all other causes), controlling for age, sex, race, and smoking status. Synthesis of NHIS data with national vital statistics data on numbers and causes of deaths was performed in WinBUGS (version 1.4.1, MRC Biostatistics Unit, UK). Correction for inconsistencies between the NHIS and vital statistics data is described. A published cohort study was a source of prior information for smoking-related mortality.

Results. Marginal posterior densities of annual mortality rates for lung cancer and other-cause death (further divided into heart disease and all other causes), stratified by 5-year age interval, race (white and black), gender, and smoking status (current, former, never), were estimated, specific to a time period (1987-1995). Overall, black current smokers experienced the highest mortality rates.

Conclusions. Bayesian evidence synthesis is an effective method for estimation of cause-specific mortality rates, stratified by demographic factors.

Key Words: mortality rates • Bayesian evidence synthesis • simulation • disease

CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?

This article has been cited by other articles:

				P. M. McMahon, C. Y. Kong, B. E. Johnson, M. C. Weinstein, J. C. Weeks, K. M. Kuntz, J.-A. O. Shepard, S. J. Swensen, and G. S. Gazelle Estimating Long-term Effectiveness of Lung Cancer Screening in the Mayo CT Screening Study Radiology, May 5, 2008; (2008) 2481071446. [Abstract] [Full Text]

				A. B. Knudsen, P. M. McMahon, and G. S. Gazelle Use of Modeling to Evaluate the Cost-Effectiveness of Cancer Screening Programs J. Clin. Oncol., January 10, 2007; 25(2): 203 - 208. [Abstract] [Full Text] [PDF]

				D. A. Berry Bayesian statistics. Med Decis Making, September 1, 2006; 26(5): 429 - 430. [PDF]

				C. B. Schechter Posterior progress. Med Decis Making, September 1, 2006; 26(5): 431 - 433. [PDF]