Research Article| Volume 56, ISSUE 6, P546-552, June 2003

Multivariate estimation of cumulative incidence, prevalence, and morbidity time of a disease when death is likely

  • Yan Yan
    Corresponding author: Tel.: 314-362-9290; fax: 314-362-9275
    Department of Surgery, Washington University Medical School, 4960 Children's Place, Box 8242, St. Louis, MO 63110, USA

    Division of Biostatistics, Washington University Medical School, 660 South Euclid Avenue, St Louis, MO 63110, USA
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  • Donald R. Hoover
    Department of Statistics and Institute for Health, Health Care Policy and Aging Research, Rutgers University,110 Frelinghuysen Road, Piscataway, NJ 08854, USA
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  • Richard D. Moore
    Department of Internal Medicine, Johns Hopkins University School of Medicine, 1830 East Monument Street, Baltimore, MD 21287, USA
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  • Chengjie Xiong
    Division of Biostatistics, Washington University Medical School, 660 South Euclid Avenue, St Louis, MO 63110, USA
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      Competing risk of death from other causes before developing the outcome of interest is a common phenomenon in clinical settings. In a previous article, we developed the “sandwiching method” as one approach to estimate disease incidence and morbidity time for populations at a high risk of death from other causes. In addition to its computational simplicity, the sandwiching method is also relatively assumption free. This article extends the original sandwiching method to incorporate patient characteristics into the estimation by using Cox's proportional hazards model. Data from the Johns Hopkins Hospital AIDS service were used to illustrate this extended method. The importance of estimates was discussed in the context of planning health care needs.


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