Marker-Dependent Hazard Estimation: An Application to AIDS


Full text of article in Statistics in Medicine, 12, 843-865, 1993.


The Acquired Immunodeficiency Syndrome (AIDS) results from infection with the Human Immunodeficiency Virus (HIV). The time of infection is generally unknown since transmission usually occurs during the course of repeated sexual contacts or needle sharing. Brookmeyer and Gail (1987) describe the biases that may rise in survival analyses using the recruitment times rather than the unknown infection time as the origin in prevalent cohorts of HIV-infected individuals. We apply a nonparametric hazard estimator, introduced by Nielsen (1991), which assumes that the hazard depends upon the unknown time of infection solely through the value of possibly multidimensional markers of HIV-disease progression such as CD4+ T lymphocyte cell counts. Essentially, we estimate the hazard for a specific marker value y by dividing the number of occurrences among subjects with marker measurements in a neighborhood of y by the total risk time in that neighborhood. We present this estimator, which relies upon kernel estimator techniques to produce a smooth estimate, within a counting process framework. We apply this method to marker data form the San Francisco Men's Health Study.


Disease Modeling | Survival Analysis

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