Risk Estimation Using a Surrogate Marker Measured with Error

Our goal is to estimate the risk of contacting Pneurnocystis carinii Pneumonia (PCP) in a fixed time interval based on the current observed CD4 count for an individual. The methodology used involves a linear random effects model for the trajectory of the observed CD4 counts in order to obtain predicted values at each event time. These predicted counts are imputed in the partial likelihood for estimating a regression coefficient in the Cox model. Subsequently, Monte Carlo techniques are employed to approximate the risk of PCP in a six month period. The method will be illustrated on data from AIDS patients.