Marker processes in survival analysis.
In the development of many diseases there are often associated variables which continuously measure the progress of an individual towards the final expression of the disease (failure). Such variables are stochastic processes, here called marker processes, and, at a given point in time, they may provide information about the current hazard and subsequently on the remaining time to failure. Here we consider a simple additive model for the relationship between the hazard function at time t and the history of the marker process up until time t. We develop some basic calculations based on this model. Interest is focused on statistical applications for markers related to estimation of the survival distribution of time to failure, including (i) the use of markers as surrogate responses for failure with censored data, and (ii) the use of markers as predictors of the time elapsed since onset of a survival process in prevalent individuals. Particular attention is directed to potential gains in efficiency incurred by using marker process information.
Jewell
N P
NP
Department of Statistics, University of California, Berkeley 94720, USA.
Kalbfleisch
J D
JD
D015415:Biomarkers; D015658:HIV Infections / Q000209:etiology / Q000401:mortality; D006801:Humans; D015993:Life Tables; D016012:Poisson Distribution; D016016:Proportional Hazards Models; D013269:Stochastic Processes; D016019:Survival Analysis
D015415:Biomarkers