Abstract
Joint modeling of longitudinal data and survival data has been increasingly used in clinical trials on cancer. In prostate cancer for example, these models permit to study the effect of pronostic factors on the time of relapse, and the link between longitudinal measures of current level of prostate-specific antigen (PSA) and time of relapse. In practice, there are different types of relapse. It might be interesting to distinguish them and to research, for example, which covariates impact the risk to have a distant recurrence or a death from prostate cancer separately of their effect on the risk of local
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