Progression-related endpoints (such as time to progression or progression-free survival) and time to death are common endpoints in cancer clinical trials. It is of interest to study the link between progression-related endpoints and time to death (e.g. to evaluate the degree of surrogacy). However, current methods ignore some aspects of the definitions of progression-related endpoints. We review those definitions and investigate their impact on modeling the joint distribution. Further, we propose a multi-state model in which the association between the endpoints is modeled through a frailty term. We also argue that interval-censoring needs to be taken into account to more closely match the latent disease evolution. The joint distribution and an expression for Kendall's tau are derived. The model is applied to data from a clinical trial in advanced metastatic ovarian cancer.
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Dejardin et al. (2010) studied this question.
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