Competing risks and multistate models.

Complex clinical endpoints are present in studies in cancer. Especially in studies on hematopoietic stem-cell transplantation (HSCT), various risks exist after HSCT. Patients can experience acute and chronic graft versus host disease (GVHD) or need to undergo immunosuppressive therapy (IST), a relapse can occur, or patients can die after relapse or without former relapse (nonrelapse mortality, NRM). Sometimes, endpoints can be reasonably combined in a composite endpoint, as, for example, relapse and NRM are combined into disease-free survival (DFS). In this case, standard survival techniques, as Kaplan-Meier estimation of the DFS probability, can be applied. Often, interest focuses on endpoints for which competing risks are present, as, for example, GVHD, with death without prior GVHD as competing risk. This results in a competing risks model, a special case of a multistate model. A more complex multistate model is required when the effects of events occurring in the course of the study on further disease process shall be investigated, as, for example, the effect of GVHD on relapse and NRM. Another endpoint of interest is time under IST. As patients usually experience multiple episodes of IST, thus switching back and forth between "IST" and "no IST" during follow-up, the multistate model used for analysis must be adapted for this event structure. The aim of this nontechnical report is to explain use and interpretation of Cox-type regression models suitable for the different situations in a randomized trial on the effects of anti-T-cell globulin as GVHD prophylaxis.