Special Issue about Competing Risks and Multi-State Models

Tutorial in biostatistics: competing risks and multi-state models.

Standard survival data measure the time span from some time origin until the occurrence of one type of event. If several types of events occur, a model describing progression to each of these competing risks is needed. Multi-state models generalize competing risks models by also describing transitions to intermediate events. Methods to analyze such models have been developed over the last two d...

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, ...

Coronary heart disease incidence and competing risks: an important issue

The estimation of lifetime morbid events is not a rare presentation of relatively old and of more recent epidemiological investigations, accompanied by evaluating rates, risks and predictors (more in general determinants or risk factors). However, when the follow-up period is very long and Kaplan-Meier survival curves are adopted, or KaplanMeier-based more complex models such as Cox’s analysis ...

Competing risks models and time-dependent covariates

New statistical models for analysing survival data in an intensive care unit context have recently been developed. Two models that offer significant advantages over standard survival analyses are competing risks models and multistate models. Wolkewitz and colleagues used a competing risks model to examine survival times for nosocomial pneumonia and mortality. Their model was able to incorporate...

Special Issue