The importance of censoring in competing risks analysis of the subdistribution hazard.

ABSTRACT:

Background

The analysis of time-to-event data can be complicated by competing risks, which are events that alter the probability of, or completely preclude the occurrence of an event of interest. This is distinct from censoring, which merely prevents us from observing the time at which the event of interest occurs. However, the censoring distribution plays a vital role in the proportional subdistribution hazards model, a commonly used method for regression analysis of time-to-event data in the presence of competing risks.

Methods

We present the equations that underlie the proportional subdistribution hazards model to highlight the way in which the censoring distribution is included in its estimation via risk set weights. By simulating competing risk data under a proportional

SUBMITTER: Donoghoe MW 

PROVIDER: S-EPMC5379776 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature