Abstract:
:In the analysis of survival data, there are often competing events that preclude an event of interest from occurring. Regression analysis with competing risks is typically undertaken using a cause-specific proportional hazards model. However, modern alternative methods exist for the analysis of the subdistribution hazard with a corresponding subdistribution proportional hazards model. In this paper, we introduce a flexible parametric mixture model as a unifying method to obtain estimates of the cause-specific and subdistribution hazards and hazard-ratio functions. We describe how these estimates can be summarized over time to give a single number comparable to the hazard ratio that is obtained from a corresponding cause-specific or subdistribution proportional hazards model. An application to the Women's Interagency HIV Study is provided to investigate injection drug use and the time to either the initiation of effective antiretroviral therapy, or clinical disease progression as a competing event.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Lau B,Cole SR,Gange SJdoi
10.1002/sim.4123subject
Has Abstractpub_date
2011-03-15 00:00:00pages
654-65issue
6eissn
0277-6715issn
1097-0258journal_volume
30pub_type
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