Abstract
Analysis of recurrent events is becoming increasingly popular for understanding treatment effects in randomised controlled trials. The analysis of recurrent events can improve efficiency and capture disease burden compared to standard time-to-first event analyses. However, the added knowledge about the multi-state process comes at the cost of modelling complexity. High mortality rates can complicate matters even more. A case study using data from a randomised controlled trial, LEADER, is presented to highlight interpretation of common methods as well as potential pitfalls when analysing recurrent events in the presence of a competing risk. The presented methods either target features of the underlying intensity functions or marginal traits of a multi-state process which includes terminal events or not. In particular, approaches to handle death as a part of an event and as a competing risk are discussed. A new method targeting the marginal mean function for a composite endpoint, which includes both death as a component and as a competing risk, will be introduced. Finally, recommendations for how to capture meaningful treatment effects in randomised controlled trials when analysing recurrent and terminal events will be made.
Original language | English |
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Journal | Pharmaceutical Statistics |
Volume | 21 |
Issue number | 1 |
Pages (from-to) | 241-267 |
Number of pages | 27 |
ISSN | 1539-1604 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- competing risks
- randomised controlled trials
- recurrent events
- treatment effects
- FAILURE TIME DATA
- HEART-FAILURE
- SEMIPARAMETRIC REGRESSION
- LIKELIHOOD-ESTIMATION
- MARGINAL ANALYSIS
- CLINICAL-TRIALS
- FRAILTY MODELS
- WIN-RATIO
- IMPACT
- WEI