Methodological challenges in the analysis of recurrent events for randomised controlled trials with application to cardiovascular events in LEADER
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Methodological challenges in the analysis of recurrent events for randomised controlled trials with application to cardiovascular events in LEADER. / Furberg, Julie Kjaerulff; Rasmussen, Søren; Andersen, Per Kragh; Ravn, Henrik.
In: Pharmaceutical Statistics, Vol. 21, No. 1, 2022, p. 241-267.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Methodological challenges in the analysis of recurrent events for randomised controlled trials with application to cardiovascular events in LEADER
AU - Furberg, Julie Kjaerulff
AU - Rasmussen, Søren
AU - Andersen, Per Kragh
AU - Ravn, Henrik
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - competing risks
KW - randomised controlled trials
KW - recurrent events
KW - treatment effects
KW - FAILURE TIME DATA
KW - HEART-FAILURE
KW - SEMIPARAMETRIC REGRESSION
KW - LIKELIHOOD-ESTIMATION
KW - MARGINAL ANALYSIS
KW - CLINICAL-TRIALS
KW - FRAILTY MODELS
KW - WIN-RATIO
KW - IMPACT
KW - WEI
U2 - 10.1002/pst.2167
DO - 10.1002/pst.2167
M3 - Journal article
C2 - 34494361
VL - 21
SP - 241
EP - 267
JO - Pharmaceutical Statistics
JF - Pharmaceutical Statistics
SN - 1539-1604
IS - 1
ER -
ID: 279880327