Bivariate pseudo-observations for recurrent event analysis with terminal events

Julie K. Furberg (), Per K. Andersen, Sofie Korn, Morten Overgaard and Henrik Ravn
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Julie K. Furberg: Biostatistics GLP-1 and CV 1, Novo Nordisk A/S
Per K. Andersen: University of Copenhagen
Sofie Korn: Biostatistics 1, LEO Pharma A/S
Morten Overgaard: Aarhus University
Henrik Ravn: Biostatistics GLP-1 and CV 1, Novo Nordisk A/S

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2023, vol. 29, issue 2, No 2, 256-287

Abstract: Abstract The analysis of recurrent events in the presence of terminal events requires special attention. Several approaches have been suggested for such analyses either using intensity models or marginal models. When analysing treatment effects on recurrent events in controlled trials, special attention should be paid to competing deaths and their impact on interpretation. This paper proposes a method that formulates a marginal model for recurrent events and terminal events simultaneously. Estimation is based on pseudo-observations for both the expected number of events and survival probabilities. Various relevant hypothesis tests in the framework are explored. Theoretical derivations and simulation studies are conducted to investigate the behaviour of the method. The method is applied to two real data examples. The bivariate marginal pseudo-observation model carries the strength of a two-dimensional modelling procedure and performs well in comparison with available models. Finally, an extension to a three-dimensional model, which decomposes the terminal event per death cause, is proposed and exemplified.

Keywords: Recurrent events; Terminal events; Pseudo-observations; Simultaneous model; Multi-state model (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10985-021-09533-5

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