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Randomized Controlled Trial
. 2022 May;31(5):1359-1370.
doi: 10.1007/s11136-021-03040-8. Epub 2021 Nov 24.

Joint modelling with competing risks of dropout for longitudinal analysis of health-related quality of life in cancer clinical trials

Benjamin Cuer  1   2   3 , Thierry Conroy  4   5 , Beata Juzyna  6 , Sophie Gourgou  7   8 , Caroline Mollevi  7   8   9 , Célia Touraine  7   8   9
Affiliations
Free article
Randomized Controlled Trial

Joint modelling with competing risks of dropout for longitudinal analysis of health-related quality of life in cancer clinical trials

Benjamin Cuer et al. Qual Life Res. 2022 May.
Free article

Abstract

Purpose: Health-related quality of life (HRQoL) is an important endpoint in cancer clinical trials. Analysis of HRQoL longitudinal data is plagued by missing data, notably due to dropout. Joint models are increasingly receiving attention for modelling longitudinal outcomes and the time-to-dropout. However, dropout can be informative or non-informative depending on the cause.

Methods: We propose using a joint model that includes a competing risks sub-model for the cause-specific time-to-dropout. We compared a competing risks joint model (CR JM) that distinguishes between two causes of dropout with a standard joint model (SJM) that treats all the dropouts equally. First, we applied the CR JM and SJM to data from 267 patients with advanced oesophageal cancer from the randomized clinical trial PRODIGE 5/ACCORD 17 to analyse HRQoL data in the presence of dropouts unrelated and related to a clinical event. Then, we compared the models using a simulation study.

Results: We showed that the CR JM performed as well as the SJM in situations where the risk of dropout was the same whatever the cause. In the presence of both informative and non-informative dropouts, only the SJM estimations were biased, impacting the HRQoL estimated parameters.

Conclusion: The systematic collection of the reasons for dropout in clinical trials would facilitate the use of CR JMs, which could be a satisfactory approach to analysing HRQoL data in presence of both informative and non-informative dropout.

Trial registration: This study is registered with ClinicalTrials.gov, number NCT00861094.

Keywords: Clinical trials; Competing risks; Health-related quality of life; Joint modelling; Missing data; Oncology.

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