Interim data monitoring in cluster randomised trials: practical issues and a case study

Karla Hemming, James Martin, Ioannis Gallos, Arri Coomarasamy, Lee Middleton, E-MOTIVE study group

Research output: Contribution to journalArticlepeer-review

73 Downloads (Pure)

Abstract

Background
There is an abundance of guidance for the interim monitoring of individually randomised trials. While methodological literature exists on how to extend these methods to cluster randomised trials, there is little guidance on practical implementation. Cluster trials have many features which make their monitoring needs different. We outline the methodological and practical challenges of interim monitoring of cluster trials; and apply these considerations to a case study.

Case study
The E-MOTIVE study is an 80-cluster randomised trial of a bundle of interventions to treat postpartum haemorrhage. The proposed data monitoring plan includes (1) monitor sample size assumptions, (2) monitor for evidence of selection bias, and (3) an interim assessment of the primary outcome, as well as monitoring data completeness. The timing of the sample size monitoring is chosen with both consideration of statistical precision and to allow time to recruit more clusters. Monitoring for selection bias involves comparing individual-level characteristics and numbers recruited between study arms to identify any post-randomisation participant identification bias. An interim analysis of outcomes presented with 99.9% confidence intervals using the Haybittle–Peto approach should mitigate any concern regarding the inflation of type-I error. The pragmatic nature of the trial means monitoring for adherence is not relevant, as it is built into a process evaluation.

Conclusions
The interim analyses of cluster trials have a number of important differences to monitoring individually randomised trials. In cluster trials, there will often be a greater need to monitor nuisance parameters, yet there will often be considerable uncertainty in their estimation. This means the utility of sample size re-estimation can be questionable particularly when there are practical or funding difficulties associated with making any changes to planned sample sizes. Perhaps most importantly interim monitoring has the potential to identify selection bias, particularly in trials with post-randomisation identification or recruitment. Finally, the pragmatic nature of cluster trials might mean that the utility of methods to allow for interim monitoring of outcomes based on statistical testing, or monitoring for adherence to study interventions, are less relevant. Our intention is to facilitate the planning of future cluster randomised trials and to promote discussion and debate to improve monitoring of these studies.
Original languageEnglish
Pages (from-to)552-561
Number of pages10
JournalClinical Trials
Volume18
Issue number5
Early online date22 Jun 2021
DOIs
Publication statusPublished - 1 Oct 2021

Bibliographical note

Funding Information:
The authors thank members of the data monitoring committee read and commented on the data monitoring charter but are not listed as co-authors to retain independence. The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This research was partly funded by the UK NIHR Collaborations for Leadership in Applied Health Research and Care West Midlands initiative. K.H. is funded by an NIHR Senior Research Fellowship SRF-2017-10-002. E-MOTIVE is a commissioned trial by the Bill & Melinda Gates Foundation. The Institute of Global Innovation and Alumni Fund of University of Birmingham are also financially supporting the study.

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This research was partly funded by the UK NIHR Collaborations for Leadership in Applied Health Research and Care West Midlands initiative. K.H. is funded by an NIHR Senior Research Fellowship SRF-2017-10-002. E-MOTIVE is a commissioned trial by the Bill & Melinda Gates Foundation. The Institute of Global Innovation and Alumni Fund of University of Birmingham are also financially supporting the study.

Publisher Copyright:
© The Author(s) 2021.

Keywords

  • Data monitoring
  • cluster randomised trials
  • selection bias

ASJC Scopus subject areas

  • Pharmacology

Fingerprint

Dive into the research topics of 'Interim data monitoring in cluster randomised trials: practical issues and a case study'. Together they form a unique fingerprint.

Cite this