Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention

Claire, Ravinder; Gluud, Christian; Berlin, Ivan; Coleman, Tim; Leonardi-Bee, Jo

Abstract

Background: Assessing benefits and harms of health interventions is resource-intensive and often requires feasibility and pilot trials followed by adequately powered randomised clinical trials. Data from feasibility and pilot trials are used to inform the design and sample size of the adequately powered randomised clinical trials. When a randomised clinical trial is conducted, results from feasibility and pilot trials may be disregarded in terms of benefits and harms. Methods: We describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention’s effects. Results: We provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial.

Conclusions: Trial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.

Citation

Claire, R., Gluud, C., Berlin, I., Coleman, T., & Leonardi-Bee, J. (2020). Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention. BMC Medical Research Methodology, 20(1), Article 284. https://doi.org/10.1186/s12874-020-01169-7

• Journal Article Type: Article
• Acceptance Date: Nov 19, 2020
• Online Publication Date: Nov 30, 2020
• Publication Date: Nov 30, 2020
• Deposit Date: Nov 24, 2020
• Publicly Available Date: Dec 3, 2020
• Journal: BMC Medical Research Methodology
• Electronic ISSN: 1471-2288
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Issue: 1
• Article Number: 284
• DOI: https://doi.org/10.1186/s12874-020-01169-7
• Keywords: Meta-analysis, Trial sequential analysis methods, Trial Sequential Analysis software, Sample size, Information size, Smoking, Pregnancy, Randomised clinical trial, Pilot trial, Feasibility trial
• Public URL: https://nottingham-repository.worktribe.com/output/5068976
• Publisher URL: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01169-7
• Additional Information: Received: 12 June 2020; Accepted: 19 November 2020; First Online: 30 November 2020; : Not applicable.; : Not applicable.; : RC, CG, IB and TC declare that they have no competing interests.JLB reports fees from undertaking independent statistical review for Danone Nutricia Research, and in relation to providing statistical expertise to the Food Standards Agency, both outside the subject of the submitted work.