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Research Article
Modelling, prediction and adaptive adjustment of recruitment in multicentre trials
Article first published online: 18 JUL 2007
DOI: 10.1002/sim.2956
Copyright © 2007 John Wiley & Sons, Ltd.
Issue
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Statistics in Medicine
Special Issue: French Society of Statistics, Biopharmacy and Health Group Fifth International Meeting on Statistical Methods in Biopharmacy “Statistical innovations in clinical trials”
Volume 26, Issue 27, pages 4958–4975, 30 November 2007
Additional Information
How to Cite
Anisimov, V. V. and Fedorov, V. V. (2007), Modelling, prediction and adaptive adjustment of recruitment in multicentre trials. Statistics in Medicine, 26: 4958–4975. doi: 10.1002/sim.2956
Publication History
- Issue published online: 10 OCT 2007
- Article first published online: 18 JUL 2007
- Manuscript Accepted: 27 APR 2006
- Manuscript Received: 1 DEC 2005
- Abstract
- References
- Cited By
Keywords:
- multicentre trial;
- random recruitment;
- Poisson-gamma model;
- estimation;
- prediction;
- adaptive adjustment
Abstract
This paper is focused on statistical modelling, prediction and adaptive adjustment of patient recruitment in multicentre clinical trials. We consider a recruitment model, where patients arrive at different centres according to Poisson processes, with recruitment rates viewed as a sample from a gamma distribution. A statistical analysis of completed studies is provided and properties of a few types of parameter estimators are investigated analytically and using simulation. The model has been validated using many real completed trials. A statistical technique for predictive recruitment modelling for ongoing trials is developed. It allows the prediction of the remaining recruitment time together with confidence intervals using current enrolment information, and also provision of an adaptive adjustment of recruitment by calculating the number of additional centres required to accomplish a study up to a certain deadline with a pre-specified probability. Results are illustrated for different recruitment scenarios. Copyright © 2007 John Wiley & Sons, Ltd.