Some issues in predicting patient recruitment in multi-centre clinical trials

Bakhshi, A., Senn, S. and Phillips, A. (2013) Some issues in predicting patient recruitment in multi-centre clinical trials. Statistics in Medicine, 32(30), pp. 5458-5468. (doi: 10.1002/sim.5979) (PMID:24105891)

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Abstract

A key paper in modelling patient recruitment in multi-centre clinical trials is that of Anisimov and Fedorov. They assume that the distribution of the number of patients in a given centre in a completed trial follows a Poisson distribution. In a second stage, the unknown parameter is assumed to come from a Gamma distribution. As is well known, the overall Gamma-Poisson mixture is a negative binomial. For forecasting time to completion, however, it is not the frequency domain that is important, but the time domain and that of Anisimov and Fedorov have also illustrated clearly the links between the two and the way in which a negative binomial in one corresponds to a type VI Pearson distribution in the other. They have also shown how one may use this to forecast time to completion in a trial in progress. However, it is not just necessary to forecast time to completion for trials in progress but also for trials that have yet to start. This suggests that what would be useful would be to add a higher level of the hierarchy: over all trials. We present one possible approach to doing this using an orthogonal parameterization of the Gamma distribution with parameters on the real line. The two parameters are modelled separately. This is illustrated using data from 18 trials. We make suggestions as to how this method could be applied in practice.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Senn, Professor Stephen and Bakhshi, Mrs Andisheh
Authors: Bakhshi, A., Senn, S., and Phillips, A.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Robertson Centre
College of Science and Engineering > School of Mathematics and Statistics
Journal Name:Statistics in Medicine
Journal Abbr.:Stat Med
Publisher:Wiley
ISSN:0277-6715
ISSN (Online):1097-0258
Published Online:17 September 2013

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