| Literature DB >> 28608361 |
Nathan Minois1,2, Valérie Lauwers-Cances3, Stéphanie Savy2, Michel Attal4, Sandrine Andrieu1,2,3, Vladimir Anisimov5, Nicolas Savy1,6.
Abstract
At the design of clinical trial operation, a question of a paramount interest is how long it takes to recruit a given number of patients. Modelling the recruitment dynamics is the necessary step to answer this question. Poisson-gamma model provides very convenient, flexible and realistic approach. This model allows predicting the trial duration using data collected at an interim time with very good accuracy. A natural question arises: how to evaluate the parameters of recruitment model before the trial begins? The question is harder to handle as there are no recruitment data available for this trial. However, if there exist similar completed trials, it is appealing to use data from these trials to investigate feasibility of the recruitment process. In this paper, the authors explore the recruitment data of two similar clinical trials (Intergroupe Francais du Myélome 2005 and 2009). It is shown that the natural idea of plugging the historical rates estimated from the completed trial in the same centres of the new trial for predicting recruitment is not a relevant strategy. In contrast, using the parameters of a gamma distribution of the rates estimated from the completed trial in the recruitment dynamic model of the new trial provides reasonable predictive properties with relevant confidence intervals.Entities:
Keywords: Bayesian statistics; Cox process; clinical trials; recruitment time; trial feasibility
Mesh:
Year: 2017 PMID: 28608361 DOI: 10.1002/sim.7365
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373