Literature DB >> 28608361

Using Poisson-gamma model to evaluate the duration of recruitment process when historical trials are available.

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.
Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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


  2 in total

1.  Concept and development of an interactive tool for trial recruitment planning and management.

Authors:  Ruan Spies; Nandi Siegfried; Bronwyn Myers; Sara S Grobbelaar
Journal:  Trials       Date:  2021-03-06       Impact factor: 2.279

2.  Does asymmetry in patient recruitment in large critical care trials follow the Pareto principle?

Authors:  Mahesh Ramanan; Laurent Billot; Dorrilyn Rajbhandari; John Myburgh; Simon Finfer; Rinaldo Bellomo; Balasubramanian Venkatesh
Journal:  Trials       Date:  2020-05-05       Impact factor: 2.279

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.