Related Experiment Video
Updated: Feb 28, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Using Poisson-gamma model to evaluate the duration of recruitment process when historical trials are available
Nathan Minois1,2, Valérie Lauwers-Cances3, Stéphanie Savy2
1University of Toulouse III, Toulouse, F-31073, France.
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.
Related Concept Videos
Poisson Probability Distribution
The...
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Comparing the Survival Analysis of Two or More Groups
Hazard Rate
Assumptions of Survival Analysis

