ABSTRACT
This paper investigates the Bayesian procedures for comparing proportions. These procedures are especially suitable for accepting (or rejecting) the equivalence of two population proportions. Furthermore the Bayesian predictive probabilities provide a natural and flexible tool in monitoring trials, especially for choosing a sample size and for conducting interim analyses. These methods are illustrated with two examples where antithrombotic treatments are administrated to prevent further occurrences of thromboses.
Subject(s)
Bayes Theorem , Clinical Trials as Topic/statistics & numerical data , Data Interpretation, Statistical , Binomial Distribution , Drug Evaluation , Fibrinolytic Agents/pharmacology , Humans , Odds Ratio , Predictive Value of Tests , Sample SizeABSTRACT
In order to fulfil the ethical principles linked to the protection of patients randomized in a controlled clinical trial, monitoring procedures need to be set up. In this context, a committee of experts, called the data monitoring committee is in charge of reviewing regularly unblinded data to assess the quality and the relevance of the trial, to evaluate the evidence of an emerging treatment difference and to control the rate of occurrence of serious adverse events. After each meeting, the monitoring committee reports to the steering committee its recommendation to continue or to stop the trial prematurely. Protocol modifications might be proposed as well. Illustrated with several examples, this article reviews different situations a monitoring committee might have to tackle with.
Subject(s)
Clinical Trials as Topic , Drug Monitoring/methods , Pharmacy and Therapeutics Committee/organization & administration , Clinical Protocols , Drug Tolerance , France , Humans , Treatment OutcomeABSTRACT
Although the decision to continue or to stop prematurely a clinical trial is not solely based on statistical tests, they bring useful objective arguments to the data monitoring board. However, the multiple use of statistical tests leads to increase the risk of false positive conclusions in favor of one of the treatments, and several methods have been developed to address this problem. This article presents the four major strategies that are being used for monitoring clinical trials, as well as the rationale for planning and using such statistical monitoring procedures.
