[How to assess the size of a clinical trial?]

The interpretation of the results of a clinical trial, an experimental method now recognised as the agreed technique for studying new therapeutic modes of treatment in man, is based on a statistical study of data collected on a sample of patients enrolled in the study and treated till its fulfillment. This interpretation is often made using statistical inference techniques based on the construction of a decision rule associated with a statistical hypothesis test; this hypothesis test serves to formalize a research question in a precise manner, and allows the null hypothesis H0 to be tested against an alternative hypothesis H1. The decision rule will be constructed using a probability distribution, which assumes control against type I error, and consists of falsely rejecting the null hypothesis. However, the control of the risk of type II error, made error where one mistakenly takes a decision not to reject the null hypothesis, can only be achieved using a sufficiently large sample. The correct evaluation of the sample size is thus paramount if one does not wish to be doomed to the failure of a study, by including an insufficient number of patients to achieve the aimed objective. The aim of this report is to review how this evaluation can be due, in a practical manner without proof, in the context of simple situations which are used when Phase II or III clinical trials are put into action.