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International Clinical Trials

Sample Sizing

With increased pressure to design more efficient and effective clinical trials in order to speed up the drug development process, it is imperative that strategies for reducing the number of patients are considered during the design phase of a clinical trial. A large amount of research (1-7) has been undertaken on the problem of sample size estimation for different trial designs.

However, in practice the methods are rarely used and sample sizes are usually based on simple formulae derived for the comparison of two means or proportions. After reviewing how sample sizes are derived, strategies for reducing the number of patients needed in clinical studies will be discussed; for example:

◆ Improving the precision of estimates without increasing patient numbers

◆ Expanding the treatment effect to be detected

◆ Implementing an adaptive sample size re-estimation strategy

◆ The use of one-sided tests in early phase development

◆ Incorporating study design features and data structures when estimating patient numbers

It will be shown that matching the sample size estimation process to the design and analysis strategy often reduces the number of patients in a clinical trial.

BASICS OF SAMPLE SIZE ESTIMATION

Sample size estimates for a clinical trial depend on several factors, including:

δ : The clinically meaningful difference to be detected
α : The type I error or probability of detecting a significant difference when the treatments are equally effective
β : The type II error or the probability of not detecting a significant difference when there is a difference of magnitude δ and given level of statistical significance


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Alan Phillips is Senior Director Biostatistics, Europe and the Rest of the World, at ICON Clinical Research. Prior to joining ICON, Alan worked at Wyeth Pharmaceuticals, where his last position was Senior Director Biostatistics at Wyeth Research’s worldwide headquarters in the US. His statistical interests include biostatistical guidelines for regulatory submissions, clinical trials and adaptive designs. Alan was a member of the Statisticians in Pharmaceutical Industry main committee from 1993 to 1996, the scientific sub-committee from 1995 to 1996, and the training sub-committee from 1991 to 1994. He has belonged to the Association of British Pharmaceutical Industry Statistics Task Force/PSI Regulatory sub-committee since 1998.
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