The most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee’s definition of a “large” trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false.
Thus, a critical aspect of clinical trial design is determination of the sample size needed to establish the feasibility of the study (sufficient statistical power). The number of participants in a clinical trial should always be large enough to provide a sufficiently precise answer to the research question posed, but it should also be the minimum necessary to achieve this aim. A proposed study that cannot answer the question being asked because the necessary sample size cannot be attained should not be conducted on ethical grounds. That is, it is unacceptable to expose patients or research participants to harms even inconveniences if there is no prospect that useful and potentially generalizable information will result from the study.
Adequately powered randomized clinical trials and double-blind, randomized clinical trials are generally regarded as the most authoritative research methods for establishment of the efficacies of therapeutic interventions. By allocating sufficient numbers of individuals to groups (e.g., experimental or control groups), investigators can estimate or determine with some degree of certainty the effect of a given intervention.
Because of the design and analysis constraints of small sample size trials and because of their inherent uncertainties, they require at least as much and probably more thought and planning than traditional large clinical trials. Small sample size studies may also require additional methods for evaluation of the effectiveness of a therapeutic intervention. In addition, inferences should consider the size of the population relative to the size of the sample.
