Abstract
Sample size calculations are fundamental to the power of a study. Estimates of the necessary sample size to achieve a given treatment effect size can be performed pre-trial based on available literature.Sample size calculations take into account the chosen effect size i.e. the minimal effect of the treatment which would be considered clinically relevant. Smaller effect sizes require a sufficiently large sample size or higher event rate to detect differences between groups. Larger effect sizes are sometimes chosen for study in order to justify the risks of adverse events and expense of certain treatments.Lower than expected event rates, mediated by censoring and competing risks, period effects, and inclusion of patients at lower risk of the outcome, can impact the power of the study.Time-to-event study designs adjust for censoring and competing risks.If a lower than expected event rate is highlighted during an interim analysis, strategies include increasing the sample size, either by changing the inclusion or exclusion criteria, increasing the number of study centers or increasing the study duration.