Standard 4: Determining Adequate Sample Sizes

* Abbreviations: CINV — : chemotherapy-induced nausea and vomiting RCT — : randomized controlled trial RSV — : respiratory syncytial virus There are many challenges to be faced when conducting randomized controlled trials (RCTs) in pediatric research. One important challenge is the determination of an appropriate sample size. Recruiting more children than necessary risks unnecessary overexposure of children to an inferior treatment, whereas underestimating the sample required will lead to inconclusive or unreliable results. Both options pose important ethical dilemmas for the pediatric researcher. Reviews have concluded that sample size calculations are frequently based on inaccurate assumptions regarding the key pieces of information needed.1,2 For example, a recent “failed” pediatric RCT highlighted the commonly encountered problem of underestimating the SD of a continuous primary outcome variable.3 This leads to underestimation of the necessary sample size, inadequate statistical power, and, consequently, an unanswered study question. Similarly, an incorrect estimation of the frequency with which a dichotomous outcome, or event, occurs in the control group of a trial (known as the control or baseline event rate) will also lead to incorrect sample size estimation. This standards article uses a series of scenarios to assist pediatric researchers in not only determining an adequate trial sample size but also how to proceed when this sample size may be difficult to achieve. Recommendations for practice are summarized in Table 1. View this table: TABLE 1 Recommendations for Practice Methods to calculate adequate sample sizes are described for superiority, noninferiority, and cluster-randomized trials with various types of primary outcome variables, including continuous, dichotomous, or time-to-event data.4–10 In this article, we focus primarily on superiority trial designs with continuous or dichotomous outcomes. Information on noninferiority or equivalence designs, as well as on cluster-randomized designs, can be found in the literature.9,10 RCTs generally have many outcomes of interest, but the number of patients required (and the main statistical analysis) should be based on … Address correspondence to Martin Offringa, MD, PhD, Senior Scientist and Program Head, Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, 555 University Ave, Toronto, Ontario, Canada M5G 1X8. E-mail: martin.offringa{at}sickkids.ca