Why perform a priori sample size calculation?

Abstract

The application of evidence-based care in the practice of surgery has improved in the past decade (i.e., colorectal surgery, arthroplasty surgery),1,2 but surgical treatments are still less likely to be studied using full-scale and well-designed randomized controlled trials (RCTs).3 Few surgical RCTs report and justify sample size calculations, and insufficient study power is one of the major shortcomings of many surgical trials.4 For example, systematic reviews of the surgical RCTs have shown that only 28% of coronary artery bypass grafting surgery trials,4 12% of trauma or orthopedic surgery trials,5 41% of pancreatico-duodenectomy trials6 and 25% of laparoscopic surgery trials7 have reported sample size calculations. The findings from underpowered and poorly designed surgical RCTs may be overvalued because their design grants them unwarranted credibility.3 Moreover, erroneous conclusions generated by these trials may guide clinical practice as clinicians’ decisions may be influenced by the fact that an RCT design was used. This article focuses on the importance, concept and methods of a priori sample size calculation (or power analysis) in surgical RCTs. The underlying methods described for RCTs are equally applied to non-RCT designs.