TY - JOUR T1 - Expertise-based design in surgical trials: a narrative review JF - Canadian Journal of Surgery JO - CAN J SURG SP - E594 LP - E602 DO - 10.1503/cjs.008520 VL - 64 IS - 6 AU - Ali Alsagheir AU - Alex Koziarz AU - Emilie P. Belley-Côté AU - Richard P. Whitlock Y1 - 2021/11/10 UR - http://canjsurg.ca/content/64/6/E594.abstract N2 - Randomized controlled trials (RCTs) are the most robust study design for evaluating the safety and efficacy of a therapeutic intervention. However, their internal validity are at risk when evaluating surgical interventions. This review summarizes existing expertise- based trials in surgery and related methodological concepts to guide surgeons performing this work. We provide caseloads required to reach the learning curve for various surgical interventions and report criteria for expertise from published and unpublished expertise-based trials. In addition, we review design and implementation concepts of expertise-based trials, including recruitment of surgeons, crossover, ethics, generalizability, sample size and definitions for learning curve. Several RCTs have used an expertise-based design. We found that the majority of definitions used for expertise were vague, heterogeneous, and inconsistent across trials evaluating the same surgical intervention. Statistical methods exist to adjust for the learning curve; however, there is limited guidance. We developed the following criteria for surgical expertise for future trials: 1) decide on the proxy to be used for the learning curve, and 2) assess eligible surgeons by comparing their performance to the previously defined expertise criteria. ER -