Scoping review of learning curve methods in minimally invasive thoracic surgery

Purpose The objective of this scoping review is to determine how learning curves are assessed in the thoracic surgical literature for video- and robot-assisted thoracic lung resections. Methods This scoping review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. A literature search was conducted, using four electronic databases: Ovid Medline, Ovid Embase, EBSCO CINAHL, and Web of Science. Two reviewers independently screened studies, extracted data, and assessed quality, with a third reviewer to resolve conflicts. Included studies were peer-reviewed primary data, that were written in English and evaluated the learning curve of minimally invasive anatomical segmental resection, lobectomy, pneumonectomy, wedge resection, and combinations of various lung resections. Results The search yielded a total of 1614 articles. After the screening phases, 56 articles remained eligible for inclusion. The most common method used to construct the learning curve was the chronological grouping of cases (split-group analysis), which was performed in 22 (39.29%) studies. The cumulative sum (CUSUM) method was the second most commonly used approach for evaluating the learning curve, used in 21 (37.50%) studies. Across the 56 included studies, a total of 15 unique outcomes were used for the learning curve analyses. The most commonly used learning curve outcome was operative time, which was used in 39 (69.64%) of the studies. Conclusion This scoping review explored the problem of heterogeneity in learning curve study methodology. Variation in study methods makes comparisons of the learning curves between and within different surgical procedures difficult. Therefore, further investigation in the uptake of set reporting standards in learning curve methodology may allow for the use of informing medical curricula, physician education, and quality control monitoring processes.