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OBJECTIVES: To establish current practice of the management of learning and clustering effects, by treating center and surgeon, in the design and analysis of randomized surgical trials. STUDY DESIGN AND SETTING: The need for more surgical randomized trials is well recognized, and in recent years conduct has grown. Rigorous design, conduct, and analyses of such studies is important. Two methodological challenges are clustering effects, by center or surgeon, and surgical learning on trial outcomes. Sixteen leading journals were searched for randomized trials published within a two-year period. Data were extracted on considerations for learning and clustering effects. RESULTS: A total of 247 eligible studies were identified. Trials accounted for learning with 2% using an expertise-based design and 39% accounting for expertise by predefining surgeon credentials. One study analyzed learning. Clustering, by site and surgeon, was commonly managed by stratifying randomization, although one-third of center and 40% of surgeon stratified trials did not also adjust analysis. CONCLUSION: Considerations for surgical learning and clustering effects are often unclear. Methods are varied and demonstrate poor adherence to established reporting guidelines. It is recommended that researchers consider these issues on a trial-by-trial basis, and report methods or justify where not needed to inform interpretation of results.

Original publication

DOI

10.1016/j.jclinepi.2018.11.004

Type

Journal article

Journal

J clin epidemiol

Publication Date

03/2019

Volume

107

Pages

27 - 35

Keywords

Clustering, Learning curve, Randomized controlled trial, Statistics, Surgery