Randomized trials involving surgery did not routinely report considerations of learning and clustering effects

Elizabeth Jane Conroy, Anna Rosala-Hallas, Jane Blazeby, Girvan Burnside, Jonathan Cook, Carrol Gamble

Research output: Contribution to journalArticle (Academic Journal)peer-review

5 Citations (Scopus)
244 Downloads (Pure)

Abstract

Objective
To establish current practice of the management of learning and clustering effects, by treating centre and surgeon, in the design and analysis of randomised surgical trials.

Study design and setting
The need for more surgical randomised trials is well recognised, and in recent years conduct has grown. Rigorous design, conduct and analyses of such studies is important. Two methodological challenges are clustering effects, by centre or surgeon, and surgical learning on trial outcomes.

Sixteen leading journals were searched for randomised trials published within a two year period. Data were extracted on considerations for learning and clustering effects.

Results
247 eligible studies were identified. Trials accounted for learning with 2% using an expertise-based design and 39% accounting for expertise by pre-defining surgeon credentials. One study analysed learning. Clustering, by site and surgeon, was commonly managed by stratifying randomisation, although one-third of centre 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 languageEnglish
Pages (from-to)27-35
Number of pages9
JournalJournal of Clinical Epidemiology
Volume107
Early online date13 Nov 2018
DOIs
Publication statusPublished - Mar 2019

Structured keywords

  • Centre for Surgical Research

Keywords

  • Randomized controlled trial
  • Surgery
  • Clustering
  • Learning curve

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