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.
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 language | English |
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Pages (from-to) | 27-35 |
Number of pages | 9 |
Journal | Journal of Clinical Epidemiology |
Volume | 107 |
Early online date | 13 Nov 2018 |
DOIs | |
Publication status | Published - Mar 2019 |
Research Groups and Themes
- Centre for Surgical Research
Keywords
- Randomized controlled trial
- Surgery
- Clustering
- Learning curve