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Clinical Trials
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Statistical evaluation of learning curve effects in surgical trials

Jonathan A Cook

Health Services Research Unit, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen, AB25 2ZD, UK; j.a.cook{at}abdn.ac.uk

Craig R Ramsaya

Health Services Research Unit, University of Aberdeen, UK

Peter Fayers

Department of Public Health, University of Aberdeen, UK and Unit for Applied Clinical Research, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

Randomized controlled trials (RCTs) in surgery have been impeded by concerns that improvements in the technical performance of a new technique over time (a "learning curve") may distort comparisons. The statistical assessment of learning curves in trials has received little attention. In this paper, we discuss what a learning curve effect is, the factors which effect it, how to display it, and how to incorporate the learning effect into the trial analysis. Bayesian hierarchical models are proposed to adjust the trial results for the existence of a learning curve effect. The implications for trial evaluation and data collection are considered.

Clinical Trials, Vol. 1, No. 5, 421-427 (2004)
DOI: 10.1191/1740774504cn042oa
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