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ACCOUNTING FOR BETWEEN-STUDY VARIATION IN INCREMENTAL NET BENEFIT IN VALUE OF INFORMATION METHODOLOGY

Authors

  • Andrew R. Willan,

    Corresponding author
    1. SickKids Research Institute, Toronto, Ontario, Canada
    • Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
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  • Simon Eckermann

    1. Centre for Health Services Development and Sydney Business School, University of Wollongong, Wollongong, New South Wales, Australia
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CHES, SickKids Research Institute, 555 University Avenue, Toronto, Ontario M5G 1X8, Canada. E-mail: andy@andywillan.com

ABSTRACT

Previous applications of value of information methods for determining optimal sample size in randomized clinical trials have assumed no between-study variation in mean incremental net benefit. By adopting a hierarchical model, we provide a solution for determining optimal sample size with this assumption relaxed. The solution is illustrated with two examples from the literature. Expected net gain increases with increasing between-study variation, reflecting the increased uncertainty in incremental net benefit and reduced extent to which data are borrowed from previous evidence. Hence, a trial can become optimal where current evidence is sufficient assuming no between-study variation. However, despite the expected net gain increasing, the optimal sample size in the illustrated examples is relatively insensitive to the amount of between-study variation. Further percentage losses in expected net gain were small even when choosing sample sizes that reflected widely different between-study variation. Copyright © 2011 John Wiley & Sons, Ltd.

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