OBJECTIVES: In the majority of clinical trials patients are randomised equally between treatment groups. This approach maximises statistical power for a given total sample size. The objectives of this paper were to determine if, when research costs between treatments differ, it is more economically efficient to randomise additional patients to the cheaper treatment, and how the optimum randomisation ratio can be estimated. METHODS: Estimation of the most economically efficient randomisation ratio for four hypothetical clinical trials using cost-effectiveness analysis. RESULTS: When research costs differ between treatments, and there is no constraint on total sample size, it is always more cost-effective to randomise more patients to the cheaper treatment. For example, a cost ratio between the lesser and more expensive treatment of ten, results in a randomisation ratio of 3.2:1. CONCLUSIONS: Unequal randomisation ratios should be more widely used as this will achieve optimum statistical power for the lowest expenditure of research resources.
RCT Entities:
OBJECTIVES: In the majority of clinical trials patients are randomised equally between treatment groups. This approach maximises statistical power for a given total sample size. The objectives of this paper were to determine if, when research costs between treatments differ, it is more economically efficient to randomise additional patients to the cheaper treatment, and how the optimum randomisation ratio can be estimated. METHODS: Estimation of the most economically efficient randomisation ratio for four hypothetical clinical trials using cost-effectiveness analysis. RESULTS: When research costs differ between treatments, and there is no constraint on total sample size, it is always more cost-effective to randomise more patients to the cheaper treatment. For example, a cost ratio between the lesser and more expensive treatment of ten, results in a randomisation ratio of 3.2:1. CONCLUSIONS: Unequal randomisation ratios should be more widely used as this will achieve optimum statistical power for the lowest expenditure of research resources.
Authors: Jill Porthouse; Sarah Cockayne; Christine King; Lucy Saxon; Elizabeth Steele; Terry Aspray; Mike Baverstock; Yvonne Birks; Jo Dumville; Roger Francis; Cynthia Iglesias; Suezann Puffer; Anne Sutcliffe; Ian Watt; David J Torgerson Journal: BMJ Date: 2005-04-30
Authors: Yvonne F Birks; Jill Porthouse; Caroline Addie; Karen Loughney; Lucy Saxon; Mike Baverstock; Roger M Francis; David M Reid; Ian Watt; David J Torgerson Journal: Osteoporos Int Date: 2004-03-03 Impact factor: 4.507