Abstract
OBJECTIVES: The preceding article proposed an assured treatment design that would address certain difficulties in recruiting persons who are at greater risk into randomized clinical trials. The purpose of this article is to illustrate the statistical validity of the design in a practical setting. METHODS: Three actual randomized clinical trials were considered as case studies; in each, the data that would have been obtained under assured allocation were identified. Then, with only these data, together with a reasonable choice of model describing the response of subjects under standard treatment as a function of initial severity, the treatment effect was estimated for the subjects at greater risk. The estimates were compared with conventional estimates for the sicker patients randomized in the original trials. RESULTS: In each case, the estimates produced in the assured treatment trial were close to those observed in the randomized trial. CONCLUSIONS: Risk-based allocation trials deserve serious consideration when randomized clinical trials are difficult or impossible to execute. The proposed designs and analyses would allow physicians to offer persons at greater risk assurance that they would receive the new treatment, while researchers would retain the ability to draw valid statistical conclusions about treatment efficacy.
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Selected References
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