On Cost-Efficient Designs for Clinical Studies
Open AccessThe cost of conducting clinical trials in the United States continues to increase. Factors that drive the cost of a study include the length of recruitment, the procedures or interventions under study, the frequency of measuring or evaluating outcomes, the overall length of the study, and the number of participants to be included in the study. However, typical approaches for designing clinical studies do not consider study costs. For example, for a given effect size (e.g., hazard ratio) the power to detect differences between two groups is typically a function of the total number of events observed in the study. Therefore, the same level of power will be achieved based on various combinations of the total number of participants, the length of accrual and follow-up times, and the group allocation probability.Herein, we provide a general framework for designing cost-efficient studies in the context of three clinical study designs. Study designs with continuous-time survival outcomes, sequential multiple assignment randomized trials (SMART), and multiply matched case-control studies are considered. Among the various study designs that achieve the desired level of power to detect a given effect size for a fixed type-I error level, the cost-efficient design is the design that minimizes the expected total study cost. The method is general and can be used for various studies with a sample size formula under various assumptions. For each study design, the proposed approach for designing the cost-efficient study is described. R Shiny web applications that implement these proposed methods are also presented.
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Sandoval_gwu_0075A_15623.pdf | 2022-03-06 | Open Access |
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