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Abstract:
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Clinical trials (CTs) are often monitored for efficacy or futility. Several methods for interim monitoring of CTs have been developed. Although informative, few of these methods convey information regarding effect sizes (e.g., treatment differences) and none use prediction to convey information regarding potential effect size estimates and associated precision, with trial continuation. We propose use of prediction and specifically "predicted intervals" (PIs) as a flexible and practical tool for quantitative monitoring of CTs. PIs provide information regarding effect sizes, are invariant to study design, and provide flexibility in the decision making process. We outline construction of PIs for binary, continuous, and time-to-event endpoints and present examples of their use. PIs provide a valuable tool for Data Monitoring Committees (DMCs).
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