Issues in designing sequential stopping rules for monitoring side effects in clinical trials.
In a clinical trial of a new treatment, severe side effects may be a problem, and the trial may have to be stopped if the incidence is too high. We need to anticipate the need for such a decision to halt the trial early, and possibly design formal stopping rules for an excess of untoward events. The work presented here discusses the issues involved in such monitoring in comparison with more conventional analysis of the outcome variable. Stopping rules are derived by application of the sequential probability ratio test (SPRT), followed by computation of the exact size and power and adjustments of the consequent rules to achieve chosen operating characteristics appropriate to a monitoring situation. Rules are also derived from a Bayesian approach. These rules are applied to an illustrative trial and compared to the actual conditions that lead to the closing the trial.
Goldman
A I
AI
Division of Biometry, University of Minnesota, Minneapolis 55455.
D016026:Bone Marrow Transplantation; D002986:Clinical Trials as Topic; D006086:Graft vs Host Disease / Q000517:prevention & control; D006801:Humans; D000922:Immunotoxins / Q000009:adverse effects; D011336:Probability; D012107:Research Design
D000922:Immunotoxins