title: Informing the selection of futility stopping thresholds: case study from a late-phase clinical trial.
abstract: In an environment where (i) potential risks to subjects participating in clinical studies need to be managed carefully, (ii) trial costs are increasing, and (iii) there are limited research resources available, it is necessary to prioritize research projects and sometimes re-prioritize if early indications suggest that a trial has low probability of success. Futility designs allow this re-prioritization to take place. This paper reviews a number of possible futility methods available and presents a case study from a late-phase study of an HIV therapeutic, which utilized conditional power-based stopping thresholds. The two most challenging aspects of incorporating a futility interim analysis into a trial design are the selection of optimal stopping thresholds and the timing of the analysis, both of which require the balancing of various risks. The paper outlines a number of graphical aids that proved useful in explaining the statistical risks involved to the study team. Further, the paper outlines a decision analysis undertaken which combined expectations of drug performance with conditional power calculations in order to produce probabilities of different interim and final outcomes, and which ultimately led to the selection of the final stopping thresholds.
authors.affiliation: Infectious Diseases Statistics, GSK Research & Development, Greenford Road, Greenford, Middlesex, UK. sara.h.hughes@gsk.com
authors.forename: Sara
authors.initials: S
authors.lastname: Hughes
authors.forename: Robert L
authors.initials: RL
authors.lastname: Cuffe
authors.forename: Alfons
authors.initials: A
authors.lastname: Lieftucht
authors.forename: W
authors.initials: W
authors.lastname: Garrett Nichols
mesh_terms: D002986:Clinical Trials as Topic / Q000941:ethics / Q000379:methods; D003661:Decision Support Techniques; D006801:Humans; D008962:Models, Theoretical; D012107:Research Design; D018570:Risk Assessment; D013223:Statistics as Topic