Fitting spending functions.
Group sequential monitoring is used to provide guidance on stopping a clinical trial in progress based on interim evaluation of its efficacy objectives. A trial could stop because an experimental regimen (1) is efficacious, (2) lacks any sign of efficacy, or (3) is specifically less efficacious than a control. Group sequential methods using alpha- and beta-spending functions (Biometrika 1983; 70:659-663) are often used to create stopping boundaries for test statistics for efficacy hypotheses computed at interim analyses. This paper explores fitting alpha- and beta-spending functions that have specific values at specific interim analyses. Commonly used one-parameter families may not provide an adequate fit to more than one desired critical value. We define new one- and two-parameter families to provide additional flexibility along with examples to demonstrate their usefulness. The logistic family is one of these two-parameter families, which has been applied in several trials.
Anderson
Keaven M
KM
Clinical Biostatistics and Research Decision Sciences, Merck Research Laboratories, North Wales, PA 19454-2505, U.S.A. keaven_anderson@merck.com
Clark
Jason B
JB
D002986:Clinical Trials as Topic / Q000592:standards*; D003657:Decision Making; D006801:Humans; D016015:Logistic Models