Assessment of type I error rate associated with dose-group switching in a longitudinal Alzheimer trial.
In clinical trials, there always is the possibility to use data-driven adaptation at the end of a study. There prevails, however, concern on whether the type I error rate of the trial could be inflated with such design, thus, necessitating multiplicity adjustment. In this project, a simulation experiment was set up to assess type I error rate inflation associated with switching dose group as a function of dropout rate at the end of the study, where the primary analysis is in terms of a longitudinal outcome. This simulation is inspired by a clinical trial in Alzheimer's disease. The type I error rate was assessed under a number of scenarios, in terms of differing correlations between efficacy and tolerance, different missingness mechanisms, and different probabilities of switching. A collection of parameter values was used to assess sensitivity of the analysis. Results from ignorable likelihood analysis show that the type I error rate with and without switching was approximately the posited error rate for the various scenarios. Under last observation carried forward (LOCF), the type I error rate blew up both with and without switching. The type I error inflation is clearly connected to the criterion used for switching. While in general switching, in a way related to the primary endpoint, may impact the type I error, this was not the case for most scenarios in the longitudinal Alzheimer trial setting under consideration, where patients are expected to worsen over time.
a I-BioStat, Universiteit Hasselt , Diepenbeek , Belgium.
Aklilu
A
Habteab Ghebretinsae
Geert
G
Molenberghs
Alex
A
Dmitrienko
Walt
W
Offen
Gopalan
G
Sethuraman
D000544:Alzheimer Disease / Q000188:drug therapy* / Q000453:epidemiology / Q000523:psychology; D017326:Clinical Trials, Phase III as Topic / Q000379:methods / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D023381:Endpoint Determination / Q000706:statistics & numerical data; D006801:Humans; D016013:Likelihood Functions; D008137:Longitudinal Studies; D015233:Models, Statistical; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*
Ignorable likelihood; LOCF; MAR; MNAR; Type I error