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Longitudinal clinical trials with adaptive choice of follow‐up time
Author(s) -
Jeffries Neal,
Geller Nancy L.
Publication year - 2015
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12287
Subject(s) - null hypothesis , context (archaeology) , time point , type i and type ii errors , test statistic , clinical trial , computer science , medicine , statistics , statistic , test (biology) , mathematics , statistical hypothesis testing , econometrics , paleontology , philosophy , biology , aesthetics
Summary In longitudinal studies comparing two treatments with a maximum follow‐up time there may be interest in examining treatment effects for intermediate follow‐up times. One motivation may be to identify the time period with greatest treatment difference when there is a non‐monotone treatment effect over time; another motivation may be to make the trial more efficient in terms of time to reach a decision on whether a new treatment is efficacious or not. Here, we test the composite null hypothesis of no difference at any follow‐up time versus the alternative that there is a difference at at least one follow‐up time. The methods are applicable when a few measurements are taken over time, such as in early longitudinal trials or in ancillary studies. Suppose the test statistic Z t kwill be used to test the hypothesis of no treatment effect at a fixed follow‐up time t k . In this context a common approach is to perform a pilot study on N 1 subjects, and evaluate the treatment effect at the fixed time points t 1 , … , t K and choose t * as the value of t k for which Z t kis maximized. Having chosen t * a second trial can be designed. In a setting with group sequential testing we consider several adaptive alternatives to this approach that treat the pilot and second trial as a seamless, combined entity and evaluate Type I error and power characteristics. The adaptive designs we consider typically have improved power over the common, separate trial approach.