Noninferiority testing with censoring when the event rate is low

Author:

Gallagher, Shannon K [ORCID]

Wang,Jing

Lumbard, Keith

Dodd, Lori E

Proschan, Michael [ORCID]
Author Address

Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA., Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.,

Abstract:

The PREDICT TB trial tests noninferiority of an abbreviated treatment regimen (arm A) vs a conventional treatment regimen (arm C). Treatment trials of drug-susceptible tuberculosis are expected to have low event rates (ie, relapse probabilities around 3-5%). We examine the question of what is the "best" way to test for noninferiority in a setting with low event rates. In a series of simulations supported by theoretical arguments, we examine operating characteristics of five tests, including normal approximation, exact, and simulation-based tests. Two of these tests are constructed from Kaplan-Meier based-estimators, which account for variable follow-up time (and those lost to follow-up). We evaluate the effect of loss to follow-up via simulations. We also examine the results of the five tests on a data set similar to PREDICT TB, the REMoxTB trial. We find that the normal approximation tests perform well, albeit with small type I error rate inflation. We also find that the Kaplan-Meier methods generally have larger power than the other tests, especially when there is between 10-30% loss to follow-up. © 2022 John Wiley & Sons Ltd.

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