Noninferiority testing with censoring when the event rate is low.

Kaplan-Meier estimates Tuberculosis exact tests loss to follow-up noninferiority

Journal

Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016

Informations de publication

Date de publication:
10 11 2022
Historique:
revised: 19 07 2022
received: 07 04 2021
accepted: 29 07 2022
pubmed: 23 8 2022
medline: 22 10 2022
entrez: 22 8 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 35995145
doi: 10.1002/sim.9556
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

5102-5112

Informations de copyright

© 2022 John Wiley & Sons Ltd.

Références

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Auteurs

Shannon K Gallagher (SK)

Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA.

Jing Wang (J)

Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.

Keith Lumbard (K)

Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.

Lori E Dodd (LE)

Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA.

Michael Proschan (M)

Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Rockville, Maryland, USA.

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