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Serra, Alessandra ; Mozgunov, Pavel ; Davies, Geraint ; Jaki, Thomas

Determining the minimum duration of treatment in tuberculosis: An order restricted non‐inferiority trial design

Serra, Alessandra , Mozgunov, Pavel, Davies, Geraint and Jaki, Thomas (2023) Determining the minimum duration of treatment in tuberculosis: An order restricted non‐inferiority trial design. Pharmaceutical Statistics 22 (5), pp. 938-962.

Date of publication of this fulltext: 18 Mar 2025 10:05
Article
DOI to cite this document: 10.5283/epub.75773


Abstract

Tuberculosis (TB) is one of the biggest killers among infectious diseases worldwide. Together with the identification of drugs that can provide benefits to patients, the challenge in TB is also the optimisation of the duration of these treatments. While conventional duration of treatment in TB is 6 months, there is evidence that shorter durations might be as effective but could be associated with ...

Tuberculosis (TB) is one of the biggest killers among infectious diseases worldwide. Together with the identification of drugs that can provide benefits to patients, the challenge in TB is also the optimisation of the duration of these treatments. While conventional duration of treatment in TB is 6 months, there is evidence that shorter durations might be as effective but could be associated with fewer side effects and may be associated with better adherence. Based on a recent proposal of an adaptive order-restricted superiority design that employs the ordering assumptions within various duration of the same drug, we propose a non-inferiority (typically used in TB trials) adaptive design that effectively uses the order assumption. Together with the general construction of the hypothesis testing and expression for type I and type II errors, we focus on how the novel design was proposed for a TB trial concept. We consider a number of practical aspects such as choice of the design parameters, randomisation ratios, and timings of the interim analyses, and how these were discussed with the clinical team.



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Details

Item typeArticle
Journal or Publication TitlePharmaceutical Statistics
Publisher:Wiley
Place of Publication:HOBOKEN
Volume:22
Number of Issue or Book Chapter:5
Page Range:pp. 938-962
Date6 July 2023
InstitutionsInformatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki)
Identification Number
ValueType
10.1002/pst.2320DOI
KeywordsMOXIFLOXACIN; RIFAPENTINE; REGIMENS; MULTIARM; ISSUES; adaptive designs; infectious diseases; multi-arm multi-stage; non-inferiority; order restriction
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
600 Technology > 615 Pharmacy
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgPartially
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-757737
Item ID75773

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