Abstract

Background

Rifampicin-resistant tuberculosis (RR-TB) remains an important global health problem. Ideally, the complete drug-resistance profile guides individualized treatment for all RR-TB patients, but this is only practised in high-income countries. Implementation of whole genome sequencing (WGS) technologies into routine care in low and middle-income countries has not become a reality due to the expected implementation challenges, including translating WGS results into individualized treatment regimen composition.

Methods

This trial is a pragmatic, single-blinded, randomized controlled medical device trial of a WGS-guided automated treatment recommendation strategy for individualized treatment of RR-TB. Subjects are 18 years or older and diagnosed with pulmonary RR-TB in four of the five health districts of the Free State province in South Africa. Participants are randomized in a 1:1 ratio to either the intervention (a WGS-guided automated treatment recommendation strategy for individualized treatment of RR-TB) or control (RR-TB treatment according to the national South African guidelines). The primary effectiveness outcome is the bacteriological response to treatment measured as the rate of change in time to liquid culture positivity during the first 6 months of treatment. Secondary effectiveness outcomes include cure rate, relapse rate (recurrence of RR-TB disease) and TB free survival rate in the first 12 months following RR-TB treatment completion. Additional secondary outcomes of interest include safety, the feasibility of province-wide implementation of the strategy into routine care, and health economic assessment from a patient and health systems perspective.

Discussion

This trial will provide important real-life evidence regarding the feasibility, safety, cost, and effectiveness of a WGS-guided automated treatment recommendation strategy for individualized treatment of RR-TB. Given the pragmatic nature, the trial will assist policymakers in the decision-making regarding the integration of next-generation sequencing technologies into routine RR-TB care in high TB burden settings.

Trial registration

ClinicalTrials.gov NCT05017324. Registered on August 23, 2021.

Details

Title
Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment (SMARTT): a study protocol for a phase IV pragmatic randomized controlled patient management strategy trial
Author
Van Rie, Annelies 1   VIAFID ORCID Logo  ; De Vos, Elise 1 ; Costa, Emilyn 2 ; Verboven, Lennert 1 ; Ndebele, Felex 3 ; Heupink, Tim H. 1 ; Abrams, Steven 1 ; Maraba, Noriah; Makkan, Heeran; Beattie, Trevor; Sibeko, Zandile Rachel; Bohlela, S’thabiso; Segwaba, Pulane; Ogunbayo, Emmanuel Ayodeji; Mhlambi, Nomadlozi; Wells, Felicia; Rigouts, Leen; Maartens, Gary; Conradie, Francesca; Black, John; Potgieter, Sam; Fanampe, Boitumelo 4 ; Van der Spoel Van Dyk, Anneke 5 ; Charalambous, Salome 3 ; Churchyard, Gavin 3 ; Warren, Rob 2 

1  University of Antwerp, Family Medicine and Population Health, Faculty of Medicine and Health Sciences, Antwerp, Belgium (GRID:grid.5284.b) (ISNI:0000 0001 0790 3681) 
2  Stellenbosch University, South African Medical Research Council Centre for Tuberculosis Research, DST NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Cape Town, South Africa (GRID:grid.11956.3a) (ISNI:0000 0001 2214 904X) 
3  Aurum Institute, Johannesburg, South Africa (GRID:grid.414087.e) (ISNI:0000 0004 0635 7844) 
4  Free State Department of Health, Bloemfontein, South Africa (GRID:grid.5284.b) 
5  University of the Free State, Universitas Academic Laboratory, National Health Laboratory Service and Department of Medical Microbiology, Faculty of Health Sciences, Bloemfontein, South Africa (GRID:grid.412219.d) (ISNI:0000 0001 2284 638X) 
Pages
864
Publication year
2022
Publication date
Dec 2022
Publisher
Springer Nature B.V.
e-ISSN
17456215
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1186/s13063-022-06793-w
ProQuest document ID
2808563719
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.