ArticleTrials2022
Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment (SMARTT): a study protocol for a phase IV pragmatic randomized controlled patient management strategy trial.
Article in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05017324 (Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment Trial), which is not on this map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment Trial
Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- A tiled amplicon protocol for culture-free whole-genome sequencing ofJournal of clinical microbiology · 2026Article
- Article
- Targeted and whole-genome sequencing for drug resistance and genetic relatedness inference of rifampicin-resistantERJ open research · 2026Article
- Article
- Improving the efficiency of drug resistant tuberculosis treatment trials: a time-to-event alternative marker for bacteriological response and adaptive minimization for randomization.BMC medical research methodology · 2025Article
- Pretomanid for the treatment of drug resistant pulmonary tuberculosis: a comprehensive review.Archives of microbiology · 2025Review
- Reimagining Tuberculosis Control in the Era of Genomics: The Case for Global Investment inPathogens (Basel, Switzerland) · 2025Review
- Collaborative learning in the digital age: empowering tuberculosis researchers through virtual training.Journal of microbiology & biology education · 2024Article
- Drug-resistant tuberculosis: a persistent global health concern.Nature reviews. Microbiology · 2024Review
- A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis.PloS one · 2024Article
- Article
- The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples.PLoS computational biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundRifampicin-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.
methodsThis 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 registrationClinicalTrials.gov NCT05017324. Registered on August 23, 2021.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.