Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment Trial
SMARTT
3 other identifiers
interventional
248
1 country
1
Brief Summary
The primary aim of this pragmatic trial is to determine the effectiveness of a Whole Genome Sequencing (WGS) Drug Sensitivity Testing (DST) strategy to guide individualised treatment of rifampicin resistant tuberculosis (RR-TB) patients. The primary objective is to determine the effectiveness of this WGS DST strategy in patients diagnosed with RR-TB. We will additionally perform an exploratory health economics evaluation of both arms, and will determine the feasibility of the WGS DST strategy.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Sep 2021
Longer than P75 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 22, 2021
CompletedFirst Posted
Study publicly available on registry
August 23, 2021
CompletedStudy Start
First participant enrolled
September 21, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
January 1, 2025
CompletedOctober 15, 2021
October 1, 2021
1.2 years
April 22, 2021
October 14, 2021
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
The Effectiveness of a WGS DST strategy for individualisation of RR-TB treatment
The effectiveness will be determined by the rate of change in time to positivity (TTP) over 6 months in the Mycobacterial Growth Indicator Tuber (MGIT) system \[time from: Day 0 to Week 24\]. The effectiveness of the WGS DST strategy will be determined by the rate of change in TTP in liquid media MGIT cultures of sputum samples collected during the first 6 months of treatment. The TTP will be used to determine the change in mycobacterial load using a non-linear mixed effect time-to-event model that provides a longitudinal representation of mycobacterial load (measured as TTP in MGIT) at weeks 2, 3, 4, 5, 6, 7, 8, 12, 16, 20 and 24
Day 0 to month 6 (6 months)
Secondary Outcomes (2)
Health economic evaluation of a WGS DST strategy for individualization of RR-TB treatment
Start of treatment to end of treatment (which may vary from 6 months to over 11 months)
Impact of WGS strategy for individualisation of RR-TB treatment on Health related Quality of Life (HRQOL)
Start of treatment to end of treatment (which may vary from 6 months to over 11 months)
Study Arms (2)
WGS DST strategy
EXPERIMENTALWGS DST strategy for diagnosing the TB drug resistance profile and an individualised RR-TB treatment recommendation
Standard of Care
NO INTERVENTIONStandard of care diagnosis of the drug resistance profile and individualised treatment
Interventions
WGS DST strategy for diagnosing the TB drug resistance profile and an algorithm-determined individualised RR-TB treatment recommendation
Eligibility Criteria
You may qualify if:
- Diagnosed with RR-TB
- Diagnosed with pulmonary TB (PTB) or PTB plus extra-pulmonary TB (EPTB)
- ≥18 years of age
- Able to sign informed consent
- Not on TB treatment at time of enrolment
You may not qualify if:
- Patients diagnosed EPTB without pulmonary involvement
- Patients with TB Meningitis or TB of the bone.
- Has any condition that, in the opinion of the investigator or physician, would preclude provision of informed consent, make participation in the study unsafe, complicate interpretation of study outcome data, interfere with achieving the study objectives or compromise patient safety.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Universiteit Antwerpenlead
- Aurum Institutecollaborator
- University of Stellenboschcollaborator
- University of the Free Statecollaborator
- Free State Department of Healthcollaborator
Study Sites (1)
Free State Department of Health Clinics
Bloemfontein, Free State, South Africa
Related Publications (1)
Van Rie A, De Vos E, Costa E, Verboven L, Ndebele F, Heupink TH, Abrams S; SMARTT team; Fanampe B, Van der Spoel Van Dyk A, Charalambous S, Churchyard G, Warren R. Sequencing Mycobacteria and Algorithm-determined Resistant Tuberculosis Treatment (SMARTT): a study protocol for a phase IV pragmatic randomized controlled patient management strategy trial. Trials. 2022 Oct 8;23(1):864. doi: 10.1186/s13063-022-06793-w.
PMID: 36209235DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Gavin Churchyard, PhD, MD
Aurum Institute
- PRINCIPAL INVESTIGATOR
Annelies Van Rie, PhD, MD
Universiteit Antwerpen
- PRINCIPAL INVESTIGATOR
Rob M Warren, PhD
Stellenbosch University, MRC
- PRINCIPAL INVESTIGATOR
Salome Charalambous, PhD
Aurum Institute
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Purpose
- HEALTH SERVICES RESEARCH
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
April 22, 2021
First Posted
August 23, 2021
Study Start
September 21, 2021
Primary Completion
December 1, 2022
Study Completion
January 1, 2025
Last Updated
October 15, 2021
Record last verified: 2021-10
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ICF, CSR
- Time Frame
- From publication of the results of the primary up to 5 years thereafter
- Access Criteria
- WGS: available on European Nucleotide Archive (ENA) Other data: access will be provided to researchers who have obtained Institutional Review Board (IRB) approval for analyses
The analysable individual patient data (IPD) will be made available, including WGS data (to be published on the European Nucleotide Archive (ENA)) and de-identified clinical and demographic IPD. This ensures an adit trial for summary results reporting, enables re-analyses of trial data and the possibility for combining the data with others for novel investigations.