Sub-studies

• ASSURE

  Assessing Sterilizing Cure After Anti-TB Treatment (ASSURE)

  Diagnostic markers that can accurately monitor and provide prognostic information about a patient’s health status throughout treatment are paramount to reducing the global TB burden. Evidence suggests that sterilization is not achieved in a portion of cured patients at the end of anti-TB treatment. There remains a fraction of viable Mtb, undetectable by current diagnostic tests, which may represent a risk for relapse and/or transmission.

  The ASSURE sub-study sought to assess which portion of patients still retained live Mtb at the end of treatment using novel tools for detecting Mtb that may be present in a dormant state. To this end, we aimed to quickly identify patients at risk of relapse and/or requiring extended treatment. This study also provided functional characterization of Mtb in this altered physiological state.

  Start/end date
  

  21 June 2017 – 31 January 2022

  Funding
  

  • NIH International Collaboration in Infectious Disease Research (ICIDR)
  • PredictTB co-funding project funded by NIH/BMGF

  Study lead
  

  • Caroline Beltran, Stellenbosch University, beltran@sun.ac.za
  • Immunology Research Group

• Evaluate4mTB

  Evaluating the response to 4 and 6 month treatment of pulmonary tuberculosis by 18F-FDG PET/CT lung imaging (Evaluate4mTB)

  Evaluate4mTB validated and optimised the functional and anatomical characteristics previously identified by 18F-FDG PET/CT scans on patients with PTB. It was complimentary to the PredictTB study, which focused on imaging markers at diagnosis and during early treatment.

  The sub-study focused on scans at 16 and 24 weeks of treatment. We performed qualitative and quantitative evaluations of PET/CT scans after 4 and 6 months of TB treatment, including measuring the changes from baseline. We compared the scan metrics between outcome groups and treatment arms. We used this information to provide insight into the dynamics of MTB versus host interaction, serve as a prognostic indicator and facilitate the discovery of biomarkers to monitor and understand treatment response during 16 and 24-week treatment courses.

  The sub-study also included working with biomedical engineers to fully automate scan quantitation. Scans at the end of treatment should be more accurate than early treatment scans since more treatment response variables have taken effect and provide a better understanding of lung pathology after shortened treatment. This should facilitate the discovery of biomarkers to evaluate the end-of-treatment TB infection status in the lung, regardless of treatment duration. In turn, this would be a significant step towards easy and affordable tests to allow individualised treatment duration.

  Preliminary analysis is underway and main findings should be shared as publications within 12 months after the end of the project.

  Start/end date
  

  1 April 2018 – 31 March 2022

  Funding
  

  • This project was part of the EDCTP2 programme supported by the European Union (grant number TMA-2016-CDF-1576 ).

  Study lead
  

  • Stephanus Malherbe, Stellenbosch University

• MERM

  The Medication Event Reminder-Monitor (MERM) is used as a tool to aid patient treatment adherence, it reminds the patient to take their the daily medication so essential to their cure. MERM is a box with an alarm that rings at the patient’s chosen time, the box opening is electronically captured as a record of the patient accessing their treatment packets. This recording is then viewed by the pharmacist at each visit to compare to the traditional pill counting as a means of monitoring adherence.

  Each participant enrolled in the PredictTB study was supplied with a Medication Event Reminder-Monitor (MERM) box, a device that stores the participants’ pills and reminds them to take their medication on time.

  The sub-study assessed MERM boxes’ effect on participants’ compliance and drug accountability. This was done by comparing the data extracted from the MERM device of how many times the MERM box was opened with the manual pill count by each clinical site. In addition to the factual data, the study also assessed both the participants’ and the clinical staff’s perceptions of the MERM box with questionnaires. The participants were asked to complete two questionnaires, one at the start and one at the end of treatment, to evaluate if their perception of the MERM box changed over time.

  Start/end date
  

  November 2017 – January 2022

  Funding
  

  • PredictTB was supported by The Foundation for the National Institutes of Health (FNIH) through the Bill & Melinda Gates Foundation, European & Developing Countries Clinical Trials Partnership (EDCTP), Grand Challenges China, and NIH’s International Collaborations in Infectious Disease Research (ICIDR) Program in collaboration with the Consortium for TB Biomarkers and the Regional Prospective Observational Research in Tuberculosis in the Republic of South Africa (RePORT South Africa).

  Study lead
  

  • Kim Narunsky, Kim.Narunsky@uct.ac.za, +27 214066605 / +27 822977745

• PK

  PK Substudy for Sub-Breakpoint Minimum Inhibitory Concentrations (MIC) Comparison

  Minimum inhibitory concentrations (MIC) are used in standard drug susceptibility testing assays to determine at what drug concentrations a “resistant” bacterium will grow in culture.

  Previous studies have shown that just as high-level MIC resistance correlates with treatment outcome, low-level or sub-breakpoint MIC resistance also correlates with treatment outcome. Additionally, TB patients are known to have widely variable serum PK values and these differences appear to affect treatment outcomes. Because a given patient’s serum drug concentration would clearly affect the clinical interpretation of a given MIC result, a model incorporating both parameters may predict outcomes better than either one alone.

  To test the sub-breakpoint MIC concept, we have identified those at the highest risk of relapse to see if there were differences in sub-breakpoint MIC and/or PK/sub-breakpoint MIC at baseline, compared with those who did not relapse.

  Start/end date
  

  December 2017 – December 2022

  Funding
  

  PredictTB was supported by The Foundation for the National Institutes of Health (FNIH) through the Bill & Melinda Gates Foundation, European & Developing Countries Clinical Trials Partnership (EDCTP), Grand Challenges China, China Ministry of Science and Technology (MOST), and NIH’s International Collaborations in Infectious Disease Research (ICIDR) Program in collaboration with the Consortium for TB Biomarkers and the Regional Prospective Observational Research in Tuberculosis in the Republic of South Africa (RePORT South Africa).

  Study lead
  

  • Ray Chen, MD, (301) 443-5816, RChen@niaid.nih.gov
  • Laura Via, PhD, (301) 451-9554, lvia@niaid.nih.gov