Every year, over 4,000 people in England develop tuberculosis (TB), and doctors must treat 20 to 100 people with preventative antibiotics to stop a single case. The problem is that current tests for latent TB infection cannot reliably predict who will actually become sick, exposing many people to unnecessary antibiotics and limiting the uptake of prevention programmes. This project aims to change that by testing whether a new blood-based RNA biomarker can identify people at highest risk of progressing to active TB within six months. If successful, the approach would allow clinicians to target preventative treatment only to those who truly need it, reducing unnecessary drug exposure and making TB prevention efforts far more efficient. The research will also assess how willing patients and healthcare workers are to accept or recommend treatment based on different levels of future TB risk, and will run a small feasibility trial to see whether this biomarker-guided strategy works in practice. The ultimate goal is to design a larger definitive trial that could transform TB prevention in the UK.
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Background: There are over 4,000 tuberculosis (TB) cases in England annually. Scale-up of preventative TB treatment represents a cornerstone of the NHS TB action plan. Current tests for latent TB infection (including interferon-gamma release assays; IGRAs) have limited positive predictive value for future TB disease. Hence, we need to treat between 20-100 people with preventative antibiotics to prevent one incident TB case. This results in unnecessary antibiotic exposure and limits treatment uptake, undermining TB prevention efforts. Emerging 'incipient' TB tests aim to detect early stages in the pathogenesis of disease, before symptoms commence. Blood RNA biomarkers can detect incipient TB with high accuracy over a six-month interval and may facilitate more precise targeting of preventative antibiotics towards people at highest risk of progression to symptomatic disease. Aim: To enable more precise use of preventative antimicrobials for TB among contacts and migrants from high transmission countries, by developing the platform for a randomised-controlled trial (RCT) of incipient TB biomarker-stratified treatment. Objectives: To define the optimal incipient TB testing approach. To refine the trial outcome by quantifying the trade-off between incident TB risk and preventative treatment acceptance. To conduct a feasibility RCT. To estimate the cost-effectiveness of the intervention in a preliminary health economic analysis. Methods: (a) A systematic review of the diagnostic accuracy of candidate incipient TB tests. (b) A nested case-control study in biobanked samples from a cohort of 4,400 TB contacts. I will assess the diagnostic accuracy of seven RNA biomarkers, measured using the Nanostring platform, for incipient TB stratified by interval from testing to disease. I will compare the performance of a near-patient cartridge-based RNA assay to the Nanostring reference standard. A discrete choice experiment among patients (n=200) and healthcare workers (n=200) to assess the association between future TB risk and acceptance (or recommendation) of preventative treatment. These results will be used to inform a proposed weighted composite 'net harm' trial outcome incorporating incident TB risk and preventative treatment exposure. A feasibility RCT of IGRA-positive recent TB contacts or migrants (n=100) who do not have baseline evidence of TB. I will randomise to standard care (offering preventative treatment to all) or the intervention arm (using six-monthly incipient TB testing to guide preventative treatment), with 12 months' follow-up for all. Outcomes will include: feasibility of trial recruitment; feasibility and acceptability of the intervention; and the proportion commencing preventative treatment in each arm. Adaptation of an existing health economic dynamic-transmission model by incorporating a decision-tree reflecting the intervention, parameterised from Objectives 1-3. This will inform a preliminary analysis of intervention cost-effectiveness and can subsequently be updated following a definitive trial. Impact: This work will enable refinement of the trial design and will inform a decision on whether to proceed to a definitive trial. The intervention has the potential to transform TB prevention by reducing the burden of unnecessary preventative antibiotics. I will develop skills in clinical trials, discrete choice experiments, health economics and leadership, to continue my path towards being a research leader in respiratory infection.
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