Gupta, Rishi Kumar;
(2021)
Precision targeting of preventative therapy for tuberculosis.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Background: Scale-up of preventative treatment for tuberculosis (TB) represents a cornerstone of global control efforts. I examined a range of approaches to enable more precise targeting of preventative treatment to people at highest risk. Methods: I evaluated whether prognostic tests for TB (tuberculin skin test (TST), QuantiFERON Gold-in-tube (QFT-GIT) and T-SPOT.TB) may be optimised by implementing higher thresholds, or by a newer generation assay (QuantiFERON-TB Gold Plus; QFT-Plus). Next, I conducted a systematic review and individual participant data meta-analysis (IPD-MA) to examine TB risk among people tested for latent infection (LTBI) in settings with low TB transmission and to develop a multivariable prognostic model for incident TB. Finally, I performed a systematic review and IPD-MA of whole-blood RNA sequencing data to evaluate blood transcriptomic signatures as next-generation biomarkers. Results: In a UK cohort of 9,610 adults, higher TST, QFT-GIT and T-SPOT.TB results were associated with increased incident TB risk. Implementing higher cut-offs led to a marginal improvement in positive predictive value, but at the cost of a marked loss in sensitivity. The newer generation QFT-Plus had similar predictive ability. In a pooled dataset of >80,000 participants from 18 cohort studies, TB risk was heterogeneous among people with LTBI, even after stratification by indication for testing. I developed and validated a multivariable prognostic model, which incorporates quantitative LTBI test results and clinical covariates, and demonstrated strong potential for clinical utility to inform provision of preventative treatment. Among 1,126 whole-blood RNA sequencing samples, eight transcriptomic signatures (comprising 1-25 transcripts) performed similarly for predicting incident TB, but only met global accuracy benchmarks over a 3-6 month time-horizon. Conclusions: Personalised risk estimates integrating quantitative LTBI test results and clinical covariates may facilitate more precise targeting of preventative treatment. Blood transcriptomic biomarkers show promise, but only represent short-term TB risk. Future research priorities are highlighted.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Precision targeting of preventative therapy for tuberculosis |
| Event: | UCL (University College London) |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10129204 |
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