Discovery and validation of a personalized risk predictor for incident tuberculosis in low transmission settings. Gupta, R. K., Calderwood, C. J., Yavlinsky, A., Krutikov, M., Quartagno, M., Aichelburg, M. C., Altet, N., Diel, R., Dobler, C. C., Dominguez, J., Doyle, J. S., Erkens, C., Geis, S., Haldar, P., Hauri, A. M., Hermansen, T., Johnston, J. C., Lange, C., Lange, B., van Leth, F., Muñoz, L., Roder, C., Romanowski, K., Roth, D., Sester, M., Sloot, R., Sotgiu, G., Woltmann, G., Yoshiyama, T., Zellweger, J., Zenner, D., Aldridge, R. W., Copas, A., Rangaka, M. X., Lipman, M., Noursadeghi, M., & Abubakar, I. Nature Medicine, 26:1941–1949, Nature Publishing Group, oct, 2020.
Discovery and validation of a personalized risk predictor for incident tuberculosis in low transmission settings [link]Paper  doi  abstract   bibtex   
Globally, TB accounts for the greatest number of deaths from a single pathogen, with an estimated 1.5 million deaths and 10 million incident cases in 2018 1. The World Health Organization's End TB Strategy ambitiously aims for a 95% reduction in TB mortality and a 90% reduction in TB incidence by 2035 2. As part of this strategy, the priority for low transmission settings is to achieve pre-elimination (annual incidence of \textless1 per 100,000) by 2035 2. Preventative antimicrobial treatment for LTBI is considered critical for achieving this objective 2,3. In the absence of an assay to detect viable M. tuberculosis bacteria, LTBI is currently clinically defined as evidence of T cell memory to M. tuberculosis, in the absence of concurrent disease and any previous treatment 4,5. Individuals with LTBI are generally considered to have a lifetime TB risk ranging from 5% to 10% 4 , which is reduced by 65-80% with preventative treatment 6. The positive predictive value (PPV) for TB using the current definition of LTBI is less than 5% over a 2-year period among risk groups, such as adult TB contacts 7-9. This might lead to a large burden of unnecessary preventative treatment, with associated risks of drug toxicity to patients and excess economic costs to health services. The low PPV might also undermine the cascade of care, including uptake of preventative treatment among individuals in target groups, who perceive their individual risk of developing TB to be low 10,11. In fact, the risk of TB among individuals with LTBI is highly variable between study populations, with incidence rates ranging from 0.3 to 84.5 per 1,000 person-years of follow-up 7,12. Thus, quoting the 5-10% lifetime estimate is likely to be inaccurate for many people. Improved risk stratification is, therefore, essential to enable precise delivery of preventative treatment to those most likely to benefit 5,13. Multiple studies have shown that the magnitude of the T cell response to M. tuberculosis is associated with incident TB risk, raising hope that quantitative tuberculin skin test (TST) or interferon gamma release assay (IGRA) results might improve pre-dictive ability 14,15. However, implementing higher diagnostic thresholds alone does not improve prediction on a population level owing to a marked loss of sensitivity with this approach 16. In this study, we first sought to characterize the population risk of TB among people tested for LTBI using an individual participant data meta-analysis (IPD-MA). To study progression from LTBI to TB disease more accurately, we focused on settings with low transmission (defined as annual incidence ≤20 per 100,000 persons), where there is a minimal risk of reinfection during follow-up. The risk of tuberculosis (TB) is variable among individuals with latent Mycobacterium tuberculosis infection (LTBI), but validated estimates of personalized risk are lacking. In pooled data from 18 systematically identified cohort studies from 20 countries, including 80,468 individuals tested for LTBI, 5-year cumulative incident TB risk among people with untreated LTBI was 15.6% (95% confidence interval (CI), 8.0-29.2%) among child contacts, 4.8% (95% CI, 3.0-7.7%) among adult contacts, 5.0% (95% CI, 1.6-14.5%) among migrants and 4.8% (95% CI, 1.5-14.3%) among immunocompromised groups. We confirmed highly variable estimates within risk groups, necessitating an individualized approach to risk stratification. Therefore, we developed a personalized risk predictor for incident TB (PERISKOPE-TB) that combines a quantitative measure of T cell sensitization and clinical covariates. Internal-external cross-validation of the model demonstrated a random effects meta-analysis C-statistic of 0.88 (95% CI, 0.82-0.93) for incident TB. In decision curve analysis, the model demonstrated clinical utility for targeting preventative treatment, compared to treating all, or no, people with LTBI. We challenge the current crude approach to TB risk estimation among people with LTBI in favor of our evidence-based and patient-centered method, in settings aiming for pre-elimination worldwide.
@article{Gupta2020,
abstract = {Globally, TB accounts for the greatest number of deaths from a single pathogen, with an estimated 1.5 million deaths and 10 million incident cases in 2018 1. The World Health Organization's End TB Strategy ambitiously aims for a 95{\%} reduction in TB mortality and a 90{\%} reduction in TB incidence by 2035 2. As part of this strategy, the priority for low transmission settings is to achieve pre-elimination (annual incidence of {\textless}1 per 100,000) by 2035 2. Preventative antimicrobial treatment for LTBI is considered critical for achieving this objective 2,3. In the absence of an assay to detect viable M. tuberculosis bacteria, LTBI is currently clinically defined as evidence of T cell memory to M. tuberculosis, in the absence of concurrent disease and any previous treatment 4,5. Individuals with LTBI are generally considered to have a lifetime TB risk ranging from 5{\%} to 10{\%} 4 , which is reduced by 65-80{\%} with preventative treatment 6. The positive predictive value (PPV) for TB using the current definition of LTBI is less than 5{\%} over a 2-year period among risk groups, such as adult TB contacts 7-9. This might lead to a large burden of unnecessary preventative treatment, with associated risks of drug toxicity to patients and excess economic costs to health services. The low PPV might also undermine the cascade of care, including uptake of preventative treatment among individuals in target groups, who perceive their individual risk of developing TB to be low 10,11. In fact, the risk of TB among individuals with LTBI is highly variable between study populations, with incidence rates ranging from 0.3 to 84.5 per 1,000 person-years of follow-up 7,12. Thus, quoting the 5-10{\%} lifetime estimate is likely to be inaccurate for many people. Improved risk stratification is, therefore, essential to enable precise delivery of preventative treatment to those most likely to benefit 5,13. Multiple studies have shown that the magnitude of the T cell response to M. tuberculosis is associated with incident TB risk, raising hope that quantitative tuberculin skin test (TST) or interferon gamma release assay (IGRA) results might improve pre-dictive ability 14,15. However, implementing higher diagnostic thresholds alone does not improve prediction on a population level owing to a marked loss of sensitivity with this approach 16. In this study, we first sought to characterize the population risk of TB among people tested for LTBI using an individual participant data meta-analysis (IPD-MA). To study progression from LTBI to TB disease more accurately, we focused on settings with low transmission (defined as annual incidence ≤20 per 100,000 persons), where there is a minimal risk of reinfection during follow-up. The risk of tuberculosis (TB) is variable among individuals with latent Mycobacterium tuberculosis infection (LTBI), but validated estimates of personalized risk are lacking. In pooled data from 18 systematically identified cohort studies from 20 countries, including 80,468 individuals tested for LTBI, 5-year cumulative incident TB risk among people with untreated LTBI was 15.6{\%} (95{\%} confidence interval (CI), 8.0-29.2{\%}) among child contacts, 4.8{\%} (95{\%} CI, 3.0-7.7{\%}) among adult contacts, 5.0{\%} (95{\%} CI, 1.6-14.5{\%}) among migrants and 4.8{\%} (95{\%} CI, 1.5-14.3{\%}) among immunocompromised groups. We confirmed highly variable estimates within risk groups, necessitating an individualized approach to risk stratification. Therefore, we developed a personalized risk predictor for incident TB (PERISKOPE-TB) that combines a quantitative measure of T cell sensitization and clinical covariates. Internal-external cross-validation of the model demonstrated a random effects meta-analysis C-statistic of 0.88 (95{\%} CI, 0.82-0.93) for incident TB. In decision curve analysis, the model demonstrated clinical utility for targeting preventative treatment, compared to treating all, or no, people with LTBI. We challenge the current crude approach to TB risk estimation among people with LTBI in favor of our evidence-based and patient-centered method, in settings aiming for pre-elimination worldwide.},
author = {Gupta, Rishi K. and Calderwood, Claire J. and Yavlinsky, Alexei and Krutikov, Maria and Quartagno, Matteo and Aichelburg, Maximilian C. and Altet, Neus and Diel, Roland and Dobler, Claudia C. and Dominguez, Jose and Doyle, Joseph S. and Erkens, Connie and Geis, Steffen and Haldar, Pranabashis and Hauri, Anja M. and Hermansen, Thomas and Johnston, James C. and Lange, Christoph and Lange, Berit and van Leth, Frank and Mu{\~{n}}oz, Laura and Roder, Christine and Romanowski, Kamila and Roth, David and Sester, Martina and Sloot, Rosa and Sotgiu, Giovanni and Woltmann, Gerrit and Yoshiyama, Takashi and Zellweger, Jean-Pierre and Zenner, Dominik and Aldridge, Robert W. and Copas, Andrew and Rangaka, Molebogeng X. and Lipman, Marc and Noursadeghi, Mahdad and Abubakar, Ibrahim},
doi = {10.1038/s41591-020-1076-0},
file = {:C$\backslash$:/Users/01462563/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Gupta et al. - 2020 - Discovery and validation of a personalized risk predictor for incident tuberculosis in low transmission settings.pdf:pdf},
issn = {1078-8956},
journal = {Nature Medicine},
keywords = {Biomarkers,Diseases,Medical research,Risk factors,fund{\_}not{\_}ack,original},
mendeley-tags = {fund{\_}not{\_}ack,original},
month = {oct},
pages = {1941--1949},
pmid = {33077958},
publisher = {Nature Publishing Group},
title = {{Discovery and validation of a personalized risk predictor for incident tuberculosis in low transmission settings}},
url = {http://www.nature.com/articles/s41591-020-1076-0},
volume = {26},
year = {2020}
}
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