Discovery and validation of a personalized risk predictor for incident tuberculosis in low transmission settings

Rishi K. Gupta, Claire J. Calderwood, Alexei Yavlinsky, Maria Krutikov, Matteo Quartagno, Maximilian C. Aichelburg, Neus Altet, Roland Diel, Claudia C. Dobler, Jose Dominguez, Joseph S. Doyle, Connie Erkens, Steffen Geis, Pranabashis Haldar, Anja M. Hauri, Thomas Hermansen, James C. Johnston, Christoph Lange, Berit Lange, Frank van LethLaura Muñoz, Christine Roder, Kamila Romanowski, David Roth, Martina Sester, Rosa Sloot, Giovanni Sotgiu, Gerrit Woltmann, Takashi Yoshiyama, Jean Pierre Zellweger, Dominik Zenner, Robert W. Aldridge, Andrew Copas, Molebogeng X. Rangaka, Marc Lipman, Mahdad Noursadeghi, Ibrahim Abubakar*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1941-1949
Number of pages9
JournalNature Medicine
Issue number12
Publication statusPublished - Dec 2020
Externally publishedYes

Bibliographical note

Funding Information:
J.S.D.’s institution receives investigator-initiated research grants and consultancy income from Gilead Sciences, AbbVie, Bristol Myers Squibb and Merck. The Burnet Institute receives funding from the Victorian Government Operational Infrastructure Fund. C.L. reports honoraria from Chiesi, Gilead, Insmed, Janssen, Lucane, Novartis, Oxoid, Berlin Chemie (for participation at sponsored symposia) and Oxford Immunotec (to attend a scientific advisory board meeting), all outside of the submitted work. M.S. reports receipt of test kits free of charge from Qiagen and from Oxford Immunotec for investigator-initiated research projects. I.A. reports receiving test kits free of charge from Qiagen for an investigator-initiated research project25.

Funding Information:
This study was funded by the National Institute for Health Research (NIHR) (DRF-2018–11-ST2-004 to R.K.G. and SRF-2011-04-001 and NF-SI-0616-10037 to I.A.), the Wellcome Trust (207511/Z/17/Z to M.N.) and NIHR biomedical research funding to University College London Hospitals. C.L. is funded by the German Center for Infection Research. J.S.D. receives salary support from the National Health and Medical Research Council (Australia). This paper presents independent research supported by the NIHR. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR or the Department of Health and Social Care. The study funders had no role in the conceptualization, design, data collection, analysis, decision to publish or preparation of the manuscript. The authors would like to thank all of the research teams involved in the primary studies that contributed data for this analysis.

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.


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