Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
[Preprint]. 2024 Apr 24:2024.04.23.24305228.
doi: 10.1101/2024.04.23.24305228.

C-reactive protein-based tuberculosis triage testing: a multi-country diagnostic accuracy study

Brigitta Derendinger  1 , Tessa K Mochizuki  2   3 , Danaida Marcelo  4 , Deepa Shankar  5 , Wilson Mangeni  6 , Hanh Nguyen  7 , Seda Yerikaya  8 , William Worodria  6 , Charles Yu  4 , Nhung Viet Nguyen  7 , Devasahayam Jesudas Christopher  5 , Grant Theron  1 , Patrick P J Phillips  2   3 , Payam Nahid  2   3 , Claudia M Denkinger  8 , Adithya Cattamanchi  3   9 , Christina Yoon  2   3
Affiliations

C-reactive protein-based tuberculosis triage testing: a multi-country diagnostic accuracy study

Brigitta Derendinger et al. medRxiv. .

Update in

Abstract

Rationale: C-reactive protein (CRP)-based tuberculosis (TB) screening is recommended for people with HIV (PWH). However, its performance among people without HIV and in diverse settings is unknown.

Objectives: In a multi-country study, we aimed to determine whether CRP meets the minimum accuracy targets (sensitivity ≥90%, specificity ≥70%) for an effective TB triage test.

Methods/measurements: Consecutive outpatient adults with cough ≥2 weeks from five TB endemic countries in Africa and Asia had baseline blood collected for point-of-care CRP testing and HIV and diabetes screening. Sputum samples were collected for Xpert MTB/RIF Ultra (Xpert) testing and culture. CRP sensitivity and specificity (5 mg/L cut-point) was determined in reference to sputum test results and compared by country, sex, and HIV and diabetes status. Variables affecting CRP performance were identified using a multivariate receiver operating characteristic (ROC) regression model.

Results: Among 2904 participants, of whom 613 (21%) had microbiologically-confirmed TB, CRP sensitivity was 84% (95% CI: 81-87%) and specificity was 61% (95% CI: 59-63%). CRP accuracy varied geographically, with higher sensitivity in African countries (≥91%) than Asian countries (64-82%). Sensitivity was higher among men than women (87% vs. 79%, difference +8%, 95% CI: 1-15%) and specificity was higher among people without HIV than PWH (64% vs. 45%, difference +19%, 95% CI: 13-25%). ROC regression identified country and measures of TB disease severity as predictors of CRP performance.

Conclusions: Overall, CRP did not achieve the minimum accuracy targets and its performance varied by setting and in some sub-groups, likely reflecting population differences in mycobacterial load.

Keywords: C-reactive protein; Tuberculosis; diagnosis; screening; triage.

PubMed Disclaimer

Conflict of interest statement

William Worodria, Charles Yu, Nhung Viet Nguyen, Devasahayam Jesudas Christopher, Grant Theron, Patrick P.J. Philips, Payam Nahid, Claudia M. Denkinger, Adithya Cattamanchi, and Christina Yoon declare support from the underlying R2D2 TB Network to their institutions from the National Institute of Allergy and Infectious Diseases (NIAID) of the US National Institutes of Health (NIH). CMD also declares research grants from the German Ministry of Education and Research, German Alliance for Global Health Research, US Agency for International Development, FIND, German Center for Infection Research, and WHO. AC declares research funding to his institution from NIH, Bill and Melinda Gates Foundation, and Global Health Labs. CY declares research grants from NIH/NIAID and NIH/National Heart Lung Blood Institute, with CRP test strips and analyzers donated by Boditech Med Inc, South Korea. CY serves as a a Scientific Advisory Board member for an EDCTP-funded cluster randomized trial. All other authors declare no competing interests. CRP test strips and analyzer were donated by Boditech Med Inc, South Korea.

Figures

Figure 1.
Figure 1.
Participant flow chart. Abbreviations: TB ‒ tuberculosis, CRP ‒ C-reactive protein, Xpert ‒ Xpert MTB/RIF Ultra. * CRP testing was paused in Uganda August 15-December 31, 2022 per protocol, as a result those participants were excluded from this analysis. † CRP testing was not done for 2 participants in Vietnam, 11 in Uganda, 32 in South Africa, and 60 in India.
Figure 2.
Figure 2.
Receiver operating characteristic analysis for CRP in reference to MRS, overall study population and by country. Abbreviations: CRP ‒ C-reactive protein, MRS ‒ microbiological reference standard, AUC ‒ area under the curve. Comparison of AUCs by region using DeLong’s (African countries: 0.82 vs. Asian countries: 0.79, p=0.06); comparison between the AUCs for Uganda and the Philippines (0.76, p=0.09) and between Uganda and Vietnam (0.83 vs. 0.77, p=0.03).
Figure 3.
Figure 3.
Receiver operating characteristic analysis for CRP in reference to MRS, overall study population and by key sub-groups. Abbreviations CRP – C-reactive protein, MRS ‒ microbiological reference standard, AUC ‒ area under the curve, PWH ‒ people living with HIV, PWD – people living with diabetes.
See this image and copyright information in PMC

References

    1. Global Tuberculosis Report 2023. [Internet]. [cited 2024 Feb 2]. Available from: https://www.who.int/teams/global-tuberculosis-programme/tb-reports/globa...
    1. WHO consolidated guidelines on tuberculosis: module 3: diagnosis: rapid diagnostics for tuberculosis detection, 2021. update [Internet]. [cited 2022 Nov 21]. Available from: https://www.who.int/publications-detail-redirect/9789240029415 - PubMed
    1. Hoog AH van’t, Cobelens F, Vassall A, Kampen S van, Dorman SE, Alland D, et al. Optimal Triage Test Characteristics to Improve the Cost-Effectiveness of the Xpert MTB/RIF Assay for TB Diagnosis: A Decision Analysis. PLOS ONE. 2013. Dec 18;8(12):e82786. - PMC - PubMed
    1. Jaeger S, Karargyris A, Candemir S, Folio L, Siegelman J, Callaghan F, et al. Automatic tuberculosis screening using chest radiographs. IEEE Trans Med Imaging. 2014. Feb;33(2):233–45. - PubMed
    1. Murphy K, Habib SS, Zaidi SMA, Khowaja S, Khan A, Melendez J, et al. Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system. Sci Rep. 2020. Mar 26;10(1):5492. - PMC - PubMed

Publication types