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      Comparison of diagnostic accuracy of QuantiFERON‐TB Gold Plus and T‐SPOT.TB in the diagnosis of active tuberculosis in febrile patients

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          Abstract

          Objective

          This study aimed to compare the accuracy of QuantiFERON‐TB Gold Plus (QFT‐Plus) and T‐SPOT.TB for diagnosing active tuberculosis (ATB) in febrile patients, to explore influencing factors of positive results and to verify the potential value of QFT‐Plus in the identification of ATB and latent tuberculosis infection (LTBI).

          Methods

          A total of 240 febrile patients with ATB ( n = 80) and non‐ATB ( n = 160) were recruited to assess the accuracy of QFT‐Plus and T‐SPOT.TB for diagnosing ATB. Multivariable logistic regression was used to analyze the influencing factors of positive results.

          Results

          The proportion of indeterminate results (ITRS) in QFT‐Plus and T‐SPOT.TB were 3.3% and 0%, respectively. The consistency between the results of the QFT‐Plus and T‐SPOT.TB was substantial. The area under the receiver operating characteristic curve (AUROC) of the QFT‐Plus and T‐SPOT.TB for diagnosing ATB was 0.792 and 0.849 ( p = 0.070), respectively. The sensitivity of differentiating ATB from non‐ATB was 92.2% in QFT‐Plus versus 95.0% in T‐SPOT.TB. The influencing factors of T‐SPOT.TB positive result were male (odds ratio (OR) = 2.33, 95% confidence interval (CI) 1.27–4.26, p = 0.006), evidence of previous TB (OR 11.36, 95% CI 4.62–27.94, p < 0.001), while male (OR = 3.17, 95% CI 1.73–5.84, p < 0.001), evidence of previous TB (OR = 7.58, 95% CI 3.60–15.98, p <0.001), and use of immunosuppressant (OR = 0.49, 95% CI 0.260.94, p = 0.030) were influencing factors for QFT‐Plus positive result. There was no significant difference in QFT‐Plus in differentiating ATB from LTBI in febrile patients.

          Conclusion

          There was no significant difference between QFT‐Plus and T‐SPOT.TB for diagnosing ATB in febrile patients. QFT‐Plus is prone to ITRS. The influencing factors including males, evidence of the previous TB, and use of immunosuppressant should be considered when interpreting positive results.

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          Gamma interferon release assays for detection of Mycobacterium tuberculosis infection.

          Madhukar Pai, Claudia Denkinger, Sandra Kik … (2014)
          Identification and treatment of latent tuberculosis infection (LTBI) can substantially reduce the risk of developing active disease. However, there is no diagnostic gold standard for LTBI. Two tests are available for identification of LTBI: the tuberculin skin test (TST) and the gamma interferon (IFN-γ) release assay (IGRA). Evidence suggests that both TST and IGRA are acceptable but imperfect tests. They represent indirect markers of Mycobacterium tuberculosis exposure and indicate a cellular immune response to M. tuberculosis. Neither test can accurately differentiate between LTBI and active TB, distinguish reactivation from reinfection, or resolve the various stages within the spectrum of M. tuberculosis infection. Both TST and IGRA have reduced sensitivity in immunocompromised patients and have low predictive value for progression to active TB. To maximize the positive predictive value of existing tests, LTBI screening should be reserved for those who are at sufficiently high risk of progressing to disease. Such high-risk individuals may be identifiable by using multivariable risk prediction models that incorporate test results with risk factors and using serial testing to resolve underlying phenotypes. In the longer term, basic research is necessary to identify highly predictive biomarkers.
          Article 0 comments Cited 170 times – based on 0 reviews     Review now
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            Interferon-γ release assays for the diagnosis of active tuberculosis: a systematic review and meta-analysis.

            M. Lipman, C Giehl, A Sandgren … (2010)
            Interferon-γ release assays (IGRAs) are now established for the immunodiagnosis of latent infection with Mycobacterium tuberculosis in many countries. However, the role of IGRAs for the diagnosis of active tuberculosis (TB) remains unclear. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) and quality assessment of diagnostic accuracy studies (QUADAS) guidelines, we searched PubMed, EMBASE and Cochrane databases to identify studies published in January 2001-November 2009 that evaluated the evidence of using QuantiFERON-TB® Gold in-tube (QFT-G-IT) and T-SPOT.TB® directly on blood or extrasanguinous specimens for the diagnosis of active TB. The literature search yielded 844 studies and 27 met the inclusion criteria. In blood and extrasanguinous fluids, the pooled sensitivity for the diagnosis of active TB was 80% (95% CI 75-84%) and 48% (95% CI 39-58%) for QFT-G-IT, and 81% (95% CI 78-84%) and 88% (confirmed and unconfirmed cases) (95% CI 82-92%) for T-SPOT.TB®, respectively. In blood and extrasanguinous fluids, the pooled specificity was 79% (95% CI 75-82%) and 82% (95% CI 70-91%) for QFT-G-IT, and 59% (95% CI 56-62%) and 82% (95% CI 78-86%) for T-SPOT.TB®, respectively. Although the diagnostic sensitivities of both IGRAs were higher than that of tuberculin skin tests, it was still not high enough to use as a rule out test for TB. Positive evidence for the use of IGRAs in compartments other than blood will require more independent and carefully designed prospective studies.
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              Heterogeneity in tuberculosis

              JoAnne Flynn, Anthony M. Cadena, Sarah M. Fortune (2017)
              Infection with Mycobacterium tuberculosis , the causative agent of tuberculosis (TB), results in a range of clinical presentations in humans. Most infections manifest as a clinically asymptomatic, contained state that is termed latent TB infection (LTBI); a smaller subset of infected individuals present with symptomatic, active TB. Within these two seemingly binary states, there is a spectrum of host outcomes that have varying symptoms, microbiologies, immune responses and pathologies. Recently, it has become apparent that there is diversity of infection even within a single individual. A good understanding of the heterogeneity that is intrinsic to TB — at both the population level and the individual level — is crucial to inform the development of intervention strategies that account for and target the unique, complex and independent nature of the local host–pathogen interactions that occur in this infection. In this Review, we draw on model systems and human data to discuss multiple facets of TB biology and their relationship to the overall heterogeneity observed in the human disease.
              Article 0 comments Cited 151 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Xiaoqing Liu:
                ORCID: https://orcid.org/0000-0001-8162-0903
                liuxq@pumch.cn
                Journal
                Journal ID (nlm-ta): J Evid Based Med
                Journal ID (iso-abbrev): J Evid Based Med
                Journal ID (doi): 10.1111/(ISSN)1756-5391
                Journal ID (publisher-id): JEBM
                Title: Journal of Evidence-Based Medicine
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 1756-5391
                Publication date (Electronic): 28 June 2022
                Publication date (Print): June 2022
                Volume: 15
                Issue: 2 ( doiID: 10.1111/jebm.v15.2 )
                Pages: 97-105
                Affiliations
                [ 1 ] Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
                [ 2 ] Clinical Epidemiology Unit, Peking Union Medical College International Clinical Epidemiology Network Beijing China
                [ 3 ] Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
                [ 4 ] M.D. Program Peking Union Medical College Beijing China
                [ 5 ] Department of Tuberculosis, Beijing Chest Hospital Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute Beijing China
                Author notes
                [*] [* ] Correspondence

                Xiaoqing Liu, Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

                Email: liuxq@ 123456pumch.cn

                Author information
                https://orcid.org/0000-0001-8162-0903
                Article
                Publisher ID: JEBM12477
                DOI: 10.1111/jebm.12477
                PMC ID: 9540107
                PubMed ID: 35762517
                SO-VID: 5f389122-8886-4036-9be8-93fa3afd9398
                Copyright © © 2022 The Authors. Journal of Evidence‐Based Medicine published by Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                Date received : 21 January 2022
                Date accepted : 29 May 2022
                Page count
                Figures: 3, Tables: 6, Pages: 9, Words: 4925
                Categories
                Subject: Article
                Subject: Articles
                Custom metadata
                source-schema-version-number 2.0
                cover-date June 2022
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                ScienceOpen disciplines: Medicine
                Keywords: active tuberculosis,diagnostic accuracy,febrile,qft‐plus,t‐spot.tb
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: active tuberculosis, diagnostic accuracy, febrile, qft‐plus, t‐spot.tb

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