Blood-based host biomarker diagnostics in active case finding for pulmonary tuberculosis: A diagnostic case-control study

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

There is a need to identify scalable tuberculosis screening strategies among high burden populations. The WHO has identified a non-sputum-based triage test as a development priority.

Methods

We performed a diagnostic case-control study of point-of-care C-reactive protein (CRP) and Prototype-Xpert-MTB-Host-Response (Xpert-MTB-HR) assays in the context of a mass screening program for tuberculosis in two prisons in Brazil. All incarcerated individuals irrespective of symptoms were screened by sputum Xpert MTB/RIF and sputum culture. Among consecutive, Xpert MTB/RIF or culture-confirmed cases and Xpert MTB/RIF and culture-negative controls, CRP was quantified in serum by a point-of-care assay (iChroma-II) and a 3-gene expression score was quantified from whole blood using the Xpert-MTB-HR cartridge. We evaluated receiver operating characteristic area under the curve (AUC) and assessed specificity at 90% sensitivity and sensitivity at 70% specificity, consistent with WHO target product profile (TPP) benchmarks.

Findings

Two hundred controls (no TB) and 100 culture- or Xpert MTB/RIF-positive tuberculosis cases were included. Half of tuberculosis cases and 11% of controls reported any tuberculosis symptoms. AUC for CRP was 0·79 (95% CI: 0·73–0·84) and for Xpert-MTB-HR was 0·84 (95% CI: 0·79–0·89). At 90% sensitivity, Xpert-MTB-HR had significantly higher specificity (53·0%, 95% CI: 45·0–69·0%) than CRP (28·1%, 95% CI: 20·2–41·8%) ( p = 0·003), both well below the TPP benchmark of 70%. Among individuals with medium or high sputum Xpert MTB/RIF semi-quantitative load, sensitivity (at 70% specificity) of CRP (90·3%, 95% CI: 74·2–98·0) and Xpert-MTB-HR (96·8%, 95% CI: 83·3–99·9%) was higher.

Interpretation

For active case finding in this high tuberculosis-burden setting, CRP and Xpert-MTB-HR did not meet TPP benchmarks for a triage test. However, Xpert-MTB-HR was highly sensitive in detecting individuals with medium or high sputum bacillary burden.

Funding

National Institutes of Health (R01 AI130058 and R01 AI149620) and Brazilian National Council for Scientific and Technological Development (CNPq-404182/2019-4).

Related collections

Most cited references 26

Record: found
Abstract: found
Article: not found

pROC: an open-source package for R and S+ to analyze and compare ROC curves

Xavier Robin, Natacha Turck, Alexandre Hainard … (2013)

Background Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. Results With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. Conclusions pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

0 comments Cited 2714 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies

Patrick Bossuyt, Johannes Reitsma, David Bruns … (2015)

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting Diagnostic Accuracy (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

0 comments Cited 732 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

A prospective blood RNA signature for tuberculosis disease risk

Daniel E. Zak, Adam Penn-Nicholson, Thomas Scriba … (2016)

Background Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease may lead to interventions that impact the epidemic. Methods Healthy, M. tuberculosis infected South African adolescents were followed for 2 years; blood was collected every 6 months. A prospective signature of risk was derived from whole blood RNA-Sequencing data by comparing participants who ultimately developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. The latter participants were household contacts of adults with active pulmonary tuberculosis disease. Findings Of 6,363 adolescents screened, 46 progressors and 107 matched controls were identified. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% confidence interval, 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA-Seq and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6–64·3) and a specificity of 82·8% (76·7–86) in 12 months preceding tuberculosis. Interpretation The whole blood tuberculosis risk signature prospectively identified persons at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. Funding Bill and Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union and the South African Medical Research Council (detail at end of text).

0 comments Cited 194 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Jason R. Andrews

Journal

Journal ID (nlm-ta): EClinicalMedicine

Journal ID (iso-abbrev): EClinicalMedicine

Title: EClinicalMedicine

Publisher: Elsevier

ISSN (Electronic): 2589-5370

Publication date PMC-release: 06 March 2021

Publication date Collection: March 2021

Publication date (Electronic): 06 March 2021

Volume: 33

Electronic Location Identifier: 100776

Affiliations

[a ]Faculty of Health Sciences, Federal University of Grande Dourados, Dourados, MS, Brazil

[b ]Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA

[c ]Cepheid, Sunnyvale, CA, USA

[d ]Cepheid AB, Solna, Sweden

[e ]Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA

[f ]Oswaldo Cruz Foundation, Campo Grande, MS, Brazil

[g ]School of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil

[h ]Yale School of Public Health, New Haven, CT, USA

Author notes

[* ]Corresponding author at: Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Biomedical Innovations Building, Rm 3458, 240 Pasteur Dr., Stanford, CA 94305, USA. jandr@ 123456stanford.edu

[1]

Contributed equally.

Article

Publisher Item ID: S2589-5370(21)00056-0 Publisher ID: 100776

DOI: 10.1016/j.eclinm.2021.100776

PMC ID: 8020164

PubMed ID: 33842866

SO-VID: 97896ea6-9637-4261-a616-87510c53c465

License:

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

History

Date received : 31 December 2020

Date revision received : 11 February 2021

Date accepted : 12 February 2021

Comments

Comment on this article

scite_

Cited by 17

See all cited by

Most referenced authors 587

See all reference authors

Blood-based host biomarker diagnostics in active case finding for pulmonary tuberculosis: A diagnostic case-control study

Read this article at

Abstract

Background

Methods

Findings

Interpretation

Funding

Related collections

Point-Of-Care Testing for Tuberculosis

Most cited references 26

pROC: an open-source package for R and S+ to analyze and compare ROC curves

STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies

A prospective blood RNA signature for tuberculosis disease risk

Author and article information

Contributors

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 91

Cited by 17

Most referenced authors 587