Cited by 77Tuberculosis Research and EpidemiologyInfectious Diseases and TuberculosisLung Cancer Diagnosis and Treatment

Automated chest-radiography as a triage for Xpert testing in resource-constrained settings: a prospective study of diagnostic accuracy and costs

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Philipsen, R. H. H. M., Sánchez, C. I., Maduskar, P., Melendez, J., Peters-Bax, L., Peter, J. G., Dawson, R., Theron, G. +2 more·2015·Scientific Reports

Abstract

Molecular tests hold great potential for tuberculosis (TB) diagnosis, but are costly, time consuming and HIV-infected patients are often sputum scarce. Therefore, alternative approaches are needed. We evaluated automated digital chest radiography (ACR) as a rapid and cheap pre-screen test prior to Xpert MTB/RIF (Xpert). 388 suspected TB subjects underwent chest radiography, Xpert and sputum culture testing. Radiographs were analysed by computer software (CAD4TB) and specialist readers and abnormality scores were allocated. A triage algorithm was simulated in which subjects with a score above a threshold underwent Xpert. We computed sensitivity, specificity, cost per screened subject (CSS), cost per notified TB case (CNTBC) and throughput for different diagnostic thresholds. 18.3% of subjects had culture positive TB. For Xpert alone, sensitivity was 78.9%, specificity 98.1%, CSS $13.09 and CNTBC $90.70. In a pre-screening setting where 40% of subjects would undergo Xpert, CSS decreased to $6.72 and CNTBC to $54.34, with eight TB cases missed and throughput increased from 45 to 113 patients/day. Specialists, on average, read 57% of radiographs as abnormal, reducing CSS ($8.95) and CNTBC ($64.84). ACR pre-screening could substantially reduce costs and increase daily throughput with few TB cases missed. These data inform public health policy in resource-constrained settings.

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Authors
Philipsen, R. H. H. M., Sánchez, C. I., Maduskar, P., Melendez, J., Peters-Bax, L., Peter, J. G., Dawson, R., Theron, G., Dheda, K., & van Ginneken, B.
Affiliations
  • Radboud University Medical Center (NL)
  • University of Cape Town (ZA)
Corresponding author
Philipsen, R. H. H. M.
Venue
Scientific Reports
Published
2015-07-27
Volume
5
Issue
1
Pages
12215-12215
ISSN
2045-2322 (ISSN-L)
OpenAlex
W1014541510
Cited by
77
References
0
Citations by year
2026: 2 · 2025: 8 · 2024: 5 · 2023: 10 · 2022: 11 · 2021: 11 · 2020: 10 · 2019: 8 · 2018: 6 · 2017: 3 · 2016: 3
FWCI
3.11
Type
journal article
Language
en
Open access
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Funders
European and Developing Countries Clinical Trials Partnership
Topics
  • Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
  • Health Sciences › Medicine › Surgery › Infectious Diseases and Tuberculosis
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
Keywords
tuberculosis diagnosis, Xpert MTB/RIF, triage, computer-aided detection, CAD4TB, diagnostic accuracy, throughput, resource-limited settings, people living with HIV, sputum culture, prescreening
MeSH terms
Machine Learning, Adult, Female, Humans, Male, Netherlands, Pattern Recognition, Automated, Prospective Studies, Sensitivity and Specificity, Radiography, Thoracic, Triage, Tuberculosis, Pulmonary, Utilization Review, Reproducibility of Results, Prevalence, Health Care Costs, Molecular Diagnostic Techniques, Resource Allocation

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