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Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis
BACKGROUND: Automated digital microscopy has the potential to improve the diagnosis of tuberculosis (TB), particularly in settings where molecular testing is too expensive to perform routinely. The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain. M...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4913947/ https://www.ncbi.nlm.nih.gov/pubmed/27322162 http://dx.doi.org/10.1371/journal.pone.0157554 |
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author | Jha, Swati Ismail, Nazir Clark, David Lewis, James J. Omar, Shaheed Dreyer, Andries Chihota, Violet Churchyard, Gavin Dowdy, David W. |
author_facet | Jha, Swati Ismail, Nazir Clark, David Lewis, James J. Omar, Shaheed Dreyer, Andries Chihota, Violet Churchyard, Gavin Dowdy, David W. |
author_sort | Jha, Swati |
collection | PubMed |
description | BACKGROUND: Automated digital microscopy has the potential to improve the diagnosis of tuberculosis (TB), particularly in settings where molecular testing is too expensive to perform routinely. The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain. METHODS: Using data from a demonstration study of an automated digital microscopy system (TBDx, Applied Visual Systems, Inc.), we performed an economic evaluation of TB diagnosis in South Africa from the health system perspective. The primary outcome was the incremental cost per new TB diagnosis made. We considered costs and effectiveness of different algorithms for automated digital microscopy, including as a stand-alone test and with confirmation of positive results with Xpert MTB/RIF (‘Xpert’, Cepheid, Inc.). Results were compared against both manual microscopy and universal Xpert testing. RESULTS: In settings willing to pay $2000 per incremental TB diagnosis, universal Xpert was the preferred strategy. However, where resources were not sufficient to support universal Xpert, and a testing volume of at least 30 specimens per day could be ensured, automated digital microscopy with Xpert confirmation of low-positive results could facilitate the diagnosis of 79–84% of all Xpert-positive TB cases, at 50–60% of the total cost. The cost-effectiveness of this strategy was $1280 per incremental TB diagnosis (95% uncertainty range, UR: $340-$3440) in the base case, but improved under conditions likely reflective of many settings in sub-Saharan Africa: $677 per diagnosis (95% UR: $450-$935) when sensitivity of manual smear microscopy was lowered to 0.5, and $956 per diagnosis (95% UR: $40-$2910) when the prevalence of multidrug-resistant TB was lowered to 1%. CONCLUSIONS: Although universal Xpert testing is the preferred algorithm for TB diagnosis when resources are sufficient, automated digital microscopy can identify the majority of cases and halve the cost of diagnosis and treatment when resources are more scarce and multidrug-resistant TB is not common. |
format | Online Article Text |
id | pubmed-4913947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49139472016-07-06 Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis Jha, Swati Ismail, Nazir Clark, David Lewis, James J. Omar, Shaheed Dreyer, Andries Chihota, Violet Churchyard, Gavin Dowdy, David W. PLoS One Research Article BACKGROUND: Automated digital microscopy has the potential to improve the diagnosis of tuberculosis (TB), particularly in settings where molecular testing is too expensive to perform routinely. The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain. METHODS: Using data from a demonstration study of an automated digital microscopy system (TBDx, Applied Visual Systems, Inc.), we performed an economic evaluation of TB diagnosis in South Africa from the health system perspective. The primary outcome was the incremental cost per new TB diagnosis made. We considered costs and effectiveness of different algorithms for automated digital microscopy, including as a stand-alone test and with confirmation of positive results with Xpert MTB/RIF (‘Xpert’, Cepheid, Inc.). Results were compared against both manual microscopy and universal Xpert testing. RESULTS: In settings willing to pay $2000 per incremental TB diagnosis, universal Xpert was the preferred strategy. However, where resources were not sufficient to support universal Xpert, and a testing volume of at least 30 specimens per day could be ensured, automated digital microscopy with Xpert confirmation of low-positive results could facilitate the diagnosis of 79–84% of all Xpert-positive TB cases, at 50–60% of the total cost. The cost-effectiveness of this strategy was $1280 per incremental TB diagnosis (95% uncertainty range, UR: $340-$3440) in the base case, but improved under conditions likely reflective of many settings in sub-Saharan Africa: $677 per diagnosis (95% UR: $450-$935) when sensitivity of manual smear microscopy was lowered to 0.5, and $956 per diagnosis (95% UR: $40-$2910) when the prevalence of multidrug-resistant TB was lowered to 1%. CONCLUSIONS: Although universal Xpert testing is the preferred algorithm for TB diagnosis when resources are sufficient, automated digital microscopy can identify the majority of cases and halve the cost of diagnosis and treatment when resources are more scarce and multidrug-resistant TB is not common. Public Library of Science 2016-06-20 /pmc/articles/PMC4913947/ /pubmed/27322162 http://dx.doi.org/10.1371/journal.pone.0157554 Text en © 2016 Jha et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Jha, Swati Ismail, Nazir Clark, David Lewis, James J. Omar, Shaheed Dreyer, Andries Chihota, Violet Churchyard, Gavin Dowdy, David W. Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis |
title | Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis |
title_full | Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis |
title_fullStr | Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis |
title_full_unstemmed | Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis |
title_short | Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis |
title_sort | cost-effectiveness of automated digital microscopy for diagnosis of active tuberculosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4913947/ https://www.ncbi.nlm.nih.gov/pubmed/27322162 http://dx.doi.org/10.1371/journal.pone.0157554 |
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