Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis.
BACKGROUND: Algorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. Th...
Published in: | PLoS Neglected Tropical Diseases |
---|---|
Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Public Library of Science (PLoS)
2011
|
Subjects: | |
Online Access: | https://doi.org/10.1371/journal.pntd.0001233 https://doaj.org/article/ccab37acf3bb4fde8040814a7a6360b4 |
id |
ftdoajarticles:oai:doaj.org/article:ccab37acf3bb4fde8040814a7a6360b4 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:ccab37acf3bb4fde8040814a7a6360b4 2023-05-15T15:14:15+02:00 Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. Francesco Checchi François Chappuis Unni Karunakara Gerardo Priotto Daniel Chandramohan 2011-07-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0001233 https://doaj.org/article/ccab37acf3bb4fde8040814a7a6360b4 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC3130008?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0001233 https://doaj.org/article/ccab37acf3bb4fde8040814a7a6360b4 PLoS Neglected Tropical Diseases, Vol 5, Iss 7, p e1233 (2011) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2011 ftdoajarticles https://doi.org/10.1371/journal.pntd.0001233 2022-12-31T00:59:59Z BACKGROUND: Algorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. There is insufficient evidence on the relative accuracy of these algorithms. This paper presents estimates of the accuracy of five algorithms used by past Médecins Sans Frontières programmes in the Republic of Congo, Southern Sudan and Uganda. METHODOLOGY AND PRINCIPAL FINDINGS: The sequence of tests in each algorithm was programmed into a probabilistic model, informed by distributions of the sensitivity, specificity and staging accuracy of each test, constructed based on a literature review. The accuracy of algorithms was estimated in a baseline scenario and in a worst-case scenario introducing various near worst-case assumptions. In the baseline scenario, sensitivity was estimated as 85-90% in all but one algorithm, with specificity above 99.9% except for the Republic of Congo, where CATT serology was used as independent confirmation test: here, positive predictive value (PPV) was estimated at <50% in realistic active screening prevalence scenarios. Furthermore, most algorithms misclassified about one third of true stage 1 cases as stage 2, and about 10% of true stage 2 cases as stage 1. In the worst-case scenario, sensitivity was 75-90% and PPV no more than 75% at 1% prevalence, with about half of stage 1 cases misclassified as stage 2. CONCLUSIONS: Published evidence on the accuracy of widely used tests is scanty. Algorithms should carefully weigh the use of serology alone for confirmation, and could enhance sensitivity through serological suspect follow-up and repeat parasitology. Better evidence on the frequency of low-parasitaemia infections is needed. Simulation studies should guide the tailoring of algorithms to specific scenarios of HAT prevalence and availability of control tools. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLoS Neglected Tropical Diseases 5 7 e1233 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Francesco Checchi François Chappuis Unni Karunakara Gerardo Priotto Daniel Chandramohan Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
BACKGROUND: Algorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. There is insufficient evidence on the relative accuracy of these algorithms. This paper presents estimates of the accuracy of five algorithms used by past Médecins Sans Frontières programmes in the Republic of Congo, Southern Sudan and Uganda. METHODOLOGY AND PRINCIPAL FINDINGS: The sequence of tests in each algorithm was programmed into a probabilistic model, informed by distributions of the sensitivity, specificity and staging accuracy of each test, constructed based on a literature review. The accuracy of algorithms was estimated in a baseline scenario and in a worst-case scenario introducing various near worst-case assumptions. In the baseline scenario, sensitivity was estimated as 85-90% in all but one algorithm, with specificity above 99.9% except for the Republic of Congo, where CATT serology was used as independent confirmation test: here, positive predictive value (PPV) was estimated at <50% in realistic active screening prevalence scenarios. Furthermore, most algorithms misclassified about one third of true stage 1 cases as stage 2, and about 10% of true stage 2 cases as stage 1. In the worst-case scenario, sensitivity was 75-90% and PPV no more than 75% at 1% prevalence, with about half of stage 1 cases misclassified as stage 2. CONCLUSIONS: Published evidence on the accuracy of widely used tests is scanty. Algorithms should carefully weigh the use of serology alone for confirmation, and could enhance sensitivity through serological suspect follow-up and repeat parasitology. Better evidence on the frequency of low-parasitaemia infections is needed. Simulation studies should guide the tailoring of algorithms to specific scenarios of HAT prevalence and availability of control tools. |
format |
Article in Journal/Newspaper |
author |
Francesco Checchi François Chappuis Unni Karunakara Gerardo Priotto Daniel Chandramohan |
author_facet |
Francesco Checchi François Chappuis Unni Karunakara Gerardo Priotto Daniel Chandramohan |
author_sort |
Francesco Checchi |
title |
Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. |
title_short |
Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. |
title_full |
Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. |
title_fullStr |
Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. |
title_full_unstemmed |
Accuracy of five algorithms to diagnose gambiense human African trypanosomiasis. |
title_sort |
accuracy of five algorithms to diagnose gambiense human african trypanosomiasis. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2011 |
url |
https://doi.org/10.1371/journal.pntd.0001233 https://doaj.org/article/ccab37acf3bb4fde8040814a7a6360b4 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 5, Iss 7, p e1233 (2011) |
op_relation |
http://europepmc.org/articles/PMC3130008?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0001233 https://doaj.org/article/ccab37acf3bb4fde8040814a7a6360b4 |
op_doi |
https://doi.org/10.1371/journal.pntd.0001233 |
container_title |
PLoS Neglected Tropical Diseases |
container_volume |
5 |
container_issue |
7 |
container_start_page |
e1233 |
_version_ |
1766344726292725760 |