Evidence map›Paper›PMID 28747371›Full record

ArticleJournal of clinical microbiology2017

Designing HIV Testing Algorithms Based on 2015 WHO Guidelines Using Data from Six Sites in Sub-Saharan Africa.

Cara S Kosack, Leslie Shanks, Greet Beelaert, Tumwesigye Benson, Aboubacar Savane, Anne Ng'ang'a, André Bita, Jean-Paul B N Zahinda, Katrien Fransen, Anne-Laure Page

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Treatment-adjusted prevalence to assess HIV testing programmes.Bulletin of the World Health Organization · 2021
    Article
  5. Review
  6. Differences among diagnostic testing algorithms in the time from HIV diagnosis to care.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2019
    Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Cara S KosackMédecins sans Frontières, Amsterdam, Netherlands.
Leslie ShanksMédecins sans Frontières, Amsterdam, Netherlands.
Greet BeelaertInstitute of Tropical Medicine, Antwerp, Belgium.
Tumwesigye BensonMinistry of Health Uganda, Kampala, Uganda.
Aboubacar SavaneLaboratoire National de Reference, Conakry, Guinea.
Anne Ng'ang'aNational AIDS and Sexually Transmitted Infections Control Programme, Nairobi, Kenya.
André BitaRegional Delegation of Public Health for the Littoral Region, Yaounde, Cameroon.
Jean-Paul B N ZahindaProgramme National de Lutte contre le Sida et les IST (PNLS), Bukavu, Democratic Republic of Congo.
Katrien FransenInstitute of Tropical Medicine, Antwerp, Belgium.
Anne-Laure PageEpicentre, Paris, France anne-laure.page@epicentre.msf.org.ORCID 0000-0001-7952-3178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our objective was to evaluate the performance of HIV testing algorithms based on WHO recommendations, using data from specimens collected at six HIV testing and counseling sites in sub-Saharan Africa (Conakry, Guinea; Kitgum and Arua, Uganda; Homa Bay, Kenya; Douala, Cameroon; Baraka, Democratic Republic of Congo). A total of 2,780 samples, including 1,306 HIV-positive samples, were included in the analysis. HIV testing algorithms were designed using Determine as a first test. Second and third rapid diagnostic tests (RDTs) were selected based on site-specific performance, adhering where possible to the WHO-recommended minimum requirements of ≥99% sensitivity and specificity. The threshold for specificity was reduced to 98% or 96% if necessary. We also simulated algorithms consisting of one RDT followed by a simple confirmatory assay. The positive predictive values (PPV) of the simulated algorithms ranged from 75.8% to 100% using strategies recommended for high-prevalence settings, 98.7% to 100% using strategies recommended for low-prevalence settings, and 98.1% to 100% using a rapid test followed by a simple confirmatory assay. Although we were able to design algorithms that met the recommended PPV of ≥99% in five of six sites using the applicable high-prevalence strategy, options were often very limited due to suboptimal performance of individual RDTs and to shared falsely reactive results. These results underscore the impact of the sequence of HIV tests and of shared false-reactivity data on algorithm performance. Where it is not possible to identify tests that meet WHO-recommended specifications, the low-prevalence strategy may be more suitable.

Indexed as

AlgorithmsAfrica South of the SaharaDiagnostic Tests, RoutineEnzyme-Linked Immunosorbent AssayGuidelines as TopicHIV InfectionsHumansMass ScreeningSensitivity and SpecificityWorld Health Organizationdiagnostic accuracydiagnostic algorithmshuman immunodeficiency viruspositive predictive valuerapid testsWHO guidelines

Identifiers

PMID28747371
PMCPMC5625386

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.