Evidence map›Paper›PMID 25227265›Full record

ArticleJournal of the International AIDS Society2014

CD4 criteria improves the sensitivity of a clinical algorithm developed to identify viral failure in HIV-positive patients on antiretroviral therapy.

Denise H Evans, Matthew P Fox, Mhairi Maskew, Lynne McNamara, Patrick MacPhail, Christopher Mathews, Ian Sanne

Abstract readEvaluation Study
In one paragraph

Article in Journal of the International AIDS Society, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

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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

7 authors.

Denise H EvansHealth Economics and Epidemiology Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; devans@heroza.org.
Matthew P FoxHealth Economics and Epidemiology Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Boston University, Center for Global Health & Development, Boston, MA, USA.
Mhairi MaskewHealth Economics and Epidemiology Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Lynne McNamaraClinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Patrick MacPhailClinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Right to Care, Johannesburg, South Africa.
Christopher MathewsDepartment of Medicine, University of California, San Diego, CA, USA.
Ian SanneClinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Right to Care, Johannesburg, South Africa.

Funding

Virology CoreP30AI027767 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI OLAF KUTSCH · 1988 to 2026
$84.1M
VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Maile Ann Young Karris · 1994 to 2026
$78.4M
NIAID NIH HHS AI036214NIAID NIH HHS P30 AI027767NIAID NIH HHS P30AI027767NIAID NIH HHS P30 AI036214
6 · The paper itself

Abstract

introductionSeveral studies from resource-limited settings have demonstrated that clinical and immunologic criteria are poor predictors of virologic failure, confirming the need for viral load monitoring or at least an algorithm to target viral load testing. We used data from an electronic patient management system to develop an algorithm to identify patients at risk of viral failure using a combination of accessible and inexpensive markers.

methodsWe analyzed data from HIV-positive adults initiated on antiretroviral therapy (ART) in Johannesburg, South Africa, between April 2004 and February 2010. Viral failure was defined as ≥ 2 consecutive HIV-RNA viral loads >400 copies/ml following suppression ≤ 400 copies/ml. We used Cox-proportional hazards models to calculate hazard ratios (HR) and 95% confidence intervals (CI). Weights for each predictor associated with virologic failure were created as the sum of the natural logarithm of the adjusted HR and dichotomized with the optimal cut-off at the point with the highest sensitivity and specificity (i.e. ≤ 4 vs. >4). We assessed the diagnostic accuracy of predictor scores cut-offs, with and without CD4 criteria (CD4 <100 cells/mm(3); CD4 < baseline; >30% drop in CD4), by calculating the proportion with the outcome and the observed sensitivity, specificity, positive and negative predictive value of the predictor score compared to the gold standard of virologic failure.

resultsWe matched 919 patients with virologic failure (1:3) to 2756 patients without. Our predictor score included variables at ART initiation (i.e. gender, age, CD4 count <100 cells/mm(3), WHO stage III/IV and albumin) and laboratory and clinical follow-up data (drop in haemoglobin, mean cell volume (MCV) <100 fl, CD4 count <200 cells/mm(3), new or recurrent WHO stage III/IV condition, diagnosis of new condition or symptom and regimen change). Overall, 51.4% had a score 51.4% had a score ≥ 4 and 48.6% had a score <4. A predictor score including CD4 criteria performed better than a score without CD4 criteria and better than WHO clinico-immunological criteria or WHO clinical staging to predict virologic failure (sensitivity 57.1% vs. 40.9%, 25.2% and 20.9%, respectively).

conclusionsPredictor scores or risk categories, with CD4 criteria, could be used to identify patients at risk of virologic failure in resource-limited settings so that these patients may be targeted for focused interventions to improve HIV treatment outcomes.

Indexed as

AlgorithmsAdultAnti-Retroviral AgentsCD4 Lymphocyte CountCD4-Positive T-LymphocytesClinical Laboratory TechniquesDrug MonitoringFemaleHIV InfectionsHumansMaleRetrospective StudiesSensitivity and SpecificitySouth AfricaTreatment FailureViral LoadAnti-Retroviral Agentsalgorithmantiretroviral therapyCD4HIVmonitoringresource limitedviral load

Identifiers

PMID25227265
PMCPMC4165719

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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.