Evidence map›Paper›PMID 28445088›Full record

ArticleAIDS patient care and STDs2017

Predicting the Need for Third-Line Antiretroviral Therapy by Identifying Patients at High Risk for Failing Second-Line Antiretroviral Therapy in South Africa.

Dorina Onoya, Cornelius Nattey, Eric Budgell, Liudmyla van den Berg, Mhairi Maskew, Denise Evans, Kamban Hirasen, Lawrence C Long, Matthew P Fox

Abstract read
In one paragraph

Article in AIDS patient care and STDs, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 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

9 authors.

Dorina Onoya1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Cornelius Nattey1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Eric Budgell1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Liudmyla van den Berg2 Right to Care, Johannesburg, South Africa .
Mhairi Maskew1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Denise Evans1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Kamban Hirasen1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Lawrence C Long1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .
Matthew P Fox1 Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand , Johannesburg, South Africa .

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although third-line antiretroviral therapy (ART) is available in South Africa's public sector, its cost is substantially higher than first and second line. Identifying risk factors for failure on second-line treatment remains crucial to reduce the need for third-line drugs. We conducted a case-control study including 194 adult patients (≥18 years; 70 cases and 124 controls) who initiated second-line ART in Johannesburg, South Africa. Unconditional logistic regression was used to assess predictors of virologic failure (defined as 2 consecutive viral load measures ≥1000 copies/mL, ≥3 months after switching to second line). Variables included a social instability index, ART adherence, self-reported as well as diagnosed adverse drug reactions (ADRs), HIV disclosure, depression, and factors affecting access to HIV clinics. Overall 60.0% of cases and 54.0% of controls were female. Mean ages of cases and controls were 41.8 ± 9.6 and 43.3 ± 8.0, respectively. Virologic failure was predicted by ART adherence <90% [odds ratio (OR) 4.7; 95% confidence interval (95% CI): 2.1-10.5], younger age (<40 years of age; OR 0.6; 95% CI: 0.3-1.1), high social instability (OR 3.8; 95% CI: 1.30-11.5), self-reported ADR (OR 1.9; 95% CI: 1.0-3.5), disclosure to friends/colleagues rather than partner/relatives (OR 3.4; 95% CI: 1.3-9.1), and medium/high depression compared to low/no depression (OR 4.4; 95% CI: 1.5-13.4). Our results suggest complex socioeconomic factors contributing to risk of virologic failure, possibly by impacting ART adherence, among patients on second-line therapy in South Africa. Identifying patients with possible indicators of nonadherence could facilitate targeted interventions to reduce the risk of second-line treatment failure and mitigate the demand for third-line regimens.

Indexed as

Patient ComplianceAdultAnti-HIV AgentsAntiretroviral Therapy, Highly ActiveCase-Control StudiesDepressionDisclosureDrug-Related Side Effects and Adverse ReactionsDrug Resistance, ViralFemaleHIV-1HIV InfectionsHumansMaleMiddle AgedRisk AssessmentAnti-HIV Agentsantiretroviral therapyHIV treatmentsecond-line regimenSouth Africavirologic failure

Identifiers

PMID28445088
PMCPMC5446602

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.