Evidence map›Paper›PMID 27548695›Full record

Observational studyPloS one2016

Marginal Structural Models to Assess Delays in Second-Line HIV Treatment Initiation in South Africa.

Julia K Rohr, Prudence Ive, C Robert Horsburgh, Rebecca Berhanu, Kate Shearer, Mhairi Maskew, Lawrence Long, Ian Sanne, Jean Bassett, Osman Ebrahim and 1 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Ranking tailoring variables for constructing individualized treatment rules: an application to schizophrenia.Journal of the Royal Statistical Society. Series C, Applied statistics · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Article
  20. 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

11 authors.

Julia K RohrCenter for Global Health & Development, Boston University, Boston, United States of America.ORCID http://orcid.org/0000-0002-1180-8764
Prudence IveClinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
C Robert HorsburghCenter for Global Health & Development, Boston University, Boston, United States of America.
Rebecca BerhanuClinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Kate ShearerHealth Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Mhairi MaskewHealth 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 LongHealth Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Ian SanneHealth Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Jean BassettWitkoppen Health and Welfare Centre, Johannesburg, South Africa.
Osman EbrahimDepartment of Medical Microbiology, University of Pretoria, Pretoria, South Africa.
Matthew P FoxCenter for Global Health & Development, Boston University, Boston, United States of America.

Funding

Johns Hopkins HIV Epidemiology and Prevention Sciences Training ProgramT32AI102623 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Shruti H Mehta · 2013 to 2026
$5.3M
NIAID NIH HHS T32 AI102623
6 · The paper itself

Abstract

backgroundSouth African HIV treatment guidelines call for patients who fail first-line antiretroviral therapy (ART) to be switched to second-line ART, yet logistical issues, clinician decisions and patient preferences make delay in switching to second-line likely. We explore the impact of delaying second-line ART after first-line treatment failure on rates of death and virologic failure.

methodsWe include patients with documented virologic failure on first-line ART from an observational cohort of 9 South African clinics. We explored predictors of delayed second-line switch and used marginal structural models to analyze rates of death following first-line failure by categorical time to switch to second-line. Cox proportional hazards models were used to examine virologic failure on second-line ART among patients who switched to second-line.

results5895 patients failed first-line ART, and 63% switched to second-line. Among patients who switched, median time to switch was 3.4 months (IQR: 1.1-8.7 months). Longer time to switch was associated with higher CD4 counts, lower viral loads and more missed visits prior to first-line failure. Worse outcomes were associated with delay in second-line switch among patients with a peak CD4 count on first-line treatment ≤100 cells/mm3. Among these patients, marginal structural models showed increased risk of death (adjusted HR for switch in 6-12 months vs. 0-1.5 months = 1.47 (95% CI: 0.94-2.29), and Cox models showed increased rates of second-line virologic failure despite the presence of survivor bias (adjusted HR for switch in 3-6 months vs. 0-1.5 months = 2.13 (95% CI: 1.01-4.47)).

conclusionsEven small delays in switch to second-line ART were associated with increased death and second-line failure among patients with low CD4 counts on first-line. There is opportunity for healthcare providers to switch patients to second-line more quickly.

Indexed as

AdultAnti-HIV AgentsAntiretroviral Therapy, Highly ActiveCD4 Lymphocyte CountCD4-Positive T-LymphocytesCohort StudiesDrug SubstitutionFemaleHIV InfectionsHumansMalePatient ComplianceProportional Hazards ModelsSouth AfricaTime FactorsTreatment FailureAnti-HIV Agents

Identifiers

PMID27548695
PMCPMC4993510

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.