Evidence map›Paper›PMID 29029637›Full record

Observational studyAIDS research and therapy2017

Drug resistance patterns following pharmacy stock shortage in Nigerian Antiretroviral Treatment Program.

Seema T Meloni, Beth Chaplin, John Idoko, Oche Agbaji, Sulaimon Akanmu, Godwin Imade, Prosper Okonkwo, Robert L Murphy, Phyllis J Kanki

Abstract readObservational Study
In one paragraph

Observational study in AIDS research and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Prodrugs of PKC modulators show enhanced HIV latency reversal and an expanded therapeutic window.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

9 authors.

Seema T MeloniDepartment of Immunology & Infectious Diseases, Harvard T. H. Chan School of Public Health, 651 Huntington Avenue, FXB 405, Boston, 02115, MA, USA.
Beth ChaplinDepartment of Immunology & Infectious Diseases, Harvard T. H. Chan School of Public Health, 651 Huntington Avenue, FXB 405, Boston, 02115, MA, USA.
John IdokoUniversity of Jos, Jos, Plateau State, Nigeria.
Oche AgbajiUniversity of Jos, Jos, Plateau State, Nigeria.
Sulaimon AkanmuLagos University Teaching Hospital, Lagos, Lagos State, Nigeria.
Godwin ImadeUniversity of Jos, Jos, Plateau State, Nigeria.
Prosper OkonkwoAPIN Public Health Initiatives, Ltd./Gte, Abuja, Nigeria.
Robert L MurphyNorthwestern University, Chicago, IL, USA.
Phyllis J KankiDepartment of Immunology & Infectious Diseases, Harvard T. H. Chan School of Public Health, 651 Huntington Avenue, FXB 405, Boston, 02115, MA, USA. pkanki@hsph.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor patients on antiretroviral therapy (ART), treatment interruptions can impact patient outcomes and result in the accumulation of drug resistance mutations leading to virologic failure. There are minimal published data on the impact of an ART stock shortage on development of drug resistance mutations (DRMs). In this report, we evaluate data from patients enrolled in the Government of Nigeria National ART Program that were receiving treatment at the time of a national drug shortage in late 2003.

methodsWe conducted a cross-sectional evaluation of samples collected between December 2004 and August 2005 from ART patients in virologic failure that either had a treatment interruption or did not during the late 2003 drug shortage period at the Jos University Teaching Hospital (JUTH). Plasma virus was genotyped, sequence data were edited and analyzed, and mutation profiles were categorized to evaluate predicted drug susceptibility. Data were analyzed to examine factors associated with development of resistance mutations. A genotypic sensitivity score to the alternate recommended regimen was computed to assess drug susceptibility if regimens were changed.

resultsA total of 56 patients were included in this evaluation (28 interrupted, 28 uninterrupted). Patients in the interrupted group had more DRMs than those in the uninterrupted group (p < 0.001); interrupted patients were more likely than uninterrupted patients to have one or more TAM-2 mutations (57.1% interrupted vs. 21.3% uninterrupted; p = 0.04). There was a statistically significant difference in resistance to both d4T (53.7% interrupted vs. 17.9 uninterrupted; p = 0.011) and AZT (64.3% interrupted vs. 25.0% uninterrupted; p = 0.003) by drug interruption status. Examining genotypic sensitivity scores, we found that 67.9% of the interrupted patients, as compared to 25.0% of the uninterrupted patients, did not have full susceptibility to one drug in the regimen to which guidelines recommended they be switched (p = 0.001). DISCUSSION: In this small observational study, we found evidence of a difference in resistance profiles and ART susceptibility between those that were stocked-out of drug versus those that were not. We believe that these data are relevant for many other low- and middle-income countries (LMIC) that also experienced similar ART shortages as they rapidly scaled up their national programs.

Indexed as

AdultAnti-HIV AgentsCross-Sectional StudiesDrug Resistance, ViralFemaleHIV-1HIV InfectionsHumansMaleMiddle AgedNigeriaTreatment OutcomeViral LoadAnti-HIV AgentsAntiretroviral therapyDrug resistanceDrug shortageMutationsNigeriaUnstructured treatment interruption

Identifiers

PMID29029637
PMCPMC5640939

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.