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Record W2981591622 · doi:10.1016/j.eclinm.2019.10.008

Initiation of antiretroviral therapy with integrase strand-transfer inhibitor-based regimens and reduction of the risk of horizontal transmission of HIV-1

2019· article· en· W2981591622 on OpenAlexaboutno aff
Juan Berenguer, Javier Parrondo, Raphael J. Landovitz

Bibliographic record

VenueEClinicalMedicine · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsTransmission (telecommunications)MedicineRegimenIntegraseMen who have sex with menAntiretroviral therapyVirologyIntegrase inhibitorHuman immunodeficiency virus (HIV)ScopusInternal medicineViral loadMEDLINETelecommunicationsComputer scienceBiology

Abstract

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We read with interest the modeling study published by Zhu J et al. showing that initiating antiretroviral therapy (ART) with integrase strand-transfer inhibitor (INSTI)-based regimens can potentially reduce HIV transmission risk significantly when compared to non-INSTI regimens [[1]Zhu J. Rozada I. David J. et al.The potential impact of initiating antiretroviral therapy with integrase inhibitors on HIV transmission risk in British Columbia, Canada.EClinicalMedicine. 2019; 13: 101-111Summary Full Text Full Text PDF PubMed Scopus (8) Google Scholar]. Our group found similar results, first presented in July 2017 at the 9th IAS Conference [[2]Berenguer J. Parrondo J. Landovitz R.J. HIV transmission from condomless anal intercourse differs by initial ART regimen in HIV-infected MSM. Abstract # WEPEC0967.in: 9th IAS conference on HIV science, Paris, France2017Google Scholar], and now published in July 2019 in PLoS ONE [[3]Berenguer J. Parrondo J. Landovitz R.J. Mathematical modeling of HIV-1 transmission risk from condomless anal intercourse in HIV-infected MSM by the type of initial ART.PLoS One. 2019; 14e0219802Crossref Scopus (3) Google Scholar]. We too performed a modeling study that showed that initial use of INSTI-based regimens has the potential to impact HIV-1 horizontal transmission following initiation of ART in treatment naïve men who have sex with men (MSM). In brief, we used discrete event simulation modeling to estimate transmission events during the first eight weeks after initiation of ART as first line therapy for MSM. Simulated transmission events were modeled using inputs from meta-analyses [[4]Wilson D.P. Law M.G. Grulich A.E. Cooper D.A. Kaldor J.M. Relation between HIV viral load and infectiousness: a model-based analysis.Lancet. 2008; 372: 314-320Summary Full Text Full Text PDF PubMed Scopus (274) Google Scholar] and sexual behavior inputs for MSM derived from those found in the START trial [[5]Rodger A.J. Lampe F.C. Grulich A.E. et al.Transmission risk behaviour at enrolment in participants in the INSIGHT Strategic Timing of AntiRetroviral Treatment (START) trial.HIV Med. 2015; 16: 64-76Crossref PubMed Scopus (12) Google Scholar]. HIV RNA decay in MSM was modeled from the databases of three clinical trials Single (dolutegravir [DTG] vs. efavirenz [EFV]), Spring-2 (DTG vs. raltegravir [RAL]) and Flamingo (DTG vs. darunavir/ritonavir [DRV/r]). Our model showed that DTG led to 22.72% fewer transmissions than EFV, 0.52% fewer transmissions than RAL, and 38.67% fewer transmissions than DRV/r. The results of several sensitivity analyses confirmed the robustness of the model. It is reassuring and corroborative that Zhu and colleagues had similar findings in their current analysis. The potential impact of initiating antiretroviral therapy with integrase inhibitors on HIV transmission risk in British Columbia, CanadaInitiating ART on INSTI-based regimens has the potential to reduce HIV transmission risk among individuals with high baseline viral load levels, especially among those with high levels of sexual activity. Full-Text PDF Open Access

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.311
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2019
Admission routes1
Has abstractyes

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