The potential impact of initiating antiretroviral therapy with integrase inhibitors on HIV transmission risk in British Columbia, Canada
Bibliographic record
Abstract
Background Available agents within the integrase strand-transfer inhibitor (INSTI) class have been shown to lead to a faster decay in viral load than other regimens. Therefore, we estimated the potential reduction in HIV transmission risk among antiretroviral-naïve individuals initiating on INSTI-based antiretroviral therapy (ART), focusing on the gay, bisexual and other men who have sex with men (gbMSM) population and various degrees of sexual activity. Methods Using two mathematical models that estimate the HIV transmission risk corresponding to different viral loads, we estimated the average probability of HIV transmission per risky contact for gbMSM during the six months post-ART initiation, stratified by stage of HIV infection, viral load at ART initiation and type of first-line ART (i.e., INSTI or non-INSTI-based ART). This study focused individuals who initiated ART between 2011 and 2016 with at least one year of follow-up in British Columbia, Canada. Findings Time to first virologic suppression for INSTI-based regimens was 21.4 days (95% credible interval (CI) 19.9–23.2), compared to 58.6 days (95% CI 54.1–62.2) for non-INSTI regimens. We showed that INSTI-based regimens could reduce the HIV transmission risk by at least 25% among those with viral load ≥5 log 10 copies/mL at ART initiation. Interpretation Initiating 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. Funding The British Columbia Ministry of Health, the Canadian Institutes of Health Research, and the Michael Smith Foundation for Health Research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".