Predictors of viral suppression and rebound among HIV-positive men who have sex with men in a large multi-site Canadian cohort
Bibliographic record
Abstract
BACKGROUND: Gay, bisexual and other men who have sex with men (MSM) are disproportionately affected by HIV in Canada. Combination antiretroviral therapy has been shown to dramatically decrease progression to AIDS, premature death and HIV transmission. However, there are no comprehensive data regarding combination antiretroviral therapy outcomes among this population. We sought to identify socio-demographic and clinical correlates of viral suppression and rebound. METHODS: Our analysis included MSM participants in the Canadian Observational Cohort, a multi-site cohort of HIV-positive adults from Canada's three most populous provinces, aged ≥18 years who first initiated combination antiretroviral therapy between 2000 and 2011. We used accelerated failure time models to identify factors predicting time to suppression (2 measures <50 copies/mL ≥30 days apart) and subsequent rebound (2 measures >200 copies/mL ≥30 days apart). RESULTS: Of 2,858 participants, 2,448 (86 %) achieved viral suppression in a median time of 5 months (Q1-Q3: 3-7 months). Viral suppression was significantly associated with later calendar year of antiretroviral therapy initiation, no history of injection drug use, lower baseline viral load, being on an initial regimen consisting of non-nucleoside reverse-transcriptase inhibitors, and older age. Among those who suppressed, 295 (12 %) experienced viral rebound. This was associated with earlier calendar year of antiretroviral therapy initiation, injection drug use history, younger age, higher baseline CD4 cell count, and living in British Columbia. CONCLUSIONS: Further strategies are required to optimize combination antiretroviral therapy outcomes in men who have sex with men in Canada, specifically targeting younger MSM and those with a history of injection drug use.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".