First-line HIV treatment outcomes following the introduction of integrase inhibitors in UK guidelines
Bibliographic record
Abstract
OBJECTIVE: To investigate the characteristics and outcomes of people who initiated different antiretroviral therapy (ART) regimens during the era of integrase strand transfer inhibitors (INSTIs). DESIGN: UK-based observational cohort study. METHODS: UK Collaborative HIV Cohort study participants were included if they had started ART between 1 January 2012 and 30 June 2017. Virological failure was defined as the first of two consecutive plasma HIV RNA more than 50 copies/ml, at least 6 months after starting ART. Follow-up was censored at ART discontinuation, class switch or death. The risk of virological failure among those on INSTI, protease inhibitor or nonnucleoside reverse transcriptase inhibitor (NNRTI) regimens was compared using Kaplan-Meier and Cox regression methods. RESULTS: Of 12 585 participants, 45.6% started a NNRTI, 29.0% a protease inhibitor and 25.4% an INSTI regimen. Over a median follow-up of 20.3 months (interquartile range 7.9-38.9), 7.5% of participants experienced virological failure. Compared with those starting an NNRTI regimen, people receiving INSTIs or protease inhibitors were more likely to experience virological failure: INSTI group adjusted hazard ratio 1.52, 95% confidence interval 1.19-1.95, P = 0.0009; protease inhibitor group adjusted hazard ratio 2.70, 95% confidence interval 2.27-3.21, P less than 0.0001, likelihood ratio test P less than 0.0001. CONCLUSION: First-line INSTI regimens were associated with a lower risk of virological failure than protease inhibitor regimens but both groups were more likely to experience virological failure than those initiating treatment with a NNRTI. There is likely to be residual channelling bias resulting from selected use of INSTIs and protease inhibitors in specific clinical contexts, including in those with a perceived risk of poor adherence.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".