Effectiveness and predictors of treatment discontinuation of long-acting cabotegravir/rilpivirine in virologically suppressed people with HIV: real-life data from the Icona Cohort
Bibliographic record
Abstract
BACKGROUND: Phase 3 studies have shown long-acting (LA) cabotegravir/rilpivirine to be effective and tolerable as maintenance therapy in people with HIV (PWH). However, real-life data on their effectiveness are limited. METHODS: All PWH enrolled in the Icona Cohort who started LA cabotegravir/rilpivirine with HIV-RNA < 50 copies/mL were included. Times to treatment discontinuation (TD) and to virological failure (VF50, two consecutive HIV-RNA >50 copies/mL or one >1000 copies/mL followed by ART switch) were estimated by the Kaplan-Meier method. Cox regression models, adjusted for age, sex and mode of HIV transmission and stratified by the centre, were employed. RESULTS: Overall, 583 PWH started LA cabotegravir/rilpivirine. Six VF50 were observed, with a 1 year estimated cumulative probability of virological failure of 1.2% (95% CI, 0.5%-3.0%). Resistance-associated mutations for rilpivirine and cabotegravir were detected in 3/4 and 4/4 participants with VF50, respectively, for which the genotypic resistance test was performed.The 1 year cumulative probability of TD was 11.4% (95% CI, 8.6%-14.9%), mainly caused by toxicity/adverse events (73.2%). Multivariable analysis identified heterosexual intercourse and IV drug use as significant risk factors for TD compared with MSM. CONCLUSIONS: This analysis demonstrated the short-term effectiveness of cabotegravir/rilpivirine in a real-life setting showing minimal incidence of virological failure but a notable probability of discontinuation due to toxicity or adverse events.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".