2499. Perceptions of and Preferences for Oral or Long-Acting Injectable Antiretroviral Treatment Regimens in the United States and Canada
Bibliographic record
Abstract
Abstract Background Antiretroviral treatment (ART) for patients living with HIV (PLHIV) has improved greatly, however, challenges with daily oral dosing remain. New ART options with reduced dosing frequency and innovative delivery methods may help address these challenges. This study assesses patient and physician satisfaction with current treatments and preferences for switching to a monthly or every other month long-acting injectable (LAI) ART. Methods This is a cross-sectional online survey of PLHIV and physicians treating PLHIV in United States and Canada. A literature review, clinical expert input, and qualitative and quantitative pilots informed survey design. Eligible PLHIV were on ART for ≥ 6 months and virally suppressed (self-reported). Survey questions for patients evaluate satisfaction and adherence to current ART. Treatment preferences are assessed using a discrete choice experiment (DCE), where respondents choose between staying on current ART, switching to another oral ART or switching to a LAI ART. DCE treatment attributes include dosing frequency, side effects, forgivability, food/mealtime restrictions, and mode of administration. Pilot data for US patients is included here; the main survey will include approximately 550 patients and 450 physicians. Results Of 51 PLHIV completing the pilot survey, 80% were male, mean age was 54 years, and 63% were on ART for ≥10 years. Switching ART was common, with 55% reporting changing their ART ≥ 3 times. Just under half of patients (47%) were not totally satisfied with their current ART. Most common reasons for dissatisfaction included daily reminder of having HIV (31%) and having to take medicine every day (28%). Just over a quarter of patients (28%) reported forgetting to take their ART in the prior month. Across all DCE choices, patients preferred to remain on their current treatment 47% of the time, while 45% of the time patients preferred switching to the LAI, and for the remaining 8%, patients chose switching to another oral ART regimen. Conclusion Despite advances in ART, treatment challenges remain. Among the treatment-experienced PLHIV in this pilot survey, over half of their choices resulted in switching to an alternative regimen, and when opting to switch, most patients preferred the long-acting injectable treatment regimen. Disclosures All authors: No reported disclosures.
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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".