De‐simplifying antiretroviral therapy from a single‐tablet to a two‐tablet regimen: Acceptance, patient‐reported outcomes, and cost savings in a multicentre study
Bibliographic record
Abstract
BACKGROUND: Antiretroviral therapy (ART), which is increasingly used by people with HIV, accounts for significant care costs, particularly because of single-tablet regimens (STRs). This study explored de-simplification to a two-tablet regimen (TTR) for cost reduction. The objectives of this study were: (1) acceptance of de-simplification, (2) patient-reported outcomes, and (3) cost savings. METHODS: All individuals on Triumeq®, Atripla® or Eviplera® in five HIV clinics in the Netherlands were eligible. Healthcare providers informed individuals of this study. After inclusion, individuals were free to de-simplify. An electronic questionnaire was sent to assess study acceptance, adherence, quality of life (SF12) and treatment satisfaction (HIVTSQ). After 3 and 12 months, questionnaires were repeated. Cost savings were calculated using Dutch drug prices. RESULTS: In total, 283 individuals were included, of whom 55.5% agreed to de-simplify their ART, with a large variability between treatment centres: 41.1-74.2%. Individuals who were willing to de-simplify tended to be older, had a longer history of HIV diagnosis, and used more co-medication than those who preferred to remain on an STR regimen. Patient-reported outcomes, including quality of life and treatment satisfaction, showed no significant difference between people with HIV who switched to a TTR and those who remained on an STR regimen. Furthermore, we observed a 17.8% reduction in drug costs in our cohort of people with HIV who were initially on an STR. CONCLUSIONS: De-simplification from an STR to a TTR within the Dutch healthcare setting has been demonstrated as feasible, leads to significant cost reductions and should be discussed with every eligible person with HIV in the Netherlands.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".