Costs and benefits of on-demand HIV preexposure prophylaxis in MSM
Bibliographic record
Abstract
OBJECTIVES: We undertook the economic evaluation of the double-blind randomized ANRS-IPERGAY trial, which showed the efficacy of on-demand preexposure prophylaxis (PrEP) with tenofovir disoproxil fumarate (TDF)-emtricitabine (FTC) in preventing HIV infection among high-risk MSM. DESIGN AND METHODS: The economic evaluation was prospective. Counseling, drugs (TDF-FTC at &OV0556;500.88 for 30 tablets), tests, visits, and hospital admissions were valued based on in-trial use. The cost of on-demand PrEP/HIV infection averted was compared with the yearly and lifetime costs of HIV infection in France in a cost and benefits analysis. RESULTS: The yearly number of participants needed to treat to prevent one HIV infection was 17.6 (95% confidence interval = 10.7-49.9). The annual cost of counseling was &OV0556;690/participant. The total 1-year costs of PrEP were &OV0556;4271/participant, of which &OV0556;3129 (73%) were drug costs corresponding to 15 tablets of TDF-FTC/month. The yearly cost of on-demand PrEP to avoid one infection was &OV0556;75 258. Using TDF-FTC generic (&OV0556;179.9/30 tablets) reduced the 1-year costs of on-demand PrEP to &OV0556;2271/participant and &OV0556;39 970/infection averted, respectively. Using TDF-FTC at international market discounted prices (&OV0556;60/30 tablets) reduced the costs to &OV0556;1517/participant and the cost to &OV0556;26 787/infection averted, comparable with the yearly treatment cost of HIV infection in France. On-demand PrEP was found to be cost saving in France if the duration of exposure was less than 7.5 years at current drug price and 13 years at generic price. CONCLUSION: On-demand PrEP in high-risk MSM with TDF-FTC can be considered cost saving. Other benefits include the treatments of other diseases and reductions in secondary infections.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".