Eligibility criteria <i>vs</i>. need for pre-exposure prophylaxis: a reappraisal among men who have sex with men in Amsterdam, the Netherlands
Bibliographic record
Abstract
Abstract To reappraise pre-exposure prophylaxis (PrEP) eligibility criteria towards the men who have sex with men (MSM) with highest HIV-risk, we assessed PrEP need (i.e. HIV-risk) using Amsterdam Cohort Studies data from 2011–2017 for all non-PrEP using MSM. Outcomes were incident HIV-infection and newly-diagnosed anal STI. Determinants were current PrEP eligibility criteria (anal STI and condomless sex (CAS)) and additional determinants (age, education, group sex, alcohol use during sex and chemsex). We used targeted maximum likelihood estimation (TMLE) to estimate the relative risk (RR) and 95% confidence intervals (CI) of determinants on outcomes, and calculated population attributable fractions (PAFs) with 95% CI using RRs from TMLE. Among 810 included MSM, 22 HIV-infections and 436 anal STIs (n = 229) were diagnosed during follow-up. Chemsex (RR = 5.8 (95% CI 2.0–17.0); PAF = 55.3% (95% CI 43.3–83.4)), CAS with a casual partner (RR = 3.3 (95% CI 1.3–8.7); PAF = 38.0% (95% CI 18.3–93.6)) and anal STI (RR = 5.3 (95% CI 1.7–16.7); PAF = 22.0 (95% CI −16.8 to 100.0)) were significantly (P < 0.05) associated with and had highest attributable risk fractions for HIV. Chemsex (RR = 2.0 (95% CI 1.6–2.4); PAF = 19.5 (95% CI 10.6–30.6)) and CAS with a casual partner (RR = 2.5 (95% CI 2.0–3.0); PAF = 28.0 (95% CI 21.0–36.4)) were also significantly associated with anal STI, as was younger age (16–34/≥35; RR = 1.7 (95% CI 1.4–2.1); PAF = 15.5 (95% CI 6.4–27.6)) and group sex (RR = 1.3 (95% CI 1.1–1.6); PAF = 9.0 (95% CI −2.3 to 23.7)). Chemsex should be an additional PrEP eligibility criterion.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".