Protocol of a drug–drug interaction study between bictegravir/emtricitabine/tenofovir alafenamide and feminizing hormones in trans women living with HIV
Bibliographic record
Abstract
Aims Trans/transfeminine women are disproportionally affected by HIV. Concerns regarding negative drug–drug interactions (DDIs) between ART drugs and gender‐affirming hormone therapy (GAHT), specifically feminizing hormone therapy (FHT), may contribute to the lower ART uptake by trans women with HIV compared with their cis counterparts. The aim of this study is to investigate the bidirectional pharmacokinetic effects of components of FHT regimens (oral oestradiol and androgen‐suppressing medications) with the ART regimen (bictegravir/emtricitabine/tenofovir alafenamide [B/F/TAF)]. Methods We present a protocol for a three‐armed, parallel‐group, longitudinal (6‐month), DDI study. Group 1 includes 15 3trans women with HIV taking FHT and ART; group 2 includes 15 premenopausal cis women with HIV taking ART; group 3 includes 15 trans women without HIV taking FHT. Women with HIV must be on or switch to B/F/TAF at baseline and be virally suppressed for ≥3 months. Trans women must be taking a stable regimen of ≥2 mg daily oral oestradiol and an anti‐androgen (pharmaceutical, and/or surgical, and/or medical) for ≥3 months. Plasma ART drug concentrations will be sampled at Month 2 and compared between groups 1 and 2. Serum oestradiol concentrations will be sampled at baseline and Month 2 visits and compared between groups 1 and 3. The primary outcomes are B/F/TAF pharmacokinetic parameters (Cmin, Cmax and AUC) and oestradiol concentrations (Cmin, C4h, Cmax and AUC) at month 2. Discussion This study is of global importance as it provides critical information regarding safe coadministration of B/F/TAF and FHT, both of which are life‐saving therapies for trans women with HIV.
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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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.040 | 0.011 |
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".