1544. HIV Following Oral Pre-Exposure Prophylaxis (PrEP) Initiation
Bibliographic record
Abstract
Abstract Background Once-daily oral tenofovir-based combinations as pre-exposure prophylaxis (PrEP) are effective biomedical HIV prevention strategies. Still, low adherence and/or persistence can lead to decreased efficacy. This study describes the characteristics and HIV incidence in commercially-insured US oral PrEP users. Usage pattern results were previously presented. Methods This retrospective study used IQVIA™ PharMetrics Plus data (1/1/2015–3/31/2020) to identify adults newly initiated (index date) on emtricitabine/tenofovir disoproxil fumarate (FTC/TDF) as daily PrEP. Users had ≥ 6 months (mos.) of continuous enrollment pre-index (baseline); those diagnosed with HIV or with antiretroviral therapy (ART) use during baseline were excluded. User characteristics were described during the baseline period. Users with both an HIV diagnosis and ART dispensing post-index were considered to have acquired HIV. A sensitivity analysis was conducted using ≥ 2 dispensings of ART on separate days to define HIV infection, regardless of documented HIV diagnosis. Time to HIV infection from the index date and from the latest PrEP dispensing was reported. A separate analysis without ≥ 6 mos. of continuous enrollment pre-index was performed. Results In total, 24,232 FTC/TDF users were identified (Table 1). Mean [median] length of follow-up was 504 [390] days. By 3 mos. after initiation, 0.3% of FTC/TDF users had acquired HIV, which increased to 0.5% by 12 mos. (Table 2). The mean [median] time to detected HIV infection from index was 235 [95] days, and from the latest PrEP dispensing was 149 [29] days. 60.3% of FTC/TDF users with an HIV diagnosis had PrEP on hand at the time HIV was detected. In the sensitivity analysis requiring only ≥ 2 ART dispensings, rates were slightly higher (3 mos., 0.4%; 12 mos., 0.7%). In the analysis which removed the 6-month pre-index coverage requirement (Table 3), rates were also higher (3 mos., 2.2%; 12 mos., 2.5%). Conclusion HIV diagnosis following oral PrEP initiation is infrequent with higher incidence in those whose first covered healthcare encounter coincides with PrEP initiation. That a majority diagnosed with HIV had PrEP available at time of detection suggests challenges unexplained by access. Further research is needed to limit HIV acquisition despite access to oral PrEP. Disclosures Aimee A. Metzner, PharmD, AAHIVP, ViiV Healthcare: Full-time employee (salary/benefits/etc.)|ViiV Healthcare: Stocks/Bonds Guillaume Germain, MSc, ViiV Healthcare: I am an employee of Analysis Group, a consulting company that received research funds from ViiV Healthcare to conduct this study. François Laliberté, MS, GSK: Grant/Research Support Alan Oglesby, MPH, GlaxoSmithKline: Employment|GlaxoSmithKline: Stocks/Bonds Heidi Swygard, MD, ViiV Healthcare: Employee of ViiV Healthcare|ViiV Healthcare: Stocks/Bonds Sean MacKnight, MScPH, ViiV: I am an employee of Analysis Group, a consulting company that received research funds from ViiV to conduct this study. Annalise Hilts, BA, ViiV (I am an employee of Analysis Group, a consulting company that received research funds from ViiV to conduct this study.): Grant/Research Support Mei Sheng Duh, MPH, ScD, Analysis Group, Inc.: Mei Sheng Duh is an employee of Analysis Group, Inc., a consulting company that received funding from GSK to conduct this study|ViiV Healthcare: Grant/Research Support
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.009 | 0.002 |
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".