853. Real-World Persistency of Patients Receiving Tenofovir-Based Pre-Exposure Prophylaxis for the Prevention of HIV Infection in the US
Bibliographic record
Abstract
Abstract Background Once-daily oral tenofovir-based combinations as pre-exposure prophylaxis (PrEP) have shown to be an effective biomedical HIV prevention strategy for populations at-risk of acquiring HIV-1. However, low adherence can lead to poor effectiveness. This study described the characteristics of commercially-insured US PrEP users. 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) or emtricitabine/tenofovir alafenamide (FTC/TAF) as daily PrEP. Users had ≥6 months 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. For FTC/TDF users, proportion of days covered (PDC), persistence, treatment breaks, and switching were described during the follow-up period, which spanned from index to the earliest of disenrollment or end of data. Non-persistence was defined as a >90-day gap from last day of supply, with re-initiation after this gap indicating treatment break. For PDC and persistence, follow-up was censored at HIV infection, defined by both multi-class ART initiation and HIV diagnosis. Results In total 24,232 FTC/TDF and 1,187 FTC/TAF users were identified. Overall, mean age was 35.1 years and 94.5% were male (Table 1). Mean [median] length of follow-up was longer for FTC/TDF (504 [390] days) than FTC/TDF users (77 [70] days). On average, FTC/TDF users had 9.0 dispensings with 38.3 days of supply per dispensing over follow-up; 11.1% had ≥1 treatment break (mean length, 249 days). Among those initiated on FTC/TDF, 10.8% switched to FTC/TAF. The mean PDC for FTC/TDF users at 6 and 12 months was 0.74 and 0.67, respectively, corresponding to 63.7% and 57.9% of patients with PDC ≥0.70 (Figure 1). Persistence to FTC/TDF at 6 and 12 months was 70.2% and 57.4%, respectively (Figure 2). Table 1. Baseline Demographics and Clinical Characteristics of PrEP Users by Regimen Figure 1. Proportion of Days Covered of FTC/TDF Users Figure 2. Kaplan-Meier Persistence Rates of FTC/TDF Users Conclusion Patient characteristics of PrEP users are broadly similar between regimens, though switching from FTC/TDF to FTC/TAF is common. FTC/TDF users had lower real-world PDC and persistence than in recent clinical trials (DISCOVER and HPTN 083). Disclosures Alan Oglesby, MPH, GlaxoSmithKline (GSK) (Employee, Shareholder) Guillaume Germain, MSc, ViiV Healthcare (Other Financial or Material Support, I am an employee of Groupe d’analyse, Ltée, a consulting company that provided paid consulting services to ViiV Healthcare for the conduct of the present study.) Francois Laliberte, MA, Viiv (Research Grant or Support) Staci Bush, NP, GlaxoSmithKline (GSK) (Employee, Shareholder) Heidi Swygard, MD, ViiV Healthcare (Employee) Sean MacKnight, MScPH, Analysis Group (Employee) Annalise Hilts, BA, Analysis Group, Inc. (Employee) Mei Sheng Duh, MPH, ScD, 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".