Real-world effectiveness, safety, and health-related quality of life in people living with HIV receiving bictegravir/emtricitabine/tenofovir alafenamide—12-month results of the BICSTaR French cohort
Bibliographic record
Abstract
Objectives: BICSTaR is a multinational, prospective, observational study that aimed to evaluate bictegravir/emtricitabine/tenofovir alafenamide (B/F/TAF) in HIV treatment-naïve (TN) and treatment-experienced (TE) participants in routine clinical practice. Methods: Month 12 analysis of the French cohort with respect to virologic effectiveness, drug-related adverse events (DRAEs), emergence of resistance, body weight, and patient-reported outcomes using the HIV Symptom Index and the HIV Treatment Satisfaction Questionnaire. Results: A total of 240 participants initiated B/F/TAF in January-July 2019 (56 TN, 184 TE), 79% of whom were male, with a median age of 50 years. At baseline, 63% (TN: 46%, TE: 68%) presented with comorbidities. At month 12, HIV-1 RNA was <50 cp/mL in 92% (43/47) of TN and 96% (134 of 139) of TE in missing = excluded analysis (discontinuation = failure analysis: TN: 92% [43 of 47], TE: 92% [134 of 146]). No major mutations associated with B/F/TAF resistance emerged. A total of 7% (16 of 240) discontinued B/F/TAF, including 4% (10 of 240) due to DRAEs and none for virologic reasons. DRAEs were reported in 13% (30 of 240) (no renal DRAE). The median changes in body weight were +6.5 kg in TN and +1.0 kg in TE. The number of bothersome symptoms decreased in the TN group, and treatment satisfaction significantly increased in the TE group. Conclusions: These French real-world data confirm the effectiveness, safety, and tolerability of B/F/TAF in TN and TE participants with a high prevalence of comorbidities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".