Safety, Tolerability, and Efficacy of Darunavir (TMC114) with Low-Dose Ritonavir in Treatment-Experienced, Hepatitis B or C Co-infected Patients in POWER 1 and 3
Bibliographic record
Abstract
PURPOSE: This subanalysis examines the safety and efficacy of darunavir with low-dose ritonavir (DRV/r) in hepatitis B or C virus (HBV or HCV) co-infected patients in POWER 1 and 3 trials. METHOD: POWER 1 and 3 enrolled treatment-experienced, HIV-infected patients with > or =1 primary protease inhibitor (PI) mutation and HIV-1 RNA >1,000 copies/mL. All patients received an optimized background regimen plus either control PI (almost all ritonavir boosted) or one of four DRV/r doses (POWER 1) or DRV/r 600/100 mg bid (POWER 3). Patients with active HBV or HCV co-infection who did not require treatment for hepatitis were included. Safety parameters were evaluated. RESULTS: Of 634 DRV/r and 63 control (97% ritonavir boosted) patients assessed, 13% and 16%, respectively, had active co-infection. In both groups, more patients with active co-infection than without co-infection had liver-related adverse events (AEs). These AEs were mainly asymptomatic liver transaminase elevations, although changes were slightly less in the DRV/r group (DRV/r, 13% vs. 8%; control PI, 20% vs. 12%). Only two patients (one per treatment arm) discontinued therapy due to grade 3 or 4 alanine and aspartate transaminase elevations. CONCLUSION: DRV/r was generally well tolerated in treatment-experienced, HBV or HCV co-infected patients. No differences in liver-related AEs were observed between treatment groups.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".