Ibalizumab Plus an Optimized Background Regimen in Treatment-Experienced People Living With Multidrug-Resistant HIV-1: A Phase 3, Multicenter, Expanded Access Study
Bibliographic record
Abstract
BACKGROUND: Patients infected with multidrug-resistant (MDR) HIV-1 have limited treatment options and poor clinical outcomes. For effective suppression of viral replication, regimens with distinct mechanisms of action and nonoverlapping patterns of resistance are needed. SETTING: Studies of post-attachment inhibitor ibalizumab plus optimized background regimen (OBR) are needed to evaluate efficacy and safety of long-term use in patients with MDR HIV-1, potentially providing more treatment options. METHODS: TMB-311 was a multicenter, open-label, expanded access phase 3 study that provided a compassionate bridge to commercial availability of ibalizumab for patients with and without prior exposure to drug. RESULTS: In patients with prior exposure to ibalizumab, 23/39 (59%) had viral load (VL) <50 RNA copies/mL at study initiation and 26/34 (76%) had VL <50 copies/mL at Week 24. In ibalizumab-naïve patients receiving compassionate access, 0/38 (0%) had VL <50 copies/mL at study initiation compared to 11/24 (46%) at Week 24. Mean CD4+ cell counts increased from Baseline to Week 24 across both patient groups. Rates of serious treatment-emergent adverse events (TEAEs) up to Week 120 were low. Discontinuations due to TEAEs were 0% in the patients with prior ibalizumab exposure and 8% in those who were ibalizumab-naïve. CONCLUSIONS: Long-term ibalizumab treatment in combination with an OBR was considered safe and well tolerated with no new safety signals identified in people living with MDR HIV-1. Additionally, ibalizumab-naïve patients experienced notable and early reductions in viral load with sustained increases in CD4+ cell counts over 24 weeks.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 |
| 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".