Efficacy and Safety of 2 Fixed Doses of Ibalizumab Plus Optimized Background Regimen in Treatment-Experienced HIV-Positive Individuals
Bibliographic record
Abstract
BACKGROUND: Sustained viral suppression in patients with multidrug-resistant (MDR) HIV infection remains difficult; accordingly, agents targeting different steps in the HIV life cycle are needed. Ibalizumab, a humanized immunoglobulin G4 monoclonal antibody, is a cluster of differentiation (CD4)-directed postattachment inhibitor. METHODS: In this phase 2b study, 113 patients with MDR HIV-1 and limited treatment options were assigned an optimized background regimen (OBR) and randomized to either 800 mg ibalizumab every 2 weeks (q2wk; n = 59) or 2000 mg ibalizumab every 4 weeks (q4wk; n = 54) up to week 24. RESULTS: Viral loads (VL) below the detection limit were achieved in 44% and 28% of patients in the 800 mg q2wk and 2000 mg q4wk groups, respectively, at week 24. Mean (SD) VL (log 10 copies/mL) decreased from Baseline [4.6 (0.8), 800 mg q2wk; 4.7 (0.7), 2000 mg q4wk] to week 2, with the reduction maintained through week 24 [2.9 (1.5), 800 mg q2wk; 3.2 (1.4), 2000 mg q4wk]. Baseline CD4 + counts were 80.5 and 54.0 cells/μL in the 800 mg q2wk and 2000 mg q4wk groups, respectively. Mean CD4 + T-cell count was increased at week 24 in both groups. No serious adverse events were related to ibalizumab. CONCLUSIONS: In heavily treatment-experienced patients with HIV (PWH) at a more advanced baseline disease severity, clinically significant response rates at week 24 were achieved with ibalizumab plus OBR. Ibalizumab's unique mechanism of action and lack of cross-resistance to other antiretroviral agents make it an important component of combination treatment regimens for PWH with limited treatment options.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".