A randomized phase 3 study of the efficacy and safety of reslizumab in subjects with asthma with elevated eosinophils
Bibliographic record
Abstract
Introduction: Reslizumab (RES), a humanized anti-human interleukin-5, is under development for patients with moderate to severe, persistent asthma with elevated eosinophils (EOS). Objectives: To compare the efficacy and safety of RES vs placebo (PBO) in subjects with asthma and elevated EOS. Methods: This was a multicenter, PBO-controlled, double-blind, 16-week study ( NCT01270464 ). Subjects (N=311) were 12-75 years of age with uncontrolled asthma on at least medium ICS, had an asthma control questionnaire (ACQ) score ≥1.5, and blood EOS level of ≥400/µL. Randomization was to intravenous RES 0.3 or 3.0 mg/kg or PBO once every 4 weeks. Efficacy variables included pre-dose, pre-bronchodilator pulmonary function (FEV 1 , primary variable) and ACQ scores. Results: Following 16 weeks of therapy, RES (0.3 and 3.0 mg/kg) significantly improved overall FEV 1 ( P ≤0.024) and ACQ score ( P ≤0.033) vs PBO (treatment difference vs PBO: 115 and 160 mL, FEV 1 and 0.238 and 0.359 ACQ, respectively); improvements for RES 3.0 mg/kg vs PBO were observed in both measures (153 mL, FEV 1 ; -0.283, ACQ) as early as 4 weeks ( P ≤0.015) and maintained over the duration of the study. Clinically meaningful improvements in FVC (130 mL, P =0.017) and FEF 25-75% (0.233 L/s; P =0.055) were noted only for the 3.0 mg/kg dose. The most commonly reported AEs in any treatment group were asthma, headache, nasopharyngitis, bronchitis, and upper respiratory tract infection. Conclusion: In subjects with elevated blood EOS, 4 monthly doses of RES were well tolerated and associated with improvements in pulmonary function and patient-reported asthma control on top of standard-of-care therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".