Interim data from a long-term safety, tolerability, and efficacy study of liposomal amikacin for inhalation in cystic fibrosis patients with chronic <i>pseudomonas aeruginosa</i> infection
Bibliographic record
Abstract
Rationale: Liposomal amikacin for inhalation (LAI) is a novel lipid formulation being developed to treat chronic Pseudomonas aeruginosa (Pa) infection in cystic fibrosis (CF) patients (pts). CLEAR-110 is an extension study of a completed LAI versus tobramycin inhalation solution comparator study (CLEAR-108) to evaluate long-term safety, tolerability, and efficacy of once-daily (QD) LAI. Methods : The study was conducted in 54 centers in 16 countries in Europe and Canada. Eligible pts from CLEAR-108 received LAI 590 mg QD via a PARI Investigational eFlow ® Nebulizer System (28 days on/off treatment) for 6 cycles (12 months) and could re-consent for additional 6 cycles (12 total [∼2 yrs]). Patients were evaluated every 28 days. Results: A total of 266 pts completed CLEAR-108; 206 (77%) enrolled in CLEAR-110 and received ≥1 dose of LAI. At the time of the interim data, 98 pts had completed 6 cycles of treatment. Overall, data show that LAI was well tolerated, and no unexpected adverse events (AEs) were observed. At the end of treatment of cycle 6, mean % increase from baseline in forced expiratory volume in 1 second (FEV1 [L]) was 3.65 % and 0.78% at the end of off-treatment period of the 6th cycle. Conclusion: These interim data demonstrate that LAI was well tolerated during 6 cycles, with AEs being consistent with those expected in a population of CF patients receiving inhaled medicines. Additionally, pts receiving 6 cycles of LAI showed mean increase in relative change in FEV1 that was sustained during both on- and off-treatment months, showing longer-term durability of treatment effect.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".