S121 Lung Clearance Index to Evaluate the Effect of Ivacaftor on Lung Function in Subjects with CF Who Have the G551D-CFTR Mutation and Mild Lung Disease
Bibliographic record
Abstract
Background Ivacaftor has been shown to lead to significant improvement in lung function, exacerbation rate, weight gain and quality of life in adolescents and adults with CF and the G551D-CFTR mutation. Objectives Drugs targeting the basic defect of CF may hold potential for patients with early stage disease, but establishing benefit is more difficult. If FEV1 is normal, a more sensitive test may be useful. LCI has been shown to become abnormal at an earlier stage of disease than FEV1 and thus may be a more sensitive outcome measure in this group of patients. Methods This Phase 2, randomised, double-blind, placebo-controlled, multicenter, crossover study evaluated the effect of ivacaftor on LCI derived from multibreath washout of SF6 using an Innocor device. Subjects were ≥6 years with the G551D-CFTR mutation, FEV1 >90% predicted, and LCI >7.4 (upper limit of normal). Ivacaftor 150 mg or placebo was administered twice daily for two 4-week periods with a 4-week washout in between. Results Twenty-one subjects were randomised and 20 received a dose of ivacaftor. Seventeen subjects completed both periods. Mean (SD) age was 16.6 (10.9) years. Mean (SD) baseline LCI was 9.0 (1.5). The treatment effect of ivacaftor for adjusted mean change from baseline in LCI at Day 29 was –2.1 (P=0.0004). Mean (SD) baseline FEV1 was 97.2% predicted (10.6%). Treatment difference for the mean change from baseline in FEV1 at Day 29 was 7.0 percentage points (P=0.0117). Treatment difference for the mean change from baseline in sweat chloride at Day 29 was –45.9 mmol/L (P<0.0001). Treatment effect for the change from baseline in pooled CFQ-R Respiratory Domain score was 4.1 points versus placebo (P=0.4020). In the ivacaftor period, AEs and SAEs were reported in 13 and 2 subjects, respectively. In the placebo period, AEs and SAEs were reported in 15 and 1 subject, respectively. Conclusions In CF patients with mild lung disease, ivacaftor improved ventilation inhomogeneity as measured by LCI and respiratory function as measured by percent predicted FEV1. LCI is more sensitive to change in this mildly affected group of subjects and may be a useful outcome measure for future interventional trials in such patients.
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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) | 0.002 | 0.001 |
| 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) | 0.003 | 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".