The clinical impact of Lumacaftor-Ivacaftor on structural lung disease and lung function in children aged 6-11 with Cystic Fibrosis in a real-world setting
Bibliographic record
Abstract
Abstract Background: Data from clinical trials of lumacaftor-ivacaftor (LUM-IVA) demonstrate improvements in lung clearance index (LCI) but not in FEV1 in children with Cystic Fibrosis (CF) aged 6-11 years and homozygous for the Phe508del mutation. It is not known whether LUM/IVA use in children can impact the progression of structural lung disease. We sought to determine the real-world impact of LUM/IVA on lung structure and function in children aged 6-11 years. Methods: This real-world observational cohort study was conducted across four paediatric sites in Ireland over 24-months using spirometry-controlled CT scores and LCI as primary outcome measures. Children commencing LUM-/IVA as part of routine care were included. CT scans were manually scored with the PRAGMA CF scoring system and analysed using the automated airway-artery (AA) method. Secondary outcome measures included rate of change of ppFEV1, nutritional indices and exacerbations requiring hospitalisation. Results: Seventy-one participants were recruited to the study, 31 of whom had spirometry-controlled CT performed at baseline, and after one year and two years of LUM/IVA treatment. At two years there was a reduction from baseline in trapped air scores (0.13 to 0.07, p=0.016), but an increase from baseline in the % bronchiectasis score (0.84 to 1.23, p=0.007). There was no change in overall % disease score (2.78 to 2.25, p=0.138). Airway lumen to pulmonary artery ratios (AlumenA ratio) were abnormal at baseline and worsened over the course of the study. In 28 participants, the mean annual change from baseline LCI2.5 (-0.055 (-0.61 to 0.50), p=0.85) measurements over two years were not significant. Improvements from baseline in weight (0.10 (0.06 to 0.15, p<0.0001), height (0.05 (0.02 to 0.09), p=0.002) and BMI (0.09 (0.03 to 0.15) p=0.005) z-scores were seen with LUM/IVA treatment. The mean annual change from baseline ppFEV1 (-2.45 (-4.44 to 2.54), p=0.66) measurements over two years were not significant. Conclusion: In a real-world setting, the use of LUM/IVA over two years in children with CF aged 6-11 resulted in improvements in air trapping on CT but worsening in bronchiectasis scores. Our results suggest that LUM/IVA use in this age group improves air trapping but does not prevent progression of bronchiectasis over two years of treatment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".