Clinical Mechanism of the Cystic Fibrosis Transmembrane Conductance Regulator Potentiator Ivacaftor in G551D-mediated Cystic Fibrosis
Bibliographic record
Abstract
RATIONALE: Ivacaftor is a cystic fibrosis transmembrane conductance regulator (CFTR) potentiator recently approved for patients with CF age 6 and older with the G551D mutation. OBJECTIVES: To evaluate ivacaftor in a postapproval setting and determine mechanism of action and response of clinically relevant markers. METHODS: We conducted a longitudinal cohort study in 2012-2013 in G551D CF patients age 6 and older with no prior exposure to ivacaftor. Study assessments were performed at baseline, 1, 3, and 6 months after ivacaftor initiation. Substudies evaluated mucociliary clearance, β-adrenergic sweat secretion rate, gastrointestinal pH, and sputum inflammation and microbiology Measurements and Main Results: A total of 151 of 153 subjects were prescribed ivacaftor and 88% completed the study through 6 months. FEV1 % predicted improved from baseline to 6 months (mean absolute change, 6.7%; P < 0.001). Similarly, body mass index improved from baseline to 6 months (mean change, 0.8 kg/m(2); P < 0.001). Sweat chloride decreased from baseline to 6 months (mean change, -53.8 mmol/L; 95% confidence interval, -57.7 to -49.9; P < 0.001), reflecting augmented CFTR function. There was significant improvement in hospitalization rate (P < 0.001) and Pseudomonas aeruginosa burden (P < 0.01). Significant improvements in mucociliary clearance (P < 0.001), gastrointestinal pH (P = 0.001), and microbiome were also observed, providing clinical mechanisms underlying the therapeutic benefit of ivacaftor. CONCLUSIONS: Significant clinical and physiologic improvements were observed on initiation of ivacaftor in a broad patient population, including reduced infection with P. aeruginosa. Biomarker studies substantially improve the understanding of the mechanistic consequences of CFTR modulation on pulmonary and gastrointestinal physiology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".