Safety and effectiveness of lumacaftor-ivacaftor in adults with cystic fibrosis: A single-center Canadian experience
Bibliographic record
Abstract
RATIONALE: Lumacaftor-ivacaftor (LUM-IVA) was approved for use in Canada in January 2016. Observational studies have reported a higher incidence of treatment-emergent adverse events (AEs) leading to treatment discontinuation compared to clinical trials. There is still limited data about long-term tolerability and rates of discontinuation in patients who would not have met clinical trial eligibility criteria.OBJECTIVE: To assess the long-term safety and effectiveness of LUM-IVA in a real-world setting.METHODS: We conducted a single-center retrospective cohort study at St. Paul’s Hospital (Vancouver, Canada). We tracked changes in percent-predicted FEV1 (ppFEV1), body mass index (BMI), sweat chloride concentration, blood pressure (BP) and pulmonary exacerbations pre- and post-initiation of LUM-IVA. We noted AEs and treatment discontinuations.RESULTS: Of 22 patients who started on LUM-IVA as part of routine clinical care, 10 (45%) discontinued therapy after a median of 3.3 months. At initiation, median (IQR) ppFEV1 was 40.1% (32.7%, 55.9%). Respiratory-related symptoms were the most common AEs (59%). We observed a statistically significant increase in BP (p = 0.004). Respiratory-related symptoms and increased BP were the most common reasons for treatment discontinuation, including one instance of hypertensive emergency. There was no change in the median rate of ppFEV1 decline or BMI change despite a statistically significant decrease in sweat chloride concentration 3 months’ post-initiation (p < 0.001).CONCLUSION: The rate of LUM-IVA discontinuation in this adult cystic fibrosis (CF) cohort was high and similar to other observational studies, but we also report cases of increased BP leading to treatment discontinuation. We recommend long-term monitoring of blood pressure for patients on LUM-IVA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".