The Extrapulmonary Effects of Cystic Fibrosis Transmembrane Conductance Regulator Modulators in Cystic Fibrosis
Bibliographic record
Abstract
The effects of cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulators on lung function, pulmonary exacerbations, and quality of life have been well documented. However, CF is a multiorgan disease, and therefore an evidence base is emerging on the systemic effects of CFTR modulators beyond the pulmonary system. This is of great clinical importance, as many of these studies provide proof of concept that CFTR modulators might be used one day to prevent or treat extrapulmonary manifestations stemming from CFTR dysfunction. In this concise review of the literature, we summarize the results of key publications that have evaluated the effects of CFTR modulators on weight and growth, pancreatic function, the gastrointestinal and hepatobiliary systems, sinus disease, bone disease, exercise tolerance, fertility, mental health, and immunity. Although many of these studies have reported beneficial extrapulmonary effects related to the use of ivacaftor (IVA) in patients with CF with at least one gating mutation, most of the evidence is low or very low quality, given the limited number of patients evaluated and the lack of control groups. Based on an even smaller number of studies evaluating the extrapulmonary effects of lumacaftor-IVA, the benefits are less clear. Although limited, these studies may provide the basis for future clinical trials to evaluate CFTR modulators on the extrapulmonary manifestations of CF.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".