Unmasking the true value of cystic fibrosis transmembrane conductance regulator modulators
Bibliographic record
Abstract
Extract The licensing of the triple combination cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy elexacaftor/tezacaftor/ivacaftor (ETI) in late 2019 in the United States (US) was the translation of impressive science with the potential to change the disease course for the approximately 90% of people with cystic fibrosis (pwCF) who have responsive CFTR gene variants. However, the true impact of the therapy was obscured by the SARS-CoV-2 pandemic in early 2020, that prompted global public health restrictions that abated some of the main drivers of infective respiratory exacerbations in pwCF including a reduction in all circulating respiratory viruses. It is therefore welcome to see this report by Stephenson et al. [1] who utilise CF patient registry data in the US and Canada to attempt to disentangle the relative impact of these two major events on the health of pwCF. This elegantly conducted study concludes that ETI had twice the effect of public health interventions in reducing pulmonary exacerbations.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".