Diagnoses and treatments for participants with interstitial lung abnormalities detected in the Yorkshire Lung Screening Trial
Bibliographic record
Abstract
INTRODUCTION: Interstitial lung abnormalities (ILA) are relatively common incidental findings in participants undergoing low-dose CT screening for lung cancer. Some ILA are transient and inconsequential, but others represent interstitial lung disease (ILD). Lung cancer screening therefore offers the opportunity of earlier diagnosis and treatment of ILD for some screening participants. METHODS: The prevalence of ILA in participants in the baseline screening round of the Yorkshire Lung Screening Trial is reported, along with the proportion referred to a regional ILD service, eventual diagnoses, outcomes and treatments. RESULTS: Of 6650 participants undergoing screening, ILA were reported in 169 (2.5%) participants. Following review in a screening review meeting, 56 participants were referred to the ILD service for further evaluation (0.8% of all screening participants). 2 participants declined referral, 1 is currently awaiting review and the remaining 53 were confirmed as having ILD. Eventual diagnoses were idiopathic pulmonary fibrosis (n=14), respiratory bronchiolitis ILD (n=4), chronic hypersensitivity pneumonitis (n=2), connective tissue disease/rheumatoid arthritis-related ILD (n=4), asbestosis (n=1), idiopathic non-specific interstitial pneumonia (n=1), sarcoidosis (n=1) and pleuroparenchymal fibroelastosis (n=1). Twenty five patients had unclassifiable idiopathic interstitial pneumonia. Overall, 10 people received pharmacotherapy (7 antifibrotics and 3 prednisolone) representing 18% of those referred to the ILD service and 0.15% of those undergoing screening. 32 people remain under surveillance in the ILD service, some of whom may require treatment in future. DISCUSSION: Lung cancer screening detects clinically significant cases of ILD allowing early commencement of disease-modifying treatment in a proportion of participants. This is the largest screening cohort to report eventual diagnoses and treatments and provides an estimate of the level of clinical activity to be expected by ILD services as lung cancer screening is implemented. Further research is needed to clarify the optimal management of screen-detected ILD. TRIAL REGISTRATION NUMBER: ISRCTN42704678.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".