Spirometry performed as part of the Manchester community-based lung cancer screening programme detects a high prevalence of airflow obstruction in individuals without a prior diagnosis of COPD
Bibliographic record
Abstract
Background COPD is a major cause of morbidity and mortality in populations eligible for lung cancer screening. We investigated the role of spirometry in a community-based lung cancer screening programme. Methods Ever smokers, age 55–74, resident in three deprived areas of Manchester were invited to a ‘Lung Health Check’ (LHC) based in convenient community locations. Spirometry was incorporated into the LHCs alongside lung cancer risk estimation (Prostate, Lung, Colorectal and Ovarian Study Risk Prediction Model, 2012 version (PLCO M2012 )), symptom assessment and smoking cessation advice. Those at high risk of lung cancer (PLCO M2012 ≥1.51%) were eligible for annual low-dose CT screening over two screening rounds. Airflow obstruction was defined as FEV 1 /FVC<0.7. Primary care databases were searched for any prior diagnosis of COPD. Results 99.4% (n=2525) of LHC attendees successfully performed spirometry; mean age was 64.1±5.5, 51% were women, 35% were current smokers. 37.4% (n=944) had airflow obstruction of which 49.7% (n=469) had no previous diagnosis of COPD. 53.3% of those without a prior diagnosis were symptomatic (n=250/469). After multivariate analysis, the detection of airflow obstruction without a prior COPD diagnosis was associated with male sex ( adj OR 1.84, 95% CI 1.37 to 2.47; p<0.0001), younger age (p=0.015), lower smoking duration (p<0.0001), fewer cigarettes per day (p=0.035), higher FEV 1 /FVC ratio (<0.0001) and being asymptomatic ( adj OR 4.19, 95% CI 2.95 to 5.95; p<0.0001). The likelihood of screen detected lung cancer was significantly greater in those with evidence of airflow obstruction who had a previous diagnosis of COPD ( adj OR 2.80, 95% CI 1.60 to 8.42; p=0.002). Conclusions Incorporating spirometry into a community-based targeted lung cancer screening programme is feasible and identifies a significant number of individuals with airflow obstruction who do not have a prior diagnosis of COPD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".