Lung Cancer in Patients with Chronic Obstructive Pulmonary Disease: Incidence and Predicting Factors
Bibliographic record
Abstract
RATIONALE: Little is known about the clinical factors associated with the development of lung cancer in patients with chronic obstructive pulmonary disease (COPD), although airway obstruction and emphysema have been identified as possible risk factors. OBJECTIVES: To explore incidence, histologic type, and factors associated with development of lung cancer diagnosis in a cohort of outpatients with COPD attending a pulmonary clinic. METHODS: A cohort of 2,507 patients without initial clinical or radiologic evidence of lung cancer was followed a median of 60 months(30–90). At baseline, anthropometrics, smoking history, lung function,and body composition were recorded. Time to diagnosis and histologic type of lung cancer was then registered. Cox analysis was used to explore factors associated with lung cancer diagnosis. MEASUREMENTS AND MAIN RESULTS: A total of 215 of the 2,507 patients with COPD developed lung cancer (incidence density of 16.7 cases per 1,000 person-years). The most frequent type was squamous cell carcinoma (44%). Lung cancer incidence was lower in patients with worse severity of airflow obstruction. Global Initiative for Chronic Obstructive Lung Disease Stages I and II, older age, lower body mass index,and lung diffusion capacity of carbon monoxide less than 80%were associated with lung cancer diagnosis. CONCLUSIONS: Incidence density of lung cancer is high in outpatients with COPD and occurs more frequently in older patients with milder airflow obstruction (Global Initiative for Chronic Obstructive Lung Disease Stages I and II) and lower body mass index. A lung diffusion capacity of carbon monoxide less than 80% is associated with cancer diagnosis. Squamous cell carcinoma is the most frequent histologic type. Knowledge of these factors may help direct efforts for early detection of lung cancer and disease management.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".