Which lung cancer histologies are associated with emphysema on chest computed tomography?
Bibliographic record
Abstract
BACKGROUND: Multiple studies have demonstrated increased risk of lung cancer in the presence of emphysema, independent of smoking history and airflow obstruction, but the relationship of emphysema to specific histologic subtypes remains uncertain. OBJECTIVE: To determine the extent to which emphysema on chest computed tomography (CT) is associated with lung cancer histology. METHODS: Cross-sectional analysis of consecutive lung cancer patients referred to the Jewish General Hospital was performed (2001-2009). All those with demographic data, smoking history (pack-years), documented histology and chest CT were included. Emphysema was graded on CT by three readers, using a standardized rubric. Odds of each lung cancer subtype were compared between patients with and without emphysema, and adjusted for age, sex and smoking history by multiple logistic regression. RESULTS: Complete data were available for 498 lung cancer patients (mean age 68 years; 221 [44%] female; 78 [16%] never smokers; 263 [53%] without emphysema on CT). The most common histologies were adenocarcinoma (242 [49%]), squamous (71 [14%]), undifferentiated (48 [10%]) and small cell carcinoma (42 [8%]). The remaining 19% included bronchioloalveolar, large cell, pleomorphic and basaloid carcinomas. Presence of emphysema was associated with increased odds of squamous (OR 3.1 95%CI 1.8-5.3) and small cell (OR 2.1 95%CI 1.1-4.1) carcinoma. After adjustment for age, sex and smoking history, emphysema was associated with squamous (OR 2.7 95%CI 1.5-4.9) but not small cell (OR 1.5 95%CI 0.8-3.1) carcinoma. CONCLUSIONS: Relative to other histologic subtypes, the odds of squamous carcinoma were significantly increased among lung cancer patients with emphysema after adjustment for smoking history. This was not true of small cell carcinoma, although confidence intervals were wide so an association cannot be entirely excluded. Other common subtypes were not independently associated with emphysema.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".