Mucin-Producing Adenocarcinoma of the Lung
Bibliographic record
Abstract
OBJECTIVE: To determine the prognostic value of thin-section computed tomography (CT) findings in patients with mucin-producing adenocarcinoma (MPA) of the lung. METHODS: The study included 48 patients with pathologically proven MPA who had thin-section CT before treatment. The CT findings were correlated with the histopathologic findings and with disease-free survival on follow-up in all patients. RESULTS: Computed tomography findings identified in patients with MPA of the lung included an air bronchogram (n = 37, 77.1%), areas of ground-glass attenuation (n = 36, 75.0%), areas of air-space consolidation (n = 36, 75.0%), interlobular septal thickening (n = 33, 68.8%), bubble-like lucencies (n = 23, 47.9%), centrilobular nodules (n = 22, 45.8%), and mucus filling of airways (n = 19, 39.6%). Twenty-two (45.8%) of the 48 patients had intrapulmonary metastases. Centrilobular nodules (odds ratio [OR] = 6.7, 95% confidence interval: 1.1-41.4; P < 0.05) and mucus filling of airways (OR = 14.4, 95% 95% confidence interval: 2.0-102.7; P < 0.01) on thin-section CT were independently associated with an increased likelihood of intrapulmonary metastases. The 5-year disease-free survival rates were 67.9% and 38.4% for patients without and with intrapulmonary metastases, respectively (P < 0.05). The presence of centrilobular nodules (relative risk = 10.5, 95% confidence interval: 1.8-59.3; P < 0.01) on thin-section CT was an independent predictor of poor prognosis. CONCLUSION: Centrilobular nodules on CT are associated with a higher prevalence of intrapulmonary metastases and a poor prognosis in patients with MPA of the lung.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".