Progression of Airway Dysplasia and C-Reactive Protein in Smokers at High Risk of Lung Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RATIONALE: Chronic inflammation has been implicated in the development of airway dysplasia and lung cancer. It is unclear whether circulating biomarkers of inflammation could be used to predict progression of airway dysplasia. OBJECTIVE: We determined whether circulating levels of C-reactive protein (CRP) or other inflammatory biomarkers could predict progression of bronchial dysplasia in smokers over 6 mo. METHODS: The plasma levels of CRP, interleukins 6 and 8, and monocyte chemoattractant protein 1 were measured at baseline in 65 ex- and current smokers who had at least one site of bronchial dysplasia > 1.2 mm in size. Additional bronchial biopsies were taken after 6 mo from the same sites where dysplastic lesions were discovered at baseline. Progressive dysplastic lesions were defined as worsening of the dysplastic lesion by at least two grades or development of new dysplastic lesions. RESULTS: Half of the participants developed progressive dysplastic lesions after 6 mo. The baseline CRP levels in these participants were 64% higher than those without progressive disease (p = 0.027). Only one of eight (13%) participants with CRP < or = 0.5 mg/L developed progressive disease, whereas 31 of 57 (54%) participants with CRP > 0.5 mg/L developed progressive disease (p = 0.011). The odds of developing progressive disease were 9.6-fold higher in the latter than in the former group. CONCLUSION: Plasma CRP, in concert with lung function and pack-years of smoking, appears to have excellent predictive powers in identifying participants with bronchial dyplastic lesions whose lesions progress to more advanced stages of dysplasia.
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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 | 0.002 | 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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it