Cytoplasmic Clusterin Expression Is Associated with Longer Survival in Patients with Resected Non–Small Cell Lung Cancer
Bibliographic record
Abstract
BACKGROUND: Clusterin is a glycoprotein that has been implicated in many processes, including apoptosis, cell cycle regulation, and DNA repair. Previous studies have examined the prognostic value of clusterin expression in various malignancies. In the present study, we examined clusterin staining in tumors resected from patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: Tumor specimens were obtained for 113 patients with completely resected NSCLC from paraffin-embedded tissue microarrays and stained with an antibody specific for clusterin. Staining patterns were observed and graded based on intensity and then correlated with clinical data. RESULTS: Positive cytoplasmic clusterin staining was observed in 44 patients, and weak/negative staining was observed in 62 patients. Patients who had tumors that stained positive for cytoplasmic clusterin had significantly longer survival in multivariate analysis (hazard ratio 0.487, 95% confidence interval 0.27-0.89). A correlation was also observed for recurrence-free survival, which approached statistical significance (hazard ratio 0.345, 95% confidence interval 0.12-1.02). In univariate analysis, patients with clusterin-positive tumors had a 63% 3-year survival, whereas patients with clusterin-negative tumors had a 42% 3-year survival (P = 0.0108); clusterin-positive tumors also had significantly less recurrence (P = 0.0231). CONCLUSIONS: Cytoplasmic clusterin staining is present in a substantial number of NSCLC tumors and may be a biomarker for longer survival in patients with surgically resected NSCLC.
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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 | 0.001 |
| 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".