Prognostic significance of BAG-1 expression in nonsmall cell lung cancer
Bibliographic record
Abstract
The purpose of this study was to evaluate the expression of BAG-1 in a cohort of patients with nonsmall cell lung cancer (NSCLC). The intensity and subcellular distribution of BAG-1 expression were correlated with overall survival. Tumor samples were collected from 85 patients diagnosed with NSCLC between 1993-1995 in St. John's, Newfoundland. Expression of BAG-1 was determined by immunohistochemistry using polyclonal anti-BAG-1 antibody. There was significant variation in the immunohistochemical staining patterns of BAG-1, including nonstaining and staining of either the cytoplasm, nucleus or both. Univariate Cox regression analysis showed that those patients whose tumor overexpressed BAG-1 had a significant reduction in the risk of death (hazard ratio = 0.53, p = 0.03). The survival advantage of patients with BAG-1 overexpression tumor was also demonstrated by Kaplan-Meier analysis and log-rank tests (median survival 30.10 months versus 17.04 months, p = 0.05). In addition, multivariate Cox regression analysis showed that patients whose tumor exhibited intense cytoplasmic staining had a further reduction of the risk of death (hazard ratio = 0.42, p = 0.03) and this effect was independent of age, stage and histology. All stages were included in the analysis. Our preliminary data strongly indicate that further investigation is warranted to better define the role of BAG-1 as an independent prognostic factor in NSCLC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".