Routine Elastin Staining in Surgically Resected Colorectal Cancer
Bibliographic record
Abstract
Venous invasion (VI) is a powerful yet underreported prognostic factor in colorectal cancer (CRC). Its detection can be improved with an elastin stain. We evaluated the impact of routine elastin staining on VI detection in resected CRC and its relationship with oncologic outcomes. Pathology reports from the year before (n=145) and the year following (n=128) the implementation of routine elastin staining at our institution were reviewed for established prognostic factors, including VI. A second review, using elastin stains, documented the presence/absence, location, number, and size of VI foci. The relationship between VI and oncologic outcomes was evaluated for original and review assessments. VI detection rates increased from 21% to 45% following implementation of routine elastin staining (odds ratio [OR]=3.1; 95% confidence interval [CI]: 1.8-5.3; P<0.0001). The second review revealed a lower VI miss rate postimplementation than preimplementation (22% vs. 48%, respectively; P=0.007); this difference was even greater for extramural VI-positive cases (9% vs. 38%, respectively; P=0.0003). Missed VI cases postimplementation had fewer VI foci per missed case (P=0.02) and a trend towards less extramural VI than those missed preimplementation. VI assessed with an elastin stain was significantly associated with recurrence-free survival (P=0.003), and cancer-specific survival (P=0.01) in contrast to VI assessed on hematoxylin and eosin alone (P=0.053 and 0.1, respectively). The association between VI and hematogenous metastasis was far stronger for elastin-detected VI (OR=11.5; 95% CI: 3.4-37.1; P<0.0001) than for hematoxylin and eosin-detected VI (OR=3.7; 95% CI: 1.4-9.9; P=0.01). Routine elastin staining enhances VI detection and its ability to stratify risk in CRC and should be considered for evaluation of CRC resection specimens.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".