Current practice patterns among pathologists in the assessment of venous invasion in colorectal cancer
Bibliographic record
Abstract
AIMS: Venous invasion (VI) is a known independent prognostic indicator of recurrence and survival in colorectal cancer. The guidelines of the Royal College of Pathologists (RCPath) state that, in a series of resections, extramural VI should be detected in at least 25% of specimens. However, there is widespread variability in the reported incidence, and this may affect patient access to adjuvant therapy. This study aims to clarify the current practice patterns of pathologists regarding the assessment of VI and to identify factors associated with an increased self-reported VI detection rate. METHODS: A population-based survey was mailed to 361 pathologists in the province of Ontario, Canada. RESULTS: The overall response rate was 64.9%. Most pathologists were practicing in community-based centres (66.2%) and approximately half had been in practice for over 15 years (53.5%). A subspecialist interest in gastrointestinal (GI) pathology was declared by 27.3% of pathologists. The majority of pathologists (70.2%) reported that they detected VI in less than 10% of resection specimens, with only 9.1% reporting VI detection rates above 20%. Standardised reporting criteria were applied by 62.1%. Special stains were employed by 57.6% if VI was suspected on H&E-stained sections. Practice in a university-affiliated centre, a subspecialist interest in GI pathology and the acceptance of the 'orphan arteriole' sign were all independently associated with a self-reported VI detection rate above 10% on multivariate analysis. CONCLUSIONS: Self-reported VI detection rates are low among most pathologists. Even among specialist GI pathologists practicing in university-affiliated centres, few reported a detection rate close to that recommended by the RCPath. Strategies to increase the detection of VI may be required.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".