Oncologic Outcomes Associated With MRI-detected Extramural Venous Invasion (mrEMVI) in Rectal Cancer
Bibliographic record
Abstract
BACKGROUND: The role of MRI-detected EMVI (mrEMVI) as a reliable prognostic factor in rectal cancer has been emphasized in recent years but this finding remains underreported by many institutions. OBJECTIVE: This review aimed to demonstrate the importance of pre- and post-treatment MRI-detected EMVI as independent prognostic factors of adverse oncologic outcomes in patients undergoing neoadjuvant therapy followed by total mesorectal excision. METHODS: This review was designed using the PRISMA guidelines. The following electronic databases were searched from January 2002 to January 2020: CENTRAL, Ovid MEDLINE, PubMed, and Ovid Embase. Main outcomes included DFS and overall survival (OS). Other outcomes of interest comprised positive resection margin and synchronous metastases. RESULTS: Seventeen studies involving a total of 3821 patients were included for data synthesis. For preneoadjuvant treatment mrEMVI, pooled hazard ratio (HR) estimate for DFS was 2.30 (95% confidence intervals (CI) 1.54-3.44) for higher recurrence in mrEMVI-positive patients. mrEMVI-positive patients were found to have a lower OS with a pooled HR of 1.68 (95%CI 1.27-2.22). Pooled risk ratio for synchronous metastasis was 4.11 (95%CI 2.80-6.02) for mrEMVI-positivity. For postneoadjuvant treatment EMVI (ymrEMVI), positive status showed a lower DFS with a pooled HR of 2.04 (95%CI 1.55-2.69). Risk ratio of having a positive resection margin status was 2.95 (95%CI 1.75-4.98) for ymrEMVI-positive patients. CONCLUSIONS: This review showed that oncologic outcomes are significantly worse for both pre- and post-neoadjuvant treatment mrEMVI-positive patients. MRI-detected EMVI should be consistently reported in rectal cancer staging and may provide guidance for the targeted use of additional systemic therapy.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".