Impact of Salvage Surgery following Colonic Endoscopic Polypectomy for Patients with Invasive Neoplasia
Bibliographic record
Abstract
Background: Invasive neoplasia (Tis-T1) are increasingly being encountered in the daily routine of endoscopic polypectomy. However, the need for salvage surgery following endoscopic therapy for invasive neoplasia is controversially discussed. Patients and Methods: Patients with endoscopic removal of invasive neoplasia were identified from the national Surveillance Epidemiology and End Results (SEER) Database 2005 to 2015. Survival analysis and Cox proportional hazard regression analysis in cancer-specific mortality and overall survival rate was used, which were stratified by T stage and polyp size. Results: A total of 5805 patients with endoscopic removal of invasive neoplasia were included in the analysis, of whom 1214 (20.9%) underwent endoscopic treatment alone and 4591 (79.1%) underwent endoscopic resection plus surgery. The survival analysis revealed that patients undergoing salvage surgery had a significantly better cancer-specific survival (97.4% vs. 95.8%, p-value = 0.017). In patients with T1 stage, additional salvage surgery led to a significantly higher cancer-specific survival (92.1% vs. 95.0%, p value = 0.047). Conclusion: Salvage surgery following endoscopic polypectomy may improve the oncological survival of patients with invasive neoplasia, especially in patients with T1 stage. Furthermore, the T stage, size, and localization of polyps, as well as the level of CEA, could be identified as significant predictors for lymphonodal and distant metastases.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".