S1139 Endoscopic Resection Technique Outcomes for Non-Lifting Colorectal Lesions: A Systematic Review
Bibliographic record
Abstract
Introduction: Endoscopic mucosal resection (EMR) is dependent on submucosal injectate expansion to allow for effective and safe tissue capture. Non-lifting polypoid tissue can render colorectal neoplasia recalcitrant to EMR. A number of alternative resection modalities and auxiliary techniques targeting non-lifting polypoid tissue have been described. We therefore sought to perform a systematic comparative analysis of existing techniques for non-lifting colorectal neoplasia. Methods: Two authors (BZ, HJK) independently searched MEDLINE and EMBASE (Inception to April 2022) for citations evaluating endoscopic resection technique outcomes for non-lifting colorectal neoplasia. Eligible outcomes included technical success (removal of all visible polypoid tissue), R0 resection, intra-procedural perforation (IPP), clinically significant post-endoscopic resection bleeding (CSPEB), delayed perforation and recurrence. Categorical variables were expressed as frequency (%), with ranges estimated for the outcomes of interest, stratified by their respective techniques. Results: 2395 citations were identified in our search strategy, of which 18 citations provided endoscopic resection technique outcomes for non-lifting colorectal neoplasia (7 endoscopic full-thickness resection (EFTR), 3 endoscopic submucosal dissection (ESD), 3 hybrid resection techniques (2 hybrid EFTR and 1 dissection-enabled scaffold-assisted resection), 2 avulsion techniques, 2 cap-assisted EMR (C-EMR), and 1 ablative technique). Technical success ranged from 79–100% (EFTR: 80-100%, ESD: 79-91%, hybrid technique: 98-100%, avulsion: 100%, C-EMR: 97%, ablation: 96%). R0 for applicable modalities ranged from 54-100% (EFTR: 57-100%, ESD: 54-63%). IPP ranged from 0-9% (EFTR: 0-4%, ESD: 0-9%, hybrid technique: 0-2%, avulsion: 0-3%, C-EMR: 0-9%, ablation: 0%). CSPEB ranged from 0-29% (EFTR: 0-29%, ESD: 0%, hybrid technique: 0-4%, avulsion: 5-6%, C-EMR: 9%, ablation: 4%). Delayed perforation was between 0 -14% (EFTR: 0-14%, ESD: 0-9%, hybrid technique: 0%, avulsion: 0%, C-EMR: 0%, ablation: 0%). Recurrence ranged from 0-43% (EFTR: 0-43%, ESD: 0-4%, hybrid technique: 0-17%, avulsion: 15-17%, C-EMR: 19%, ablation: 26%). Conclusion: Endoscopic resection techniques are effective for non-lifting colorectal lesions. Given the frequency of technical success comparative analyses between existing techniques focusing on the frequency of low-risk T1 colorectal cancer histopathology post-resection and adverse outcomes are needed. (Table) Table 1. - Outcomes and complications of different auxiliary techniques for non-lifting colorectal neoplasia Modaility Number of Studies Number of Lesions Technical Success R0 Intra-procedure Perforation CSPEB 1 Delayed Perforation Recurrence EFTR 2 7 106 80-100% 57-100% 0-4% 0-29% 0-14% 0-43% ESD 3 3 46 79-91% 54-63% 0-9% 0% 0-9% 0-4% Hybrid technique 4 3 84 98-100% N/A 0-2% 0-4% 0% 0-17% Avulsion 2 121 100% N/A 0-3% 5-6% 0% 15-17% Cap-assisted EMR 5 2 82 97% N/A 0-9% 9% 0% 19% Ablation 1 26 96% N/A 0% 4% 0% 26% 1clinically significant post-endoscopic resection bleeding.2Endoscopic full-thickness resection.3Endoscopic submucosal dissection.4Includes hybrid EFTR and Dissection enabled scaffold-assisted resection.5Includes cap-assisted EMR alone and cap-assisted EMR ± cold avulsion ± ablation.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".