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Record W4408901867 · doi:10.1055/s-0045-1805260

Comparable long-term efficacy of cold and hot EMR of large colon polyps – follow up results of a randomized trial

2025· article· en· W4408901867 on OpenAlexaff
Heiko Pohl, Douglas K. Rex, Judy Barber, A. Rastogi, Matthew T. Moyer, John M. Levenick, Daniel von Renteln, S. Gordon, Harry R. Aslanian, Mazen Elatrache, Michael B. Wallace, J Elmunzer, Rajesh N. Keswani, Nikhil A. Kumta, Douglas K. Pleskow, Ehl M, Todd A. MacKenzie, Cyrus Piraka

Bibliographic record

VenueEndoscopy · 2025
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineRandomized controlled trialTerm (time)Internal medicineColonoscopyGastroenterologySurgeryColorectal cancer

Abstract

fetched live from OpenAlex

Aims Although safer, cold endoscopic mucosal resection (EMR) of large (≥ 20 mm) non-pedunculated polyps has been shown to have a high recurrence rate of>25% at first surveillance colonoscopy (SC1). The efficacy of treating recurrence at SC1 is unknown. The aim of this study was to compare recurrence between cold and hot EMR of large non-pedunculated colorectal polyps at second surveillance colonoscopy (SC2). Methods This is a follow-up study of a randomized trial of 660 patients undergoing cold or hot EMR of large non-pedunculated colorectal polyps at 15 centers in the US and Canada. We performed an interim analysis of all patients who have completed SC2. Treatment of recurrence was at the discretion of the endoscopist. Primary outcome of interest was recurrence/residual rate of neoplastic polyps at SC2. Secondary outcomes include proportion of polyps with no recurrence at S1, but recurrence at SC2. We further examined characteristics of recurrent/residual polyps. Results 273 patients (44% of surveillance eligible patients) with 281 large polyps completed SC2 with examination of the resection site after a median of 19 months (148 in the cold EMR group and 125 in the hot EMR group). Among these patients, recurrence at SC1 was significantly greater following cold EMR (36.3%) compared to hot EMR (16.9%). Recurrence at SC2 was not different and occurred 12.7% in the cold EMR group and in 8.9% in the hot EMR group (p=0.304). Among those with recurrence at SC1, complete removal with no recurrence at SC2 was more often achieved in in the cold EMR group (80.7%) compared to the hot EMR group (57.1%, p=0.035). The proportion of polyps with no recurrence at SC1 but detected recurrence at SC2 was 5.7% and 1.6% (p=0.127), respectively. Recurrent median polyp size was similar (10 and 8 mm, respectively). Histology of recurrent polyps was also similar with 90.0% adenomas (5 tubulo-villous adenomas [TVA]) and 10.0% sessile serrated lesions (SSL) in the cold EMR group and 72.7% adenomas (2 TVA), 27.2% SSL (1 dysplastic) in the hot EMR group. One polyp in the hot EMR group contained high grade dysplasia; there was no cancer in any recurrent polyp. All recurrent polyps at SC2 could be removed. Conclusions In this large follow-up study long-term efficacy of cold EMR of large non-pedunculated polyps appears comparable to hot EMR at second surveillance colonoscopy, although incomplete SC2 follow-up data is a limitation. Management of recurrence is equivalent between cold and hot EMR. The high rate of new recurrence at SC2 after cold EMR suggests that SC1 biopsies should be taken even in the absence of visible recurrence (in contrast to hot EMR). Overall, the results lower concerns of an initial high recurrence rate following cold EMR, and that early recurrence can be adequately managed. ClinicalTrials.gov no: NCT03865537. Publication History Article published online: 27 March 2025 © 2025. European Society of Gastrointestinal Endoscopy. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.019
GPT teacher head0.324
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractno

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