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Record W4414050061 · doi:10.1093/dote/doaf061.060

435. CLINICAL RESPONSE IMPROVES THE PROGNOSTIC STRATIFICATION OF PATHOLOGICAL RESPONSE AFTER NEOADJUVANT CHEMOTHERAPY IN ESOPHAGEAL ADENOCARCINOMA

2025· article· en· W4414050061 on OpenAlexaff
Luis F de Castro, Sofia Cusin, Mehrnoush Dehghani, Nicholas Bertos, Mathieu Rousseau, Sara Najmeh, Jonathan Cools‐Lartigue, Jonathan Spicer, Carmen Mueller, Pierre Fiset, Lorenzo Ferri

Bibliographic record

VenueDiseases of the Esophagus · 2025
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsPathologicalEsophagectomyGrading (engineering)ChemotherapyAdenocarcinomaNeoadjuvant therapyProportional hazards modelEsophageal adenocarcinoma

Abstract

fetched live from OpenAlex

Abstract Background Docetaxel-based neoadjuvant chemotherapy (NAT) has emerged as a leading standard of care therapy for locally advanced esophageal adenocarcinoma (EAC). Response in resected specimens is routinely assessed using the modified Ryan scheme Tumor Regression Grading (TRG) score and may affect the prediction of survival and choice of adjuvant therapy. While TRG at the extremes (complete/near complete response, TRG0/1; poor response, TRG3), appears to have clear prognostic significance, moderate response (TRG2) lacks consistent prognostic value due to heterogeneity. This study aims to refine the characterization of TRG2 patients to improve survival prognostication. Methods Patients undergoing curative-intent NAT and esophagectomy for EAC between 01/2007 and 12/2023 were identified from a prospectively collected database. Data on demographics, tumor characteristics, NAT, surgical technique, pathological findings, and overall survival (OS) were collected. Clinical/objective response rates to NAT was assessed at diagnosis and post NAT with CT (RECIST), PET (change in SUV), dysphagia score (range: 0, best to 4, worst), and endoscopic response (range: 0, complete- to 3 none), and correlated to pathological response and survival. Kaplan–Meier analysis and Cox-regression models were used to evaluate the association between factors and OS with significance set at p < 0.05 (*). Results Of 1004 esophagectomies in the database, 453 received docetaxel-based NAT resulting in pathological response of TRG0/1 (n = 92, 20.3%), TRG2 (n = 149, 32.9%), and TRG3 (n = 147, 32.5%). OS differed significantly between categories: 3-year OS for TRG 0/1 was 45% compared to 31% for TRG2 and 26% for TRG3 (*) with overlapping survival curves between the TRG2 group and entire cohort. When controlling for TRG, the absence of endoscopic response doubled the risk of death compared to complete response (*). Lack of dysphagia score improvement strongly trends towards correlation with worse survival (p = 0.07), while CT/PET response showed no significant survival impact. Conclusion Pathological response grading after NAT in EAC fails to predict oncological outcome in those with moderate response (TRG2). Clinical response criteria, especially the absence of improved endoscopic response or dysphagia scores, was associated with poor survival in TRG2 patients. By incorporating clinical response in addition to pathological response we can better predict survival in EAC patients undergoing NAT and surgery.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.017
GPT teacher head0.348
Teacher spread0.331 · 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 designObservational
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 abstractyes

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