MétaCan
Menu
Back to cohort
Record W4414050112 · doi:10.1093/dote/doaf061.059

432. OUTCOMES IN PATHOLOGIC T1N1 ESOPHAGEAL ADENOCARCINOMA

2025· article· en· W4414050112 on OpenAlexaff
Zamaan Hooda, Dylan Lansburt, Shanique Ries, Jaffer A. Ajani, Mara B. Antonoff, Reza J. Mehran, M Murphy, Ravi Rajaram, David C. Rice, Stephen G. Swisher, Ara A. Vaporciyan, Garrett L. Walsh, K. G. Mitchell, Lorenzo Ferri, Wayne Hofstetter

Bibliographic record

VenueDiseases of the Esophagus · 2025
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsLymphovascular invasionProportional hazards modelEsophageal cancerEsophageal adenocarcinomaAdenocarcinomaRetrospective cohort studyNeoadjuvant therapyAdjuvant therapy

Abstract

fetched live from OpenAlex

Abstract Background Some clinical T1N0 (cT1N0) esophageal adenocarcinoma (EAC) patients undergo surgery due to nodal disease risk factors discovered on diagnostic endoscopic resection, including deep submucosal invasion, poor differentiation, and lymphovascular invasion (LVI). Higher risk patients may ultimately be upstaged to pathologic T1N1 (pT1N1) disease. Although few retrospective studies suggest benefits of adjuvant therapy (ADT) for locally advanced EAC, limited literature exists regarding pT1N1 patient outcomes and therapy recommendations. This study aims to describe outcomes and the impact of ADT on survival in this understudied cohort. To our knowledge, this investigation represents the largest number of patients strictly diagnosed with pT1N1 EAC. Methods We identified pT1N1 EAC patients that underwent upfront surgery without neoadjuvant treatment between 2005–2022 at two different centers. Collected data included demographic, clinicopathologic, and treatment-related variables, along with survival outcomes. Patients were stratified based on receipt of ADT (ADT) or observation (OBS) following surgical resection. Survival outcomes were evaluated using the Kaplan–Meier method and multivariable (MV) Cox regression models. Results We identified 41 pT1N1 EAC patients (14 ADT and 27 OBS). Among ADT patients, 11 received chemotherapy and 3 received chemoradiation. Group similarities included male prevalence (ADT, 85.7%, n = 12/14; OBS, 70.4%, 19/27, p = 0.447) and median surgical age (ADT, 64.5 years; OBS, 64 years, p = 0.509). LVI occurred in 5 ADT (35.7%) and 14 OBS (51.8%, p = 0.510) patients. At median follow-up of 40.5 months, ADT and OBS patients had a median overall survival (OS) of 53.9 and 49 months (p = 0.881, Figure), respectively. MV Cox regression revealed no ADT influence on OS, though showed LVI negatively impacting OS (HR = 6.966, 95% CI: 1.497–32.415, P = 0.013). Conclusion Our study failed to find a significant influence of ADT on survival outcomes in pT1N1 EAC patients. Instead, our investigation revealed that LVI portends a negative prognosis in these individuals. Ultimately, this rare subset of EAC remains poorly understood, and our findings add information that is significantly lacking in the literature. Further efforts are needed to elucidate optimal management strategies for pT1N1 EAC patients.

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 score0.006

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 head0.012
GPT teacher head0.312
Teacher spread0.300 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDiseases of the EsophagusSame topicEsophageal Cancer Research and TreatmentFrench-language works237,207