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Abstract B031: Clinicopathologic features associated with metastatic early-onset gastric cancer

2025· article· en· W4417208863 on OpenAlexaboutno aff
Jessica Sheth Bhutada, Fox Bravo, Qi Nie, Ruijian Wu, Danielle Estell, Arthur Bookstein, Justine Po, Myles Cockburn, Chanita Hughes Halbert, S. Iqbal, David R. Freyer

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsCancerOdds ratioIncidence (geometry)Conditional logistic regressionDiseaseLogistic regressionStage (stratigraphy)Retrospective cohort studyPrimary tumor

Abstract

fetched live from OpenAlex

Abstract Background: The incidence of metastatic gastric cancer among young adults is rising and has a dismal prognosis with 5-year survival of only 4%. Little is known about the clinicopathologic features associated with metastatic vs locoregional disease in young adults compared to older adults. Methods: This retrospective case control study evaluated patients treated for gastric cancer at USC Norris Comprehensive Cancer Center and LA General Hospital from 2000-2022. Sociodemographic characteristics, clinical presentation and tumor features were compared for early-onset (EO; age <50 years) cases and typical onset (TO; >50 years) controls in a 1:2 ratio matched by diagnosis year and facility. All analyses were performed within matched sets, with three samples per set. Using conditional logistic regression to estimate odds ratios, the pooled analysis tested whether there is an association between sociodemographic, clinical and tumor characteristics and metastatic vs locoregional presentation in aggregate. The early versus older onset analysis examined whether these associations differ by onset type, in terms of either the direction or the magnitude of the association. Results: 795 patients were evaluable (265 EO, 530 TO). Hispanic patients are more likely to present with metastatic disease compared to Asian (OR=2.22, 95%CI 1.34-3.70, p=0.002). Non-Hispanic White are more likely to present with metastatic disease compared to Asian (OR=2.97, 95%CI 1.61-55.48, p<0.001). This association did not differ by EO vs TO. There was no difference in stage at presentation by sex, BMI, primary location of tumor or H. pylori status of the tumor. Overall, patients with intestinal histologic compared to diffuse histologic characteristics are less likely to present with metastatic disease (OR=0.30, 95%CI 0.11-0.85, p=0.023). This association does not differ between EO and TO (p=0.48). There was no difference in the association between MSI status and metastatic disease by EO vs TO (p=0.54). Patients with HER2 amplified status are more likely to present with metastatic disease compared to patients with non-amplified HER2 (OR=2.97, 95%CI 1.25-7.09, p=0.014); however, there was no difference in risk between EO vs TO (p=0.87). Patients with a negative endoscopy prior to diagnosis (16% EO, 18% TO) were equally likely to present with locoregional or metastatic disease (p=0.91). There was no difference in association between metastatic disease and smoking or alcohol use (p=0.069, p=0.64 respectively). Conclusions: Early detection of gastric cancer, especially in non-Asian communities, is crucial as they are more likely to present with metastatic disease. The similarities in disease presentation and characteristics between early vs older onset patients suggests unmeasured environmental exposures may be associated with adverse biological features driving the rising incidence of metastatic disease in young adults. Deeper molecular characterization of metastatic vs locoregional patients may identify other factors contributing to poor outcomes. Citation Format: Jessica Sheth Bhutada, Fox Bravo, Maureen Cairns, Qi Nie4, Ruopei Wu, Danielle Estell, Arthur Bookstein, Justine Po, Myles Cockburn, Chanita Hughes Halbert, Syma Iqbal, David Freyer. Clinicopathologic features associated with metastatic early-onset gastric cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr B031.

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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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.226
GPT teacher head0.535
Teacher spread0.309 · 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 designNot applicable
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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