Evidence map›Paper›PMID 40361455›Full record

ArticleCancers2025

Neoadjuvant Chemoradiotherapy in Locally Advanced Gastric Adenocarcinoma: Long-Term Results and Statistical Algorithm to Predict Individual Risk of Relapse.

Miguel Ortego, Olast Arrizibita, Adriana Martinez-Lage, Ángel Vizcay Atienza, Laura Álvarez Gigli, Oskitz Ruiz, José Carlos Subtil, Maialen Zabalza, Victor Valentí, Ana Tortajada and 3 more

Abstract read
In one paragraph

Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Miguel OrtegoDepartment of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.
Olast ArrizibitaDepartment of Mathematics and Statistic, NNBi, 31110 Noain, Spain.ORCID 0000-0002-2803-9930
Adriana Martinez-LageDepartment of Radiation Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.
Ángel Vizcay AtienzaDepartment of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.ORCID 0000-0001-9386-3654
Laura Álvarez GigliDepartment of Pathology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.
Oskitz RuizDepartment of Mathematics and Statistic, NNBi, 31110 Noain, Spain.
José Carlos SubtilDepartment of Gastroenterology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.
Maialen ZabalzaDepartment of Mathematics and Statistic, NNBi, 31110 Noain, Spain.
Victor ValentíDepartment of GI Surgery, Clínica Universidad de Navarra, 31008 Pamplona, Spain.ORCID 0000-0002-7074-2849
Ana TortajadaDepartment of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.
María José HidalgoDepartment of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.ORCID 0009-0006-6020-6491
Onintza SayarDepartment of Mathematics and Statistic, NNBi, 31110 Noain, Spain.
Javier RodriguezDepartment of Medical Oncology, Clínica Universidad de Navarra, 31008 Pamplona, Spain.ORCID 0000-0003-1899-4384

Funding

Government of Navarra's Department of Economic and Business Development 0011-1411-2020-000074
6 · The paper itself

Abstract

backgroundThe purpose of this study was to evaluate the long-term outcomes of patients with locally advanced gastric adenocarcinoma (LAGC) intended to receive induction chemotherapy, chemoradiation and surgery and to develop an algorithm to estimate the individual risk of relapse in a population-based setting.

methodsPatients with LAGC (cT3-4 and/or N+) were retrospectively evaluated. A pathological response was graded according to the Becker criteria. The nodal regression grade was assessed by a 4-point scale (A-D). A comprehensive analysis of 155 individual patient variables was performed, and logistic regression (LR) was utilized to develop a predictive model for relapse risk.

resultsFrom 2010 to 2024, 48 patients were analyzed. After a median follow-up of 49 months (range, 12-212), the 5-year actuarial PFS and OS rates were 44% and 48%, respectively. Four variables were identified as the most relevant features for training the LR model. Scores for the model accuracy, sensitivity and specificity (mean +/- sd) were 0.79 +/- 0.12, 0.74 +/- 0.221 and 0.88 +/- 0.14, respectively. For a validation dataset, the figures were 0.78, 0.88 and 0.73, respectively.

conclusionsThis neoadjuvant strategy seems to correlate with a favorable long-term outcome in a subset of intestinal-type LAGA patients who achieve ypN0 features.

Indexed as

induction chemotherapylocally advanced gastric cancerlogistic regressionlong-term outcomepreoperative chemoradiation

Identifiers

PMID40361455
PMCPMC12070951

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.