Evidence map›Paper›PMID 42695789›Full record

ArticleRadiology. Imaging cancer2026

Spectral CT-based Nomogram for Noninvasive Assessment and Prognostic Prediction of MSI/dMMR in Esophagogastric Junction Adenocarcinoma.

Yinchen Wu, Kaihe Lin, Na Lin, Yu Lin, Xinyao Huang, Mi Wang, Dejun She, Dairong Cao

Abstract read
In one paragraph

Article in Radiology. Imaging cancer, 2026. 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

5 · Who and what money

Authors and funding

8 authors.

Yinchen Wu *Department of Radiology, the First Affiliated Hospital, Fujian Medical University, 20 Cha-Zhong Road, Fuzhou, Fujian 350005, PR China.ORCID 0000-0001-7353-6605
Kaihe Lin *Department of Radiology, The First Hospital of Putian City, Putian, China.
Na LinDepartment of Radiology, the First Affiliated Hospital, Fujian Medical University, 20 Cha-Zhong Road, Fuzhou, Fujian 350005, PR China.ORCID 0009-0006-4521-985X
Yu LinDepartment of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China.
Xinyao HuangDepartment of Radiology, the First Affiliated Hospital, Fujian Medical University, 20 Cha-Zhong Road, Fuzhou, Fujian 350005, PR China.
Mi WangDepartment of Pathology, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Dejun SheDepartment of Radiology, the First Affiliated Hospital, Fujian Medical University, 20 Cha-Zhong Road, Fuzhou, Fujian 350005, PR China.ORCID 0000-0002-0143-659X
Dairong CaoDepartment of Radiology, the First Affiliated Hospital, Fujian Medical University, 20 Cha-Zhong Road, Fuzhou, Fujian 350005, PR China.ORCID 0000-0002-0051-3143

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose To establish and evaluate a nomogram based on quantitative spectral CT parameters for predicting microsatellite instability (MSI) and deficient mismatch repair (dMMR) status in patients with esophagogastric junction adenocarcinoma (EGJA). Materials and Methods In this study including retrospective and prospective datasets (enrollment period: May 2021 to January 2026), patients from two centers were divided into training, validation, external test, prospective test, and neoadjuvant chemotherapy cohorts. A nomogram was constructed integrating clinical characteristics with quantitative spectral CT parameters. Model efficacy in predicting MSI/dMMR and its associations with disease-free survival were evaluated. Primary statistical methods included logistic and Cox regression analyses. Results In total, 511 patients (median age, 67 years [IQR, 60-73 years]; 333 male) were included. The nomogram incorporated sex, clinical N stage, CT attenuation on 40-keV virtual monoenergetic images, and normalized iodine density during the venous phase. It achieved areas under the receiver operating characteristic curve of 0.87 (95% CI: 0.81, 0.93), 0.87 (95% CI: 0.78, 0.96), 0.91 (95% CI: 0.83, 0.99), 0.89 (95% CI: 0.80, 0.98), and 0.86 (95% CI: 0.76, 0.96) across the five respective cohorts: training, validation, external test, prospective test, and neoadjuvant chemotherapy. In the external test cohort, the nomogram correctly identified 9.76% (four of 41) of the patients misclassified with preoperative biopsy. Furthermore, it stratified patients into distinct disease-free survival risk groups in the training (hazard ratio, 2.04 [95% CI: 1.35, 3.09];

Indexed as

AdenocarcinomaEsophageal NeoplasmsEsophagogastric JunctionMicrosatellite InstabilityNomogramsStomach NeoplasmsTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedPrognosisProspective StudiesRetrospective StudiesCT-SpectralEsophagogastric Junction AdenocarcinomaNeoplasms-PrimaryNomogramPathologyPre-clinical ModelsPrimary NeoplasmsSpectral CTTumor Immune Microenvironment

Identifiers

PMID42695789
PMCPMC13620324

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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.