Evidence mapPaperPMID 42369062Full record

ArticleFrontiers in endocrinology2026

Preoperative electrolyte-based metabolic biomarkers for prognostic assessment in gastric cancer: a multicenter study.

Weihao Kong, Jiawen Wang, Xuqin Wu, Kangjie Zhang, Xingyu Wang, Jianlin Zhang

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Weihao Kong *Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Jiawen Wang *Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Xuqin WuMedical Records Management Department, Lujiang People's Hospital of Anhui Province, Hefei, China.
Kangjie ZhangWest China Clinical Medical College, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xingyu WangDepartment of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Jianlin ZhangDepartment of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gastric cancer remains a major cause of cancer-related mortality worldwide, with substantial heterogeneity in patient outcomes despite advances in treatment. Clinically accessible biomarkers are still needed to improve prognostic stratification. Serum electrolytes, as routine circulating parameters, may reflect systemic metabolic status, host physiological adaptation, and tumor-related stress. This study aimed to develop and externally validate an electrolyte-based metabolic biomarker score for prognostic assessment in gastric cancer. Methods: This retrospective multicenter study included 1, 371 patients with gastric cancer from two independent cohorts: a training cohort (n = 1, 085) and an external validation cohort (n = 286). Seven preoperative serum electrolytes were analyzed. Univariate and multivariate Cox regression analyses were used in the training cohort to identify independent prognostic electrolytes and construct an Electrolyte Score. Patients were stratified into high- and low-risk groups according to the median score in the training cohort, and the same cutoff was applied to the validation cohort. Kaplan-Meier analysis, time-dependent ROC analysis, calibration curves, and decision curve analysis were used to evaluate prognostic performance and clinical utility. Results: Sodium and calcium were identified as independent prognostic factors for overall survival and incorporated into the Electrolyte Score. Higher sodium and calcium levels were associated with better survival. Although the Electrolyte Score alone had limited discriminatory ability, it was able to stratify patients into prognostically distinct groups in both cohorts. A high Electrolyte Score was associated with worse overall survival (training cohort, P < 0.001; validation cohort, P = 0.004). Multivariate analysis confirmed the score as an independent prognostic factor. Importantly, a nomogram integrating the Electrolyte Score with age, TNM stage, and histological differentiation improved individualized prognostic prediction, demonstrating potential clinical utility for risk stratification and guiding patient management. Conclusions: A preoperative electrolyte-based score derived from sodium and calcium provided independent prognostic information in gastric cancer. While its predictive value alone is limited, its combination with clinicopathological variables in a nomogram enhances individualized risk stratification, offering a practical tool to complement conventional prognostic assessment in clinical practice.

Indexed as

Biomarkers, TumorElectrolytesStomach NeoplasmsAgedCalciumFemaleHumansMaleMiddle AgedPreoperative PeriodPrognosisRetrospective StudiesSodiumBiomarkers, TumorCalciumElectrolytesSodiumelectrolyte scoregastric cancermetabolic biomarkersnomogramprognostic stratification

Identifiers

PMID42369062
PMCPMC13293866

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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 Socratic graph.