Evidence map›Paper›PMID 40313248›Full record

ArticleFrontiers in oncology2025

Peripheral blood metabolic composite score based on peripheral blood metabolism can be used as an assessment of recurrence after surgery in patients with locally advanced gastric cancer: a novel and promising index.

Ning Meng, Zhiqiang Wang, Yaqi Peng, Xiaoyan Wang, Wenju Yue, Le Wang, Jingxia Lv, Wenqian Ma

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Article in Frontiers in oncology, 2025. 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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8 authors.

Ning Meng *Department of General Surgery, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Zhiqiang WangDepartment of General Surgery, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Yaqi PengBasic College, Hebei Medical University, Shijiazhuang, Hebei, China.
Xiaoyan WangDepartment of General Surgery, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Wenju YueDepartment of General Surgery, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Le WangDepartment of General Surgery, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, China.
Jingxia LvThe Third Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
Wenqian Ma *Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postoperative recurrence remains a major challenge in patients with locally advanced gastric cancer (LAGC). Identifying reliable biomarkers for predicting recurrence can guide clinical decision-making and improve patient outcomes. This study aimed to investigate the association between four peripheral blood metabolic markers and postoperative recurrence in LAGC patients, and to develop a predictive model based on these markers. Methods: This retrospective cohort study analyzed data from 1,040 patients with LAGC who underwent radical surgical resection between January 2010 and December 2019. Peripheral blood metabolic indicators, including low-density lipoprotein/high-density lipoprotein (LHR), cholesterol/high-density lipoprotein (TCHR), triglycerides/high-density lipoprotein (TGHR), and triglycerides × fasting blood glucose (TyG), were used to assess metabolic status. Multivariable regression and survival analysis were performed to assess the prognostic value of these markers. A nomogram combining metabolic markers and clinical factors was developed and validated for predicting postoperative recurrence. Results: High levels of LHR, TCHR, TGHR, and TyG were significantly associated with increased risk of postoperative recurrence in LAGC patients (P < 0.001). Multivariable analysis identified TNM stage, pathological type, systemic immune inflammation index (SII), and metabolic score as independent predictors of recurrence. A predictive model incorporating these factors demonstrated superior performance compared to clinical features alone, with an area under the curve (AUC) of 0.867 (95% CI: 0.836-0.897) in the training set, 0.887 (95% CI: 0.844-0.929) in internal validation set, 0.859 (95% CI: 0.817-0.899) in the external validation set. Patients with high metabolic scores had significantly worse overall survival (OS) and disease-free survival (DFS), further supporting the model's prognostic value. Conclusions: Peripheral blood metabolic markers, particularly LHR, TCHR, TGHR, and TyG, are valuable predictors of postoperative recurrence in LAGC patients. The combined predictive model, integrating metabolic markers and clinical features, provides an effective tool for personalized risk stratification and may assist in optimizing postoperative management in LAGC.

Indexed as

locally advanced gastric cancermetabolic markersnomogrampostoperative recurrencepredictive model

Identifiers

PMID40313248
PMCPMC12043443

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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.