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Background <p>Systemic inflammation plays a critical role in tumor progression and postoperative recurrence in gastric cancer. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are readily accessible biomarkers of systemic inflammatory and immune responses, but their dynamic changes around surgery remain underexplored. This study aimed to assess the prognostic value of principal component–derived phenotypes based on perioperative NLR and PLR—specifically, principal component 1 (PC1; preoperative inflammatory burden) and principal component 2 (PC2; postoperative inflammatory recovery dynamics)—for predicting disease-free survival (DFS) in patients with locally advanced gastric cancer (LAGC).</p> Methods <p>We retrospectively analyzed data from 375 patients with LAGC who underwent radical gastrectomy at the Affiliated Hospital of Jiangnan University between January 2018 and December 2022, with follow-up through March 2025. NLR and PLR were measured one week before and one month after surgery. Principal component analysis (PCA) was applied to derive two independent inflammatory phenotypes (PC1 and PC2). These components, together with T stage, N stage, and preoperative carcinoembryonic antigen (CEA), were incorporated into a Cox proportional hazards regression model, and internal validation was performed using bootstrap resampling (1000 times). Model performance was evaluated using Kaplan–Meier survival analysis, log-rank testing, and time-dependent receiver operating characteristic (ROC) curve analysis.</p> Results <p>PCA identified two independent components: PC1 (preoperative inflammatory burden; variance explained 40.24%) and PC2 (postoperative inflammatory recovery; variance explained 36.16%). Multivariate Cox regression revealed that N stage, T stage, preoperative carcinoembryonic antigen (CEA), PC1, and PC2 were independent predictors of DFS (all <i>p</i> &lt; 0.05). Stratified analysis demonstrated that patients with the “Dual-High” phenotype (high PC1 and high PC2) had a markedly shorter median DFS (13.1 months) compared with those with the “Dual-Low” phenotype (74.6 months; <i>p</i> &lt; 0.001). Internal validation showed good discriminative ability of the model (bias-corrected concordance index [C-index] = 0.762), and time-dependent ROC curves indicated stable predictive performance at 12, 36, and 60 months postoperatively.</p> Conclusions <p>PCA-derived perioperative inflammatory phenotypes effectively stratify recurrence risk in LAGC. The “Dual-High” phenotype indicates poor prognosis, and combining these phenotypes with T stage, N stage, and preoperative CEA enhances individualized postoperative surveillance and adjuvant therapy decision-making.</p>

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Perioperative NLR/PLR dynamic phenotypes and prediction of postoperative recurrence in locally advanced gastric cancer: a retrospective cohort study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月30日

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  • Yinxiao Wu,
  • Jie Zhou,
  • Su Li,
  • Ying Xuan,
  • Dongyan Cai

摘要

Background

Systemic inflammation plays a critical role in tumor progression and postoperative recurrence in gastric cancer. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are readily accessible biomarkers of systemic inflammatory and immune responses, but their dynamic changes around surgery remain underexplored. This study aimed to assess the prognostic value of principal component–derived phenotypes based on perioperative NLR and PLR—specifically, principal component 1 (PC1; preoperative inflammatory burden) and principal component 2 (PC2; postoperative inflammatory recovery dynamics)—for predicting disease-free survival (DFS) in patients with locally advanced gastric cancer (LAGC).

Methods

We retrospectively analyzed data from 375 patients with LAGC who underwent radical gastrectomy at the Affiliated Hospital of Jiangnan University between January 2018 and December 2022, with follow-up through March 2025. NLR and PLR were measured one week before and one month after surgery. Principal component analysis (PCA) was applied to derive two independent inflammatory phenotypes (PC1 and PC2). These components, together with T stage, N stage, and preoperative carcinoembryonic antigen (CEA), were incorporated into a Cox proportional hazards regression model, and internal validation was performed using bootstrap resampling (1000 times). Model performance was evaluated using Kaplan–Meier survival analysis, log-rank testing, and time-dependent receiver operating characteristic (ROC) curve analysis.

Results

PCA identified two independent components: PC1 (preoperative inflammatory burden; variance explained 40.24%) and PC2 (postoperative inflammatory recovery; variance explained 36.16%). Multivariate Cox regression revealed that N stage, T stage, preoperative carcinoembryonic antigen (CEA), PC1, and PC2 were independent predictors of DFS (all p < 0.05). Stratified analysis demonstrated that patients with the “Dual-High” phenotype (high PC1 and high PC2) had a markedly shorter median DFS (13.1 months) compared with those with the “Dual-Low” phenotype (74.6 months; p < 0.001). Internal validation showed good discriminative ability of the model (bias-corrected concordance index [C-index] = 0.762), and time-dependent ROC curves indicated stable predictive performance at 12, 36, and 60 months postoperatively.

Conclusions

PCA-derived perioperative inflammatory phenotypes effectively stratify recurrence risk in LAGC. The “Dual-High” phenotype indicates poor prognosis, and combining these phenotypes with T stage, N stage, and preoperative CEA enhances individualized postoperative surveillance and adjuvant therapy decision-making.