ArticleBMC cancer2026
Perioperative NLR/PLR dynamic phenotypes and prediction of postoperative recurrence in locally advanced gastric cancer: a retrospective cohort study.
Article in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSystemic 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).
methodsWe 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.
resultsPCA 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.
conclusionsPCA-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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.