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A novel potential inflammation-nutrition biomarker for predicting lymph node metastasis in clinically node-negative colon cancer

Authors :
Wanyao Duan
Wei Wang
Chiyi He
Source :
Frontiers in Oncology, Vol 13 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

BackgroundThe purpose of this study is to investigate the predictive significance of (platelet × albumin)/lymphocyte ratio (PALR) for lymph node metastasis (LNM) in patients with clinically node-negative colon cancer (cN0 CC).MethodsData from 800 patients with primary CC who underwent radical surgery between March 2016 and June 2021 were reviewed. The non-linear relationship between PALR and the risk of LNM was explored using a restricted cubic spline (RCS) function while a receiver operating characteristic (ROC) curve was developed to determine the predictive value of PALR. Patients were categorized into high- and low-PALR cohorts according to the optimum cut-off values derived from Youden’s index. Univariate and multivariate logistic regression analyses were used to identify the independent indicators of LNM. Sensitivity analysis was performed to repeat the main analyses with the quartile of PALR.ResultsA total of eligible 269 patients with primary cN0 CC were retrospectively selected. The value of the area under the ROC curve for PALR for predicting LNM was 0.607. RCS visualized the uptrend linear relationship between PALR and the risk of LNM (p-value for non-linearity > 0.05). PALR (odds ratio = 2.118, 95% confidence interval, 1.182-3.786, p = 0.011) was identified as an independent predictor of LNM in patients with cN0 CC. A nomogram incorporating PALR and other independent predictors was constructed with an internally validated concordance index of 0.637. The results of calibration plots and decision curve analysis supported a good performance ability and the sensitivity analysis further confirmed the robustness of our findings.ConclusionPALR has promising clinical applications for predicting LNM in patients with cN0 CC.

Details

Language :
English
ISSN :
2234943X
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.011f0841b1d4d45877098ec03b73d87
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2023.995637