ArticleBMC cancer2025
Development and validation of a prognostic nomogram based on inflammation and Nutrition-Related Indexes for predicting postoperative survival in patients with pancreatic neuroendocrine tumors.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Unraveling immune-inflammation-aging network interactions: an interpretable machine learning model predicts the risk of postherpetic neuralgia.Frontiers in immunology · 2026Article
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7 authors.
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Abstract
backgroundPancreatic neuroendocrine tumors (pNETs) are rare malignant tumors. While surgical resection is the primary therapeutic approach, postoperative survival outcomes remain suboptimal. This study aims to investigate the prognostic value of inflammation and nutrition-related indicators, such as Prognostic nutritional index (PNI), Neutrophil-lymphocyte ratio (NLR), Platelet-lymphocyte ratio (PLR), Systemic immune-inflammation index (SII), and Lymphocyte-monocyte ratio (LMR), in patients with pNETs undergoing surgery. Furthermore, we sought to develop and validate a prognostic nomogram incorporating independent predictors of postoperative overall survival (OS).
methodsA retrospective analysis was conducted on the clinical data from 102 patients with pathologically confirmed pNETs. Univariate and multivariate Cox regression analyses were performed to identify prognostic factors. A nomogram was developed based on independent risk factors, and its predictive performance was internally validated.
resultsThe analysis revealed that low preoperative levels of PNI, low NLR, low LMR, low SII, and low PLR were significantly associated with reduced postoperative survival. Multivariate Cox regression analysis identified PNI (HR = 0.153; 95% CI, 0.033-0.720), NLR (HR = 0.153; 95% CI, 0.037-0.633), and AJCC stage (HR = 20.126; 95% CI, 5.036-80.422) as independent prognostic factors. The developed nomogram demonstrated excellent discriminative ability, with time-dependent AUC values of 0.878 (3-year), 0.860 (5-year), and 0.830 (10-year), along with a C-index of 0.824 (95% CI 0.748, 0.901) upon internal validation. Risk stratification using the nomogram effectively distinguished low- and high-risk groups, and its validity was confirmed using Kaplan-Meier survival curves.
conclusionDespite limitations inherent to its retrospective, single-center design and small sample size, this study establishes a novel nomogram integrating inflammatory-nutritional biomarkers with clinicopathological staging. This tool provides clinicians with a personalized prognostic assessment framework to guide postoperative management strategies for pNETs patients.
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