ArticleBMC cancer2025
Identification of gastroenteropancreatic neuroendocrine tumor patients with high liver tumor burden based on clinicopathological features.
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.
- Beyond conventional biomarkers: the role of alpha-fetoprotein in gastroenteropancreatic neuroendocrine neoplasms.Frontiers in endocrinology · 2026Review
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12 authors.
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Abstract
backgroundMetastatic liver tumor burden (LTB) is a prognostic factor affecting the survival of gastroenteropancreatic neuroendocrine tumors (GEP-NETs), but evaluation of the LTB usually depends on radiologic and functional imaging. This study aimed to develop a clinical model based on easily accessible clinicopathological markers to predict LTB level in GEP-NET patients.
methodsLTB was quantified based on 68Ga-DOTANOC PET/CT scan. The optimal cut-off value for high and low-LTB was determined based on our previous study. Serum levels of liver enzymes and tumor biomarkers were obtained within one week before PET/CT scan. The whole dataset was divided into training set and validation set. LASSO regression method was used to select predictors, and multivariate logistic regression was used to develop a clinical model which was further visualized by constructing a nomogram. Area under the curve (AUC) was applied to assess the accuracy of the constructed model.
resultsWe retrospectively enrolled 200 patients with well-differentiated GEP-NETs. Ki-67 index, GGT (gamma-glutamyltransferase), LDH (lactate dehydrogenase), and NSE (neuron-specific enolase) were selected through the LASSO regression method, and a nomogram was built based on these variables. The predictive model yielded an AUC of 0.785 (95% CI, [0.708–0.862]) in the training set, and 0.783 (95% CI, [0.644–0.923]) in the validation set. Additionally, with the optimal cut-off values based on the nomogram total points, patients were categorized as LTBhigh (total points ≥ 26.2) and LTBlow (total points < 26.2) groups presenting significantly different OS.
conclusionA clinically applicable nomogram incorporating four clinicopathological characteristics was constructed to predict GEP-NET patients with high-LTB. The nomogram may help clinicians identify patients with high-LTB and take optimal treatment measures to improve prognosis.
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