ArticleFrontiers in oncology2021
Development and Validation of Novel Nomograms Using Serum Tumor Markers for the Prediction of Preoperative Histologic Grades in Gastroenteropancreatic Neuroendocrine Tumors.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Beyond conventional biomarkers: the role of alpha-fetoprotein in gastroenteropancreatic neuroendocrine neoplasms.Frontiers in endocrinology · 2026Review
- Longitudinal analysis of serum alpha-fetoprotein in stable and progressive metastatic pancreatic neuroendocrine tumours.Endocrine connections · 2025Article
- Added value of multifrequency magnetic resonance elastography in predicting pathological grading of pancreatic neuroendocrine neoplasms.Insights into imaging · 2025Article
- Establishment of an Absolute Quantitative Method to Detect a Plasma tRNA-Derived Fragment and Its Application in the Non-Invasive Diagnosis of Gastric Cancer.International journal of molecular sciences · 2022Article
- Serum levels of neuron-specific enolase as a prognostic factor for disease progression in patients with GET/NEN in the pancreas and the small intestine.Endocrine connections · 2022Article
- Nomogram for preoperative estimation of histologic grade in gastrointestinal neuroendocrine tumors.Frontiers in endocrinology · 2022Article
- Multiple rectal neuroendocrine tumors: An analysis of 15 cases and literature review.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo develop and validate nomogram models for the preoperatively prediction of the histologic grade of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) to provide appropriate treatments.
methodsA total of 1014 participants, including 211 healthy controls, 293 patients with benign diseases, 299 patients with cancers, and 211 patients with GEP-NETs were included in the final analysis. Their sociodemographic and laboratory information, including serum tumor markers such as AFP, CEA, CA19-9, CA72-4, Cyfra21-1 and NSE were collected. Nomogram models were developed to preoperatively predict histologic grades of GEP-NETs.
resultsAmong six serum tumor markers, only NSE was found to have a statistically significant association with the histologic grades in GEP-NETs (G1
conclusionsWe proposed two novel nomogram models based on sex, age and serum NSE levels to preoperatively predict the histologic grades in GEP-NETs to assist the clinical decision-making.
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