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Value of Automatically Segmented Three-Dimensional(3D) Volumetric Body Composition in Predicting the Pathological Grading and Prognosis of Gastroenteropancreatic Neuroendocrine Neoplasms: A Multicenter Study
The goal of this observational study is to learn about the value of body composition as predictors of pathological grading and prognosis in patients with gastroenteropancreatic neuroendocrine neoplasms. The main question it aims to answer is: Does body composition affect the pathological grading and prognosis of patients with gastroenteropancreatic neuroendocrine tumors? Participants with gastroenteropancreatic neuroendocrine neoplasms will answer questions about their physical condition during follow-up visits.
Objectives To explore the value of body composition parameters (BCPs) as predictors of pathological grading, prognosis in patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). Methods This retrospective multicenter analysis enrolled GEP-NENs patients pathologically confirmed from three institutions between 2015 and 2024. The volume of skeletal muscle and abdominal fat tissue was calculated based on CT scans at diagnosis. Univariate and multivariate logistic regression analyses were used to identify the relationships between BCPs and the pathological grade. The Kaplan-Meier method, along with the log-rank test, was employed for survival analysis. Independent prognostic factors were identified through uni- and multivariable Cox regression analyses.
Age
All ages
Sex
ALL
Healthy Volunteers
No
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, China
Start Date
November 4, 2024
Primary Completion Date
December 30, 2024
Completion Date
March 29, 2025
Last Updated
May 21, 2025
633
ACTUAL participants
body composition calculate
OTHER
Lead Sponsor
Tongji Hospital
NCT05746208
NCT06228066
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