Correlation Between Body Composition and Pathologic Grade/Prognosis in GEP-NENs: A Retrospective Study

NCT06983106 | Completed

• 1 other identifier: TJ-IRB202411010
• Study Type: observational
• Target: 633
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Neuroendocrine Tumors

Outcome Measures

Primary Outcomes (1)

• Correlation between CT-measured abdominal fat index(cm3/m3) and pathological grade (WHO classification) in GEP-NENs

  Quantify abdominal visceral fat index(cm3/m3) ,subcutaneous fat index(cm3/m3) and intermuscular fat index(cm3/m3) using preoperative contrast-enhanced CT, and analyze their Pearson correlation coefficient with pathological grade (WHO classification: G1, G2, G3).

  Preoperative contrast-enhanced CT performed within one month before surgery

Secondary Outcomes (1)

• Correlation between CT-measured abdominal fat index(cm3/m3) and 10-year overall survival (days) in GEP-NENs

  From baseline CT to 10-year follow-up or death

Interventions

body composition calculate OTHER

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 volume of abdominal skeletal muscle and fat tissue is calculated based on CT scans at diagnosis.

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This retrospective multi-center study involved three separate medical centers. Data from April 2015 to April 2024 were obtained from the respective hospital information systems, with CT scan images retrieved from the Picture Archiving and Communication System. Patients were included based on the following criteria: (1) a confirmed diagnosis of GEP-NENs via histopathology with a WHO grading; (2) available enhanced CT scans that included full abdominal imaging before surgery or biopsy. The exclusion criteria were: (1) therapeutic interventions before surgery or biopsy; (2) poor image quality or incomplete CT images of the whole abdomen. The WHO grading was derived from the postoperative pathology reports, which were meticulously reviewed and certified by experienced senior pathologists.

You may qualify if:

• A confirmed diagnosis of GEP-NENs via histopathology with a WHO grading
• Available enhanced CT scans that included full abdominal imaging before surgery or biopsy

You may not qualify if:

• Therapeutic interventions before surgery or biopsy
• Poor image quality or incomplete CT images of the whole abdomen

Sponsors & Collaborators

• Tongji Hospital: lead

Study Sites (1)

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, 430030, China

Location

MeSH Terms

Conditions

Neuroendocrine Tumors

Condition Hierarchy (Ancestors)

Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Nerve Tissue

Study Officials

• Zhen Li, Dr

  Tongji Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: April 21, 2025
• First Posted: May 21, 2025
• Study Start: November 4, 2024
• Primary Completion: December 30, 2024
• Study Completion: March 29, 2025
• Last Updated: May 21, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)