Predictive Effect of Abdominal Fat and Muscle Area Calculated Based on Abdominal CT on Gastric Cancer Patients
NCT ID: NCT06606912
Last Updated: 2024-09-23
Study Results
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Basic Information
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ACTIVE_NOT_RECRUITING
4000 participants
OBSERVATIONAL
2012-01-01
2024-12-31
Brief Summary
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Detailed Description
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1\. Case collection Patients diagnosed with gastric cancer and undergoing radical gastric cancer surgery were screened according to the inclusion criteria. All patients had signed informed consent.
Inclusion criteria:
1. Diagnosed with gastric cancer by pathology or cytology;
2. Age \>18 years;
3. Not having received chemotherapy, radiotherapy, targeted therapy or immunotherapy;
4. Patients with postoperative pathological stages other than stage IV, or without metastases in liver, lung or other distant organs confirmed by CT, MRI or B-ultrasound imaging and without surgical treatment;
5. Pre-operative CT examination data were kept in our hospital.
2\. Data collection Collect patients' preoperative baseline information such as gender, age, body mass index (BMI), complications, tumor stage, etc. Collect patients' preoperative CT scans (make sure to include images from lumbar 1 to lumbar 5). Collect patients' surgical conditions such as operation time and intraoperative bleeding. Collect patients' postoperative complications during hospitalization; 3. Prognostic follow-up Closely follow up the death or cancer recurrence of patients after surgery. 4. Outcome indicators
1. Primary outcome indicators: overall survival (OS), disease-free survival (DFS), postoperative complications.
2. Secondary outcome indicators: postoperative recovery time, hospitalization time, postoperative weight change.
5\. Image processing 3D Slicer was used to outline the range of subcutaneous fat, visceral fat, and muscle at the level of waist 1 to waist 5 on enhanced CT (5.0mm) images. Export the segmentation result as gpj.format, and select the Area Reading Calculator to calculate the area of fat and muscle at each level. Calculate fat area and muscle area at each level, calculate overall abdominal fat area and muscle area, and use the ratio of fat area to muscle area (e.g., visceral fat/skeletal muscle) as a predictor to generate the desired quantitative analyses.
6\. Statistical Analysis
1. Basic characteristics and imaging indices were described as mean and standard deviation or median and standard deviation.
2. Univariate analysis including Kaplan-Meier survival analysis and Log-rank test were used to evaluate the effects of fat and muscle area on postoperative survival and complications.
3. Multivariate analysis including Cox regression models or Logistic regression models were used to evaluate the independent predictive role of abdominal fat and muscle area on surgical outcomes, controlling for potential confounders (e.g., age, gender, BMI, tumor stage, etc.).
Conditions
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Study Design
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OTHER
RETROSPECTIVE
Interventions
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Skeletal muscle, subcutaneous fat and visceral fat area
CT-based measurement of skeletal muscle, subcutaneous fat and visceral fat areas at L1, L2, L3, L4 and L5 levels.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
2. aged \>18 years;
3. not received chemotherapy, radiotherapy, targeted therapy or immunotherapy;
4. post-operative pathological stages other than stage IV, or no liver, lung or other organs as confirmed by CT, MRI, B-ultrasound imaging.
5. patients who have pre-operative CT examination data kept in our hospital.
Exclusion Criteria
2. refusal to participate in this study.
18 Years
ALL
No
Sponsors
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The Second Affiliated Hospital of Chongqing Medical University
OTHER
Chongqing Medical University
OTHER
First Affiliated Hospital of Chongqing Medical University
OTHER
Responsible Party
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Dong Peng
Dr.
Locations
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the First Affiliated Hospital of Chongqing Medical University
Chongqing, Chongqing Municipality, China
the Second Affiliated Hospital of Chongqing Medical University
Chongqing, Chongqing Municipality, China
The Affiliated Yongchuan Hospital of Chongqing Medical University
Chongqing, Chongqing Municipality, China
Countries
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References
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Han J, Liu X, Tang M, Yang F, Ding Z, Wu G. Abdominal fat and muscle distributions in different stages of colorectal cancer. BMC Cancer. 2023 Mar 28;23(1):279. doi: 10.1186/s12885-023-10736-2.
Sun J, Lv H, Zhang M, Li M, Zhao L, Zeng N, Liu Y, Wei X, Chen Q, Ren P, Liu Y, Zhang P, Yang Z, Zhang Z, Wang Z. The Appropriateness Criteria of Abdominal Fat Measurement at the Level of the L1-L2 Intervertebral Disc in Patients With Obesity. Front Endocrinol (Lausanne). 2021 Dec 14;12:784056. doi: 10.3389/fendo.2021.784056. eCollection 2021.
Koh H, Hayashi T, Sato KK, Harita N, Maeda I, Nishizawa Y, Endo G, Fujimoto WY, Boyko EJ, Hikita Y. Visceral adiposity, not abdominal subcutaneous fat area, is associated with high blood pressure in Japanese men: the Ohtori study. Hypertens Res. 2011 May;34(5):565-72. doi: 10.1038/hr.2010.271. Epub 2011 Jan 13.
Other Identifiers
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ZZ2024-158-01
Identifier Type: -
Identifier Source: org_study_id
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