Ignite Creation Date:
2024-10-25 @ 7:56 PM
Last Modification Date:
2024-10-26 @ 3:40 PM
Study NCT ID:
NCT06606912
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
None
First Post:
2024-09-16
Brief Title:
Predictive Effect of Abdominal Fat and Muscle Area Calculated Based on Abdominal CT on Gastric Cancer Patients
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Predictive Effect of Abdominal Fat and Muscle Area Calculated Based on Abdominal CT on Short- and Long-term Outcomes in Patients with Gastric Cancer
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
This study aims to create a clinical prediction model Abdominal fat and muscle area also play an important role in the prediction of surgical outcomes in colorectal cancer Studies have shown that excess visceral fat and low skeletal muscle mass sarcopenia are associated with poorer postoperative outcomes including a higher risk of postoperative complications and lower survival Preoperative imaging techniques such as CT MRI and ultrasound that provide accurate measurements to assess abdominal fat and muscle area can help surgeons develop individualized surgical and rehabilitation plans improve surgical success reduce complications and improve long-term patient prognosis In this study the investigators expected to construct a prediction model of abdominal fat and muscle area on the short- and long-term outcomes of gastric and colorectal cancer patients by calculating the abdominal fat and muscle area in different levels of abdominal CT images in order to further adjust and guide the treatment plan
Detailed Description:
This is a retrospective observational study which is expected to include patients diagnosed with gastric cancer and undergoing radical gastric cancer surgery in the Department of Gastrointestinal Surgery of the First Affiliated Hospital of Chongqing Medical University the Department of Gastrointestinal Surgery of the Second Affiliated Hospital of Chongqing Medical University the Department of Gastrointestinal Surgery of the Affiliated Yongchuan Hospital of Chongqing Medical University and the Department of Gastrointestinal Surgery of the Qijiang People39s Hospital and to discuss the predictive effects of abdominal fat and muscle area on the short-term and long-term outcomes of gastric cancer patients after surgery
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 gt18 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 50mm images Export the segmentation result as gpjformat 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 eg visceral fatskeletal 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 eg age gender BMI tumor stage etc
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 gt18 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 50mm images Export the segmentation result as gpjformat 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 eg visceral fatskeletal 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 eg age gender BMI tumor stage etc
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None