Ignite Creation Date:
2024-05-06 @ 8:23 PM
Last Modification Date:
2024-10-26 @ 3:26 PM
Study NCT ID:
NCT06363123
Status:
RECRUITING
Last Update Posted:
2024-04-15
First Post:
2024-04-09
Brief Title:
Plasma Metabolic Biomarkers for Multi-Cancer Diagnosis
Sponsor:
Beijing Friendship Hospital
Organization:
Beijing Friendship Hospital
Study Overview
Official Title:
Identification and Validation of Plasma Diagnostic Biomarkers for Multi-Cancer Based on Metabolomics A Multi-Center Clinical Research and Validation Trial
Status:
RECRUITING
Status Verified Date:
2024-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The aim of this observational study is to comprehensively analyze the metabolites in plasma samples from multi-cancer patients using advanced mass spectrometry detection technology in conjunction with metabolomics approaches The goal is to construct a plasma metabolite database for multi-cancer patients Simultaneously we will delve into the exploration and validation of a series of metabolic biomarkers for early multi-cancer diagnosis The objective is to establish a safer more convenient and more sensitive early screening method thereby providing a reliable scientific foundation and critical evidence for improving the early diagnostic process for individuals at high risk of multi-cancer
Detailed Description:
Firstly a wide-targeted metabolomic measurement will be conducted on all samples to identify potential metabolite candidate markers and analyze differences in the metabolic profiles of patients with different types of cancer Additionally a comprehensive metabolite database specific to cancer patients will be constructed
Secondly Samples will be randomly allocated into modeling and testing cohorts The modeling cohort will be further divided into training and validation sets Bioinformatics methods will be used to conduct an in-depth analysis of a wide range of metabolite information to screen out metabolic marker combinations with high diagnostic efficacy for cancer
Ultimately the testing cohort will be used to validate these metabolic biomarkers aiming to ensure reliability and stability across different patient populations
Secondly Samples will be randomly allocated into modeling and testing cohorts The modeling cohort will be further divided into training and validation sets Bioinformatics methods will be used to conduct an in-depth analysis of a wide range of metabolite information to screen out metabolic marker combinations with high diagnostic efficacy for cancer
Ultimately the testing cohort will be used to validate these metabolic biomarkers aiming to ensure reliability and stability across different patient populations
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None