Ignite Creation Date:
2024-05-06 @ 8:23 PM
Last Modification Date:
2024-10-26 @ 3:26 PM
Study NCT ID:
NCT06364371
Status:
RECRUITING
Last Update Posted:
2024-04-15
First Post:
2024-04-02
Brief Title:
Dynamic Multi-omics Integration Model to Predict Neoadjuvant Therapy Response in Locally Advanced Rectal Cancer
Sponsor:
Sixth Affiliated Hospital Sun Yat-sen University
Organization:
Sixth Affiliated Hospital Sun Yat-sen University
Study Overview
Official Title:
A Study of the Clinical Value of Dynamic Multi-omics Integration Model to Predict Neoadjuvant Therapy Response in Locally Advanced Rectal Cancer T3-4NxM0
Status:
RECRUITING
Status Verified Date:
2023-06
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 goal of this observational study is to establish a dynamic multi-omics integration model for predicting pathological complete response pCR after neoadjuvant treatment in locally advanced T3-4NxM0 rectal cancer providing support for subsequent patient selection for the watch-and-wait strategy The main question it aims to answer is
What is the predictive value of this model to assess individual achievement of pathological complete response pCR after neoadjuvant treatment Eligible patients will be prospectively enrolled and the clinical features of their pre-neoadjuvant treatment during-treatment and post-treatment preoperative will be collected and annotated
What is the predictive value of this model to assess individual achievement of pathological complete response pCR after neoadjuvant treatment Eligible patients will be prospectively enrolled and the clinical features of their pre-neoadjuvant treatment during-treatment and post-treatment preoperative will be collected and annotated
Detailed Description:
This is a single-center prospective observational phase II clinical study aimed at validating a dynamic multi-omics imaging pathology molecular biomarkers integration model for predicting pathological complete response pCR after neoadjuvant treatment in locally advanced T3-4NxM0 rectal cancer Specifically the study aims to validate the predictive accuracy of the dynamic multi-omics prediction model and determine whether it outperforms other conventional prediction models based on single-modality imaging pathology and molecular biomarkers
Eligible patients will be prospectively enrolled and images of their pre-neoadjuvant treatment during-treatment and post-treatment preoperative magnetic resonance imaging MRI scans histopathology slides stained with hematoxylin and eosin HE carcinoembryonic antigen CEA and circulating tumor DNA ctDNA will be collected and annotated MRI HE images CEA ctDNA and their change features will be applied to the prediction model to assess individual achievement of pathological complete response pCR after neoadjuvant treatment The predictive results will be further compared with the pathological tumor response obtained from resected specimens
Eligible patients will be prospectively enrolled and images of their pre-neoadjuvant treatment during-treatment and post-treatment preoperative magnetic resonance imaging MRI scans histopathology slides stained with hematoxylin and eosin HE carcinoembryonic antigen CEA and circulating tumor DNA ctDNA will be collected and annotated MRI HE images CEA ctDNA and their change features will be applied to the prediction model to assess individual achievement of pathological complete response pCR after neoadjuvant treatment The predictive results will be further compared with the pathological tumor response obtained from resected specimens
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