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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.
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 (H&E), carcinoembryonic antigen (CEA), and circulating tumor DNA (ctDNA) will be collected and annotated. MRI, H&E 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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Observational cohort | Patients with locally advanced (T3-4NxM0) rectal adenocarcinoma |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Medical examination | Other | 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 (H&E), carcinoembryonic antigen (CEA), and circulating tumor DNA (ctDNA) will be collected and annotated. |
| Measure | Description | Time Frame |
|---|---|---|
| Area under curve(AUC) | Area under curve of prediction model | through study completion, an average of 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity | Sensitivity of prediction model | through study completion, an average of 6 months |
| Specificity | Specificity of prediction model |
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Inclusion Criteria:
Exclusion Criteria:
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Patients are pathological confirmed as rectal adenocarcinoma, clinical stage T3-4NxM0, and underwent the neoadjuvant therapy before surgical treatment.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jun Huang | Contact | +86-13926451242 | huangj97@mail.sysu.edu.cn | |
| Meijin Huang | Contact | +86-13924073322 | meijinhuang3@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Jun Huang | Sun Yat-sen University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Sixth Affiliated Hospital, Sun Yatsen University | Recruiting | Guangzhou | Guangdong | China |
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| ID | Term |
|---|---|
| D000095384 | Pathologic Complete Response |
| ID | Term |
|---|---|
| D018450 | Disease Progression |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D000070536 | Independent Medical Evaluation |
| ID | Term |
|---|---|
| D017531 | Health Care Evaluation Mechanisms |
| D011787 | Quality of Health Care |
| D017530 | Health Care Quality, Access, and Evaluation |
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| through study completion, an average of 6 months |
| Negative predictive value(NPV) | negative predictive value of prediction model | through study completion, an average of 6 months |
| Positive predictive value(PPV) | positive predictive value of prediction model | through study completion, an average of 6 months |