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| Name | Class |
|---|---|
| Shijiazhuang People's Hospital | OTHER |
| Baoding Central Hospital | UNKNOWN |
| Hengshui People's Hospital | OTHER |
| Wuhan University Affiliated People's Hospital |
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Gastric cancer is a major global health challenge. Currently, a combination of chemotherapy and immunotherapy (PD-1 inhibitors) is frequently used before surgery to shrink tumors, a strategy known as neoadjuvant therapy. While this approach is effective for many patients, responses vary significantly, and there are currently no reliable tools to predict which patients will benefit the most before treatment begins.
The PRISM-GC study aims to develop and validate a novel Artificial Intelligence (AI) system to address this need. This is a prospective, observational study that will collect data from patients diagnosed with locally advanced gastric cancer who are scheduled to receive standard neoadjuvant chemotherapy combined with immunotherapy in a real-world clinical setting. The specific choice of immunotherapy drug is determined by the treating physician and is not dictated by the study.
Researchers will analyze standard preoperative CT scans and pathological tissue slides using advanced deep learning algorithms. The goal is to create a "multimodal" AI model that can accurately predict how well a tumor will respond to treatment (specifically, whether the tumor will disappear or shrink significantly). If successful, this AI tool could help doctors personalize treatment plans in the future, ensuring that each patient receives the most effective therapy while avoiding unnecessary side effects.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| LAGC Pan-Immunotherapy Cohort | Patients diagnosed with locally advanced gastric cancer (cT3-4a, N+) who are scheduled to receive neoadjuvant chemotherapy combined with PD-1 inhibitors (including but not limited to Sintilimab, Tislelizumab, Camrelizumab, etc.) in a real-world clinical setting. The specific choice of immunotherapy regimen is determined by the treating physician. Multimodal data, including preoperative contrast-enhanced CT images, pathological whole-slide images, and biospecimens (blood/tissue), will be collected for AI model development and validation. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Standard of Care PD-1 Inhibitors | Drug | Patients receive standard neoadjuvant chemotherapy (e.g., SOX or XELOX regimen) combined with any NMPA-approved PD-1 inhibitor (including but not limited to Sintilimab, Tislelizumab, Camrelizumab, etc.) as determined by the treating physician in real-world practice. |
| Measure | Description | Time Frame |
|---|---|---|
| Predictive Accuracy of the Multimodal AI Model for Pathological Complete Response (pCR) | The performance of the DeepComp AI model in predicting pCR will be evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC). The model's predictions (based on preoperative baseline CT and pathology slides) will be compared with the ground truth postoperative pathological results. Secondary metrics including sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) will also be calculated. | From baseline assessment to postoperative pathological evaluation (approximately 5 months) |
| Pathological Complete Response (pCR) Rate | Defined as the complete absence of viable tumor cells in the resected specimen (primary tumor and lymph nodes, ypT0N0), assessed according to standard pathological guidelines (TRG 0). This outcome measures the real-world efficacy of neoadjuvant chemo-immunotherapy across the cohort. | At the time of postoperative pathological evaluation (approximately 1 month after surgery) |
| Measure | Description | Time Frame |
|---|---|---|
| 3-Year Disease-Free Survival (DFS) | 3 years post-surgery |
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Inclusion Criteria:
Age ≥ 18 years.
Histologically confirmed gastric or gastroesophageal junction adenocarcinoma.
Clinical stage cT3-4a, N+, M0 (locally advanced) assessed by CT/MRI and endoscopic ultrasound.
Scheduled to receive neoadjuvant chemotherapy combined with PD-1 inhibitors (regimens including but not limited to SOX/XELOX + Sintilimab/Tislelizumab/Camrelizumab, etc.) as standard of care.
Availability of standard pre-treatment contrast-enhanced abdominal CT images.
Willingness to provide peripheral blood samples and tumor tissue (biopsy/surgical) for sequencing and analysis.
ECOG performance status 0-1.
Adequate organ function to tolerate systemic chemotherapy.
Exclusion Criteria:
Evidence of distant metastasis (Stage IV) or unresectable disease.
Previous systemic anti-tumor therapy for gastric cancer (chemotherapy, radiotherapy, or immunotherapy).
History of other malignancies within the past 5 years.
Active autoimmune diseases requiring systemic immunosuppressive treatment (contraindication for PD-1 inhibitors).
Emergency surgery due to obstruction, perforation, or uncontrolled bleeding.
Severe metallic artifacts on CT images that interfere with radiomic feature extraction.
Pregnancy or lactation.
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Adult patients with locally advanced gastric cancer who are admitted to the participating centers and are scheduled to undergo neoadjuvant chemo-immunotherapy according to real-world clinical practice.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Qun Zhao | Contact | +8631186095363 | zhaoqun@hebmu.edu.cn |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Fifth Affiliated Hospital of Anhui Medical University | Recruiting | Fuyang | Anhui | 050011 | China |
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| ID | Term |
|---|---|
| D013274 | Stomach Neoplasms |
| ID | Term |
|---|---|
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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| UNKNOWN |
| The Fifth Affiliated Hospital of Anhui Medical University | UNKNOWN |
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Tumor tissue samples (including preoperative biopsy and postoperative surgical resection specimens) and matched peripheral blood samples will be retained. These specimens will be processed for DNA/RNA extraction to perform Next-Generation Sequencing (NGS) and multi-omics analysis. The goal is to identify molecular biomarkers and genetic alterations associated with sensitivity or resistance to neoadjuvant immunotherapy.
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| Multimodal AI Assessment | Diagnostic Test | Non-invasive assessment using a multimodal deep learning system (DeepComp) to analyze preoperative contrast-enhanced CT images and pathological slides. The AI model predicts the probability of pathological complete response (pCR) but does not alter the clinical treatment plan. |
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| Cangzhou People's Hospital | Recruiting | Cangzhou | Hebei | 050011 | China |
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| Hengshui People's Hospital | Recruiting | Hengshui | Hebei | 053099 | China |
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| The Second Affiliated Hospital of Xingtai Medical College | Recruiting | Xingtai | Hebei | 050011 | China |
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| Renmin Hospital of Wuhan University | Recruiting | Wuhan | Hubei | 430065 | China |
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| Yichang Central Hospital | Recruiting | Yichang | Hubei | 448000 | China |
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| Baoding Central Hospital | Recruiting | Baoding | None Selected | 050011 | China |
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| Shijiazhuang People's Hospital | Recruiting | Shijiazhuang | None Selected | 050011 | China |
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| the Fourth Hospital of Hebei Medical University | Recruiting | Shijiazhuang | None Selected | 050011 | China |
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| D004066 |
| Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D013272 | Stomach Diseases |