Multimodal Model Predicts Recurrence (FUTURE12)

Qun Zhao

Status: Completed

Conditions: Gastric Adenocarcinoma

Treatments: Diagnostic Test: Multimodal AI-driven predictive model

Study type: Observational

Funder types: Other

Identifiers

NCT06690268

FUTURE12

Details and patient eligibility

About

This study focuses on developing an advanced model that combines clinical information, imaging, and pathology data to predict the likelihood of cancer returning after surgery in patients with locally advanced gastric cancer. By using artificial intelligence (AI), this model analyzes various data sources to create a more accurate prediction of recurrence risk, which can help doctors, patients, and families better understand the chances of recurrence. This AI-driven approach allows healthcare providers to make more informed decisions about personalized follow-up care and potential additional treatments to improve patient outcomes.

Enrollment: 93 patients

Sex: All

Ages: 18 to 75 years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion criteria

**Inclusion Criteria:**

• Patients diagnosed with locally advanced gastric cancer (Stage II or III).
• Patients who have undergone surgical resection for gastric cancer.
• Patients with complete clinical, imaging, and pathology data available for analysis.
• Age 18 years or older.
• Patients who provide informed consent to participate in the study.

**Exclusion Criteria:**

• Patients with distant metastasis (Stage IV) at the time of diagnosis.
• Patients with incomplete or missing clinical, imaging, or pathology data.
• Patients who have received prior treatment for gastric cancer other than surgical resection.
• Patients with other concurrent malignancies.
• Patients who are unable or unwilling to comply with the study follow-up requirements.