Clinical Translation Research on a Multi-omics Breast Cancer Distant Metastasis Prediction Model Empowered by Artificial Intelligence

Second Affiliated Hospital, Zhejiang University, School of Medicine2,000 enrolled

Overview

Breast cancer is one of the most common malignancies in women worldwide, and distant metastasis is the main cause of poor prognosis and death. This project aims to construct a precision prediction system based on multi-omics (digital pathology, immunohistochemistry, proteomics, gene sequencing) and artificial intelligence to predict distant and organ-specific metastasis (bone, lung, liver, brain) in breast cancer, analyze its mechanisms, and provide new solutions for precision medicine.

Study Type

OBSERVATIONAL

Enrollment

2,000

Conditions

Breast Breast Cancer Pathology

Eligibility

Sex: FEMALE

Medical Language ↔ Plain English

Inclusion Criteria: 1. Female patients pathologically diagnosed with breast cancer at our hospital or participating centers between January 1, 2000, and December 30, 2028. 2. Must meet one of the following: 1) Initially diagnosed with breast cancer at our hospital, has developed distant metastasis (liver, bone, lung, or brain), and has a biopsy or surgical specimen from the metastatic site stored at our hospital, with complete clinical information available. 2) Primary tumor specimen is not at our hospital, but a biopsy or surgical specimen from a distant metastatic site (liver, bone, lung, brain) is stored at our hospital. Exclusion Criteria: 1. Concomitant metastatic malignancy from another primary cancer. 2. Incomplete clinical information.

Outcomes

Primary Outcomes

Metastasis-Free Survival

Time from initial breast cancer diagnosis to the occurrence of distant metastasis.

Time frame: From diagnosis up to December 30, 2028

Secondary Outcomes

Performance of Prediction Models

Evaluate the performance of (1) the metastatic risk stratification model, (2) the organ-specific metastasis prediction model, and (3) the metastasis time-window prediction model. Measure: Accuracy and Area Under the Curve (AUC). (Target accuracy ≥80%, AUC ≥0.80)

Time frame: At the end of the study (December 2028)