PROFOUND Study: Development and Validation of a Multi-cancer Early Detection Model Based on Peripheral Blood Multi-omic Analysis and Machine Learning: a Multicenter, Prospective, Observational, Case-control Study
PROFOUND Study: Development and Validation of a Multi-cancer Early Detection Model Based on Peripheral Blood Multi-omic Analysis and Machine Learning: a Multicenter, Prospective, Observational, Case-control Study
This study is a multi-center, case-control study aiming at developing and blinded testing machine learning-based multiple cancers early detection model by prospectively collecting blood samples from newly diagnosed cancer patients and individuals without confirmed cancer diagnosis.
Blood samples from newly diagnosed cancer patients and individuals without confirmed cancer diagnosis will be prospectively collected to identify cancer-specific circulating signals through integrative multi-omic analysis. Based on the comprehensive molecular profiling, a machine learning-driven model will be trained and blinded validated independent through a two-stage approach in clinically annotated individuals. Approximately 10327 cancer patients will be enrolled in this study and early-stage cancer patients will be enriched to improve the model sensitivity on distinguishing cancers with favorable prognosis. Approximately 6339 age and sex matched controls will be included in model development, which are volunteers without a cancer diagnosis after routine cancer screening tests.
Inclusion Criteria for Case Arm Participants:
Exclusion Criteria for Case Arm Participants:
Inclusion Criteria for Control Arm Participants:
Exclusion Criteria for Control Arm Participants:
qinyong@bytedance.com+86 186 2629 2273