PREDICT is a prospective, multi-center study for the early detection of pan-cancer through cell-free DNA (cfDNA) methylation based model, in which approximately 14,000 participants will be enrolled. The development and validation of the model will be conducted in participants with early stage cancers or benign diseases, along with non-tumor (healthy) individuals through a two-stage approach. The sensitivity and specificity of the model in cancer early detection will be evaluated, and the accuracy of the identification for tissue of origin will be obtained.
Study Type
OBSERVATIONAL
Enrollment
14,026
Cancer Hospital, Chinese Academy of Medical Sciences & China National Cancer Center
Beijing, Beijing Municipality, China
Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine
Shanghai, Shanghai Municipality, China
Zhongshan Hospital, Fudan University
Shanghai, Shanghai Municipality, China
The cfDNA methylations profiles of patients with malignancies or benign diseases using pre-treatment biospecimens.
Time frame: 32 months
The sensitivity and specificity of multi-cancer early detection and the accuracy of TOO identification via cfDNA methylation based model.
Time frame: 32 months
The sensitivity and specificity of cancer early detection and the accuracy of TOO identification via cfDNA methylation based model in pre-specified subgroups.
Time frame: 32 months
The sensitivity and specificity of cancer early detection and the accuracy of TOO identification via cfDNA methylation based model in combination with clinicopathological characteristics or other biomarkers.
Time frame: 32 months
The examinations related to cancer diagnosis from the participants who were identified as positive cases by cfDNA methylation based model while as healthy individuals by routine medical examinations.
Time frame: 32 months
The sensitivity and specificity of cancer early detection and the accuracy of TOO identification via cfDNA methylation based model in the independent training and validation sets.
Time frame: 32 months
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