The goal of this diagnostic test is to obtain multiple cell-free DNA (cfDNA) fragment profiles of subjects by whole genome sequencing based on plasma cfDNA, build a prostate cancer prediction model by machine learning, and to validate the efficacy of this model in patients who need to undergo needle prostate biopsy base on their prostate-specific antigen(PSA) or clinical or imaging evidence. Therefore, this study aims to explore the efficacy of this prostate cancer prediction model in distinguishing between patients with PSA "gray zone" (4-10 ng/ml) in the diagnosis of prostate cancer and patients with clinically significant prostate cancer.
Study Type
OBSERVATIONAL
Enrollment
1,100
Before undergoing a prostate biopsy, participants will have about 10 mLs of venous blood drawn. Blood will be sent to Geneseeq Technology Inc. for whole genome high-throughput sequencing of plasma cfDNA.
Changzheng hospital
Shanghai, Shanghai Municipality, China
RECRUITINGAUROC value for predicting positive needle biopsy results (prostate cancer) in individuals with PSA levels in the gray zone.
Time frame: Through completion of study and all data analysis which may take up to one and a half years.
Sensitivity for predicting positive needle biopsy results (prostate cancer) in individuals with PSA levels in the gray zone.
Time frame: Through completion of study and all data analysis which may take up to one and a half years.
Specificity for predicting positive needle biopsy results (prostate cancer) in individuals with PSA levels in the gray zone.
Time frame: Through completion of study and all data analysis which may take up to one and a half years.
AUROC value for predicting clinically significant prostate cancer (GS > 7) in pathological results.
Time frame: Through completion of study and all data analysis which may take up to one and a half years.
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