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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.
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Inclusion criteria
Male, 18-80 years old;
PSA: 4-10ng/ml;
Patients scheduled for prostate biopsy:
Exclusion criteria
1,100 participants in 1 patient group
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Central trial contact
Shancheng Ren, MD,PhD
Data sourced from clinicaltrials.gov
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