{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12"],"submitter":["Deng X"],"pubmed_abstract":["<h4>Objective</h4>The aim of this study was to develop a predictive model to improve the accuracy of prostate cancer (PCa) detection in patients with prostate specific antigen (PSA) levels ≤20 ng/mL at the initial puncture biopsy.<h4>Methods</h4>A total of 146 patients (46 with Pca, 31.5%) with PSA ≤20 ng/mL who had undergone transrectal ultrasound-guided 12+X prostate puncture biopsy with clear pathological results at the First Affiliated Hospital of Guangxi Medical University (November 2015 to December 2021) were retrospectively evaluated. The validation group was 116 patients drawn from Changhai Hospital(52 with Pca, 44.8%). Age, body mass index (BMI), serum PSA, PSA-derived indices, several peripheral blood biomarkers, and ultrasound findings were considered as predictive factors and w"],"journal":["Frontiers in oncology"],"pagination":["985940"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9433549"],"repository":["biostudies-literature"],"pubmed_title":["Machine learning model for the prediction of prostate cancer in patients with low prostate-specific antigen levels: A multicenter retrospective analysis."],"pmcid":["PMC9433549"],"pubmed_authors":["Pradhan S","Li T","He X","Wang F","Mo L","Ji J","Mohamud BH","Deng X","Cheng J"],"additional_accession":[]},"is_claimable":false,"name":"Machine learning model for the prediction of prostate cancer in patients with low prostate-specific antigen levels: A multicenter retrospective analysis.","description":"<h4>Objective</h4>The aim of this study was to develop a predictive model to improve the accuracy of prostate cancer (PCa) detection in patients with prostate specific antigen (PSA) levels ≤20 ng/mL at the initial puncture biopsy.<h4>Methods</h4>A total of 146 patients (46 with Pca, 31.5%) with PSA ≤20 ng/mL who had undergone transrectal ultrasound-guided 12+X prostate puncture biopsy with clear pathological results at the First Affiliated Hospital of Guangxi Medical University (November 2015 to December 2021) were retrospectively evaluated. The validation group was 116 patients drawn from Changhai Hospital(52 with Pca, 44.8%). Age, body mass index (BMI), serum PSA, PSA-derived indices, several peripheral blood biomarkers, and ultrasound findings were considered as predictive factors and w","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2025-04-04T21:38:35.33Z","creation":"2025-02-19T00:41:45.982Z"},"accession":"S-EPMC9433549","cross_references":{"pubmed":["36059701"],"doi":["10.3389/fonc.2022.985940"]}}