title: A nomogram based on age, prostate-specific antigen level, prostate volume and digital rectal examination for predicting risk of prostate cancer.
abstract: Nomograms for predicting the risk of prostate cancer developed using other populations may introduce sizable bias when applied to a Chinese cohort. In the present study, we sought to develop a nomogram for predicting the probability of a positive initial prostate biopsy in a Chinese population. A total of 535 Chinese men who underwent a prostatic biopsy for the detection of prostate cancer in the past decade with complete biopsy data were included. Stepwise logistic regression was used to determine the independent predictors of a positive initial biopsy. Age, prostate-specific antigen (PSA), prostate volume (PV), digital rectal examination (DRE) status, % free PSA and transrectal ultrasound (TRUS) findings were included in the analysis. A nomogram model was developed that was based on these independent predictors to calculate the probability of a positive initial prostate biopsy. A receiver-operating characteristic curve was used to assess the accuracy of using the nomogram and PSA levels alone for predicting positive prostate biopsy. The rate for positive initial prostate biopsy was 41.7% (223/535). The independent variables used to predict a positive initial prostate biopsy were age, PSA, PV and DRE status. The areas under the receiver-operating characteristic curve for a positive initial prostate biopsy for PSA alone and the nomogram were 79.7% and 84.8%, respectively. Our results indicate that the risk of a positive initial prostate biopsy can be predicted to a satisfactory level in a Chinese population using our nomogram. The nomogram can be used to identify and counsel patients who should consider a prostate biopsy, ultimately enhancing accuracy in diagnosing prostate cancer.
authors.affiliation: Postgraduate Institute, Southern Medical University, Guangzhou 510515, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Tang
authors.forename: Hui
authors.initials: H
authors.lastname: Chen
authors.forename: Matthew
authors.initials: M
authors.lastname: Uhlman
authors.forename: Yu-Rong
authors.initials: YR
authors.lastname: Lin
authors.forename: Xiang-Rong
authors.initials: XR
authors.lastname: Deng
authors.forename: Bin
authors.initials: B
authors.lastname: Wang
authors.forename: Wen-Jun
authors.initials: WJ
authors.lastname: Yang
authors.forename: Ke-Ji
authors.initials: KJ
authors.lastname: Xie
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D044466:Asian People; D001706:Biopsy; D051517:Digital Rectal Examination; D006801:Humans; D008297:Male; D008875:Middle Aged; D049451:Nomograms; D011467:Prostate / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D017430:Prostate-Specific Antigen / Q000032:analysis*; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging; D012372:ROC Curve; D012306:Risk; D014463:Ultrasonography
chemical_list: D017430:Prostate-Specific Antigen