A new model for patients with PSA ranging from 4 to 10 ng/ml to reduce unnecessary prostate biopsies and developing a follow-up strategy

Abstract

Objective Developing a follow-up strategy to reduce unnecessary prostate biopsies in patients with prostate specific antigen (PSA) ranging from 4 to 10 ng/ml based on the new model. Methods In the first stage, 436 patients with PSA ranging from 4 to 10 ng/ml who had undergone transrectal ultrasound (TRUS)-guided prostate biopsy were evaluated. PSA, free PSA (fPSA), digital rectal examination (DRE) findings, ultrasonic hypoechoic mass, ultrasonic microcalcifications, prostate volume (PV), PSA density (PSAD) and age, were regarded as predictive factors. In order to select independent predictors, a multiple logistic regression analysis involving a backward elimination selection procedure was applied. Based on the comprehensive analysis of the results, a new model to evaluate the risk of prostate cancer and an effective follow-up strategy were developed. Results Our model included PSA, PV, fPSA, age, rate of abnormal DRE findings and rate of hypoechoic masses detected by TRUS. When compared with using PSA alone, an evidently large area under the receiver-operating characteristic curve was obtained in our model(0.782 vs. 0.566). According to the degree of prostate cancer risk (PCaR), patients were divided into two groups. In the second stage of our study, prostate biopsies were implemented immediately for patients with PCaR>0.52 while the rest of the patients underwent closely follow-up. Compared with the first stage, the detectable rate of PCa in the second stage was significantly increased (33.0% vs. 21.1%, P=0.012). There was no significant difference between the two stages in the distribution of Gleason score (P=0.808). Conclusions A follow-up strategy were developed based on the new model to improve the PCa detection rate, which reduced unnecessary prostate biopsies without delaying the diagnosis and treatment of the patients. Key words: Prostate specific antigen (PSA); Model; Prostate biopsy; Prostate cancer risk (PCaR)