MultiParametric Magnetic Resonance Imaging-Based Nomogram for Predicting Prostate Cancer and Clinically Significant Prostate Cancer in Men Undergoing Repeat Prostate Biopsy

Abstract

Objective To develop and internally validate nomograms based on multiparametric magnetic resonance imaging (mpMRI) to predict prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in patients with a previous negative prostate biopsy. Materials and Methods The clinicopathological parameters of 231 patients who underwent a repeat systematic prostate biopsy and mpMRI were reviewed. Based on Prostate Imaging and Reporting Data System, the mpMRI results were assigned into three groups: Groups “negative,” “suspicious,” and “positive.” Two clinical nomograms for predicting the probabilities of PCa and csPCa were constructed. The performances of nomograms were assessed using area under the receiver operating characteristic curves (AUCs), calibrations, and decision curve analysis. Results The median PSA was 15.03 ng/ml and abnormal DRE was presented in 14.3% of patients in the entire cohort. PCa was detected in 75 patients (32.5%), and 59 (25.5%) were diagnosed with csPCa. In multivariate analysis, age, prostate-specific antigen (PSA), prostate volume (PV), digital rectal examination (DRE), and mpMRI finding were significantly independent predictors for PCa and csPCa (all p < 0.01). Of those patients diagnosed with PCa or csPCa, 20/75 (26.7%) and 18/59 (30.5%) had abnormal DRE finding, respectively. Two mpMRI-based nomograms with super predictive accuracy were constructed (AUCs = 0.878 and 0.927, p < 0.001), and both exhibited excellent calibration. Decision curve analysis also demonstrated a high net benefit across a wide range of probability thresholds. Conclusion mpMRI combined with age, PSA, PV, and DRE can help predict the probability of PCa and csPCa in patients who underwent a repeat systematic prostate biopsy after a previous negative biopsy. The two nomograms may aid the decision-making process in men with prior benign histology before the performance of repeat prostate biopsy.

Biomarkers in previous histologically negative prostate biopsies can be helpful in repeat biopsy decision‐making processes

“…Relatively higher rates of PCa on repeat biopsy, ranging from 20% to 34%, have been reported by previous studies. [3][4][5] However, the criteria or indications for making a decision to perform a repeat biopsy procedure are not well defined. The AUC of models constructed by traditional clinical parameters in the repeat biopsy is only approximately 70%.…”

“…However, because of the 20 to 40% false-negative rate of the initial biopsy and persistent abnormal clinical-pathological parameters more than 50% of patients who undergo initial biopsy are left with doubt regarding the potential presence of PCa and need repeat biopsy after a period of follow-up. [2][3][4][5] Despite the numbers of traditional clinical-pathological parameters, including prostate-specific antigen (PSA), percentage of free-PSA (fPSA), PSA velocity, and presence of high-grade prostatic intraepithelial neoplasia (HGPIN) or atypical small acinar proliferation (ASAP) in the previous negative biopsy tissues were used to screen patients for repeat biopsy, unfortunately, the positive biopsy rate among men undergoing repeat biopsy is only approximately 20% to 40% and high grade PCa (HGPCa) accounted for less than half, which suggests that three out of every five biopsies are unnecessary. [2][3][4][5][6] Prostate biopsy can be painful, anxiety-provoking, expensive, and potentially morbid, so there is an urgent need to supplement the above mentioned traditional parameters with novel biomarkers that enhance its specificity so that unnecessary biopsies can be avoided.…”

Multivariate risk prediction tools including MRI for individualized biopsy decision in prostate cancer diagnosis: current status and future directions

“…Huang et al [27] developed an MRI risk prediction model, based on age, PSA, prostate volume, and DRE, incorporating mpMRI (PI-RADS 1-5). The AUC for G ≥ 2 PCa for the developing cohort (n = 231, with a prevalence 25.5%) was 0.93 [0.89-0.96] (p < 0.001) ( Table 2).…”

“…The accuracy of the systematic biopsy is dependent on the number of cores. Most studies reported a transrectal approach with a median of 12 biopsy cores (Table 1) [20,[22][23][24][25][26][27]30]. However, three studies used a transperineal approach with biopsy cores ranging from 24 to 40 [21,28,29].…”

“…Due to the predictive value of mpMRI in PCa diagnosis, recently new multivariate risk prediction tools have been constructed, with the inclusion of the mpMRI suspicion score [20][21][22][23][24][25][26][27][28][29]. The purpose of this review is to explore the performance of these new MRI risk models for indicating a biopsy for prostate cancer diagnosis.…”