External validation and comparison of magnetic resonance imaging-based risk prediction models for prostate biopsy stratification.

PURPOSE: Magnetic resonance imaging (MRI) is a promising tool for risk assessment, potentially reducing the burden of unnecessary prostate biopsies. Risk prediction models that incorporate MRI data have gained attention, but their external validation and comparison are essential for guiding clinical practice. The aim is to externally validate and compare risk prediction models for the diagnosis of clinically significant prostate cancer (csPCa). METHODS: A cohort of 4606 patients across fifteen European tertiary referral centers were identified from a prospective maintained database between January 2016 and April 2023. Transrectal or transperineal image-fusion MRI-targeted and systematic biopsies for PI-RADS score of ≥ 3 or ≥ 2 depending on patient characteristics and physician preferences. Probabilities for csPCa, defined as International Society of Urological Pathology (ISUP) grade ≥ 2, were calculated for each patients using eight models. Performance was characterized by area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Subgroup analyses were performed across various clinically relevant subgroups. RESULTS: Overall, csPCa was detected in 2154 (47%) patients. The models exhibited satisfactory performance, demonstrating good discrimination (AUC ranging from 0.75 to 0.78, p < 0.001), adequate calibration, and high net benefit. The model described by Alberts showed the highest clinical utility for threshold probabilities between 10 and 20%. Subgroup analyses highlighted variations in models' performance, particularly when stratified according to PSA level, biopsy technique and PI-RADS version. CONCLUSIONS: We report a comprehensive external validation of risk prediction models for csPCa diagnosis in patients who underwent MRI-targeted and systematic biopsies. The model by Alberts demonstrated superior clinical utility and should be favored when determining the need for a prostate biopsy.

The impact of prostate volume estimation on the risk-adapted biopsy decision based on prostate-specific antigen density and magnetic resonance imaging score.

PURPOSE: Utility of prostate-specific antigen density (PSAd) for risk-stratification to avoid unnecessary biopsy remains unclear due to the lack of standardization of prostate volume estimation. We evaluated the impact of ellipsoidal formula using multiparametric magnetic resonance (MRI) and semi-automated segmentation using tridimensional ultrasound (3D-US) on prostate volume and PSAd estimations as well as the distribution of patients in a risk-adapted table of clinically significant prostate cancer (csPCa). METHODS: In a prospectively maintained database of 4841 patients who underwent MRI-targeted and systematic biopsies, 971 met inclusions criteria. Correlation of volume estimation was assessed by Kendall's correlation coefficient and graphically represented by scatter and Bland-Altman plots. Distribution of csPCa was presented using the Schoots risk-adapted table based on PSAd and PI-RADS score. The model was evaluated using discrimination, calibration plots and decision curve analysis (DCA). RESULTS: Median prostate volume estimation using 3D-US was higher compared to MRI (49cc[IQR 37-68] vs 47cc[IQR 35-66], p < 0.001). Significant correlation between imaging modalities was observed (τ = 0.73[CI 0.7-0.75], p < 0.001). Bland-Altman plot emphasizes the differences in prostate volume estimation. Using the Schoots risk-adapted table, a high risk of csPCa was observed in PI-RADS 2 combined with high PSAd, and in all PI-RADS 4-5. The risk of csPCa was proportional to the PSAd for PI-RADS 3 patients. Good accuracy (AUC of 0.69 and 0.68 using 3D-US and MRI, respectively), adequate calibration and a higher net benefit when using 3D-US for probability thresholds above 25% on DCA. CONCLUSIONS: Prostate volume estimation with semi-automated segmentation using 3D-US should be preferred to the ellipsoidal formula (MRI) when evaluating PSAd and the risk of csPCa.

The Added Value of Side-specific Systematic Biopsy in Patients Diagnosed by Magnetic Resonance Imaging-targeted Prostate Biopsy.

BACKGROUND: Systematic biopsy (SB) combined with magnetic resonance imaging (MRI)-targeted biopsy is still recommended considering the risk of missing clinically significant prostate cancer (csPCa). OBJECTIVE: To evaluate the added value in csPCa detection on side-specific SB relative to MRI lesion and to externally validate the Noujeim risk stratification model that predicts the risk of csPCa on distant SB cores relative to the index MRI lesion. DESIGN, SETTING, AND PARTICIPANTS: Overall, 4841 consecutive patients diagnosed by MRI-targeted biopsy and SB for Prostate Imaging Reporting and Data System score ≥3 lesions were identified from a prospectively maintained database between January 2016 and April 2023 at 15 European referral centers. A total of 2387 patients met the inclusion criteria and were included in the analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: McNemar's test was used to compare the csPCa detection rate between several biopsy strategies including MRI-targeted biopsy, side-specific SB, and a combination of both. Model performance was evaluated in terms of discrimination using area under the receiver operation characteristic curve (AUC), calibration plots, and decision curve analysis. Clinically significant prostate cancer was defined as International Society of Urological Pathology grade group ≥2. RESULTS AND LIMITATIONS: Overall, the csPCa detection rate was 49%. Considering MRI-targeted biopsy as reference, the added values in terms of csPCa detection were 5.8% (relative increase of 13%), 4.2% (relative increase of 9.8%), and 2.8% (relative increase of 6.1%) for SB, ipsilateral SB, and contralateral SB, respectively. Only 35 patients (1.5%) exclusively had csPCa on contralateral SB (p < 0.001). Considering patients with csPCa on MRI-targeted biopsy and ipsilateral SB, the upgrading rate was 2% (20/961) using contralateral SB (p < 0.001). The Noujeim model exhibited modest performance (AUC of 0.63) when tested using our validation set. CONCLUSIONS: The added value of contralateral SB was negligible in terms of cancer detection and upgrading rates. The Noujeim model could be included in the decision-making process regarding the appropriate prostate biopsy strategy. PATIENT SUMMARY: In the present study, we collected a set of patients who underwent magnetic resonance imaging (MRI)-targeted and systematic biopsies for the detection of prostate cancer. We found that biopsies taken at the opposite side of the MRI suspicious lesion have a negligible impact on cancer detection. We also validate a risk stratification model that predicts the risk of cancer on biopsies beyond 10 mm from the initial lesion, which could be used in daily practice to improve the personalization of the prostate biopsy.