Predictors of clinically significant prostate cancer in biopsy-naïve and prior negative biopsy men with a negative prostate MRI: improving MRI-based screening with a novel risk calculator

Abstract

Purpose: A pre-biopsy decision aid is needed to counsel men with a clinical suspicion for clinically significant prostate cancer (csPCa), despite normal prostate magnetic resonance imaging (MRI). Methods: A risk calculator (RC) for csPCa (International Society of Urological Pathology grade group (ISUP) ⩾ 2) presence in men with a negative-MRI (Prostate Imaging–Reporting and Data System (PI-RADS) ⩽ 2) was developed, and its performance was compared with RCs of the European Randomized Study of Screening for Prostate Cancer (ERSPC), Prostate Biopsy Collaborative Group (PBCG), and Prospective Loyola University mpMRI (PLUM). All biopsy-naïve and prior negative biopsy men with a negative-MRI followed by systematic prostate biopsy were included from October 2015 to September 2021. The RC was developed using multivariable logistic regression with the following parameters: age (years), family history of PCa (first- or second-degree family member), ancestry (African Caribbean/other), digital rectal exam (benign/malignant), MRI field strength (1.5/3.0 Tesla), prior negative biopsy status, and prostate-specific antigen (PSA) density (ng/ml/cc). Performance of RCs was compared using receiver operating characteristic (ROC) curve analysis. Results: A total of 232 men were included for analysis, of which 18.1% had csPCa. Parameters associated with csPCa were family history of PCa ( p < 0.0001), African Caribbean ancestry ( p = 0.005), PSA density ( p = 0.002), prior negative biopsy ( p = 0.06), and age at biopsy ( p = 0.157). The area under the curve (AUC) of the developed RC was 0.76 (95% CI 0.68–0.85). This was significantly better than the RCs of the ERSPC (AUC: 0.59; p = 0.001) and PBCG (AUC: 0.60; p = 0.002), yet similar to PLUM (AUC: 0.69; p = 0.09). Conclusion: The developed RC (Prostate Biopsy Cohort Amsterdam (‘PROBA’ RC), integrated predictors for csPCa at prostate biopsy in negative-MRI men and outperformed other widely used RCs. These findings require external validation before introduction in daily practice.

Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer

“…A total of 72 studies including 36 366 patients with suspected csPCa who underwent prostate MRI and subsequent biopsy were included (Figure 1). Details of the included study and patient characteristics are summarized in Table 1 and eTables 3 to 5 in Supplement 1. Studies were published between 2016 and 2022.…”

“…As such, ancillary clinical data have been proposed to complement MRI to minimize the number of unnecessary biopsies. This concept has been recently expanded by numerous studies, and several MRI-based risk models and strategies have been developed to guide decisions on prostate biopsy . However, it has been challenging to integrate the proposed approaches into clinical practice owing to considerable inconsistencies among them.…”

“…BMI (9 studies,13,17,19,24,25,31,39,49,79 3946 patients) 24.7 (24.2-30.8)Positive family history of PCa (16 studies,12,24,26,38,44,46,49,52,56,58,[62][63][64][72][73][74] 10 095 patients), %17 (1-35)Positive DRE (33 studies,10, 15, 17, 18, 21-23, 26, 31-33, 37, 38, 41, 42, 44-47, 51-53, 56, 58, 62-64, 72-74, 77, 78, 81 19 129 patients), %23 (7-68)Black race (5 studies,12,15,46,66,79 1880 patients), % 14 (1-29) Prior negative biopsy (58 studies, 10-13, 15, 17, 18, 21-26, 28, 29, 31, 33-35, 37-58, 60-67, 70-74, 76-79 31 177 patients), % 18 (0-100) Abbreviations: BMI, body mass index (measured as weight in kilograms divided by height in meters squared); csPCa, clinically significant prostate cancer; DRE, digital rectal examination; MRI, magnetic resonance imaging; PI-RADS, Prostate Imaging Reporting & Data System; PSA, prostate-specific antigen; PSAD, prostate-specific antigen density. SI conversion factor: To convert PSA levels to μg/L, multiply by 1.0. a Specified per row.…”

Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

“…We compared six methods that have been proposed for handling missing data with the objective of finding the method most likely to perform well in multiple external validation studies of a globally accessible online risk tool. As with all online risk tools, online publication of the original PBCG continues to result in published external validation studies providing evidence for or against its generalizability to other populations, particularly in comparison to other published tools [4,[21][22][23][24][25][26]. To date, by exclusion of prostate volume, the original PBCG tool has competed less favorably with the other tools incorporating this information.…”

Globally accessible end-user-friendly prostate cancer risk prediction tools based on contemporary cohorts with heterogeneous missing risk factors

“…We compared six methods that have been proposed for handling missing data with the objective of nding the method most likely to perform well in multiple external validation studies of a globally accessible online risk tool. As with all online risk tools, online publication of the original PBCG continues to result in published external validation studies providing evidence for or against its generalizability to other populations, particularly in comparison to other published tools [21,22,23,24,25,26,27]. To date, by exclusion of prostate volume, the original PBCG tool has competed less favorably with the other tools incorporating this information.…”