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

Schoots, Ivo G.; Roobol, Monique J.

doi:10.1007/s00345-019-02707-9

Cited by 38 publications

(32 citation statements)

References 43 publications

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“…Clinical decision making in patients with a prostate cancer diagnosis incorporating MRI findings is inherently complex, and there is no optimal way to balance the gains (eg, correctly diagnosing clinically significant cancers or avoiding unnecessary biopsy) and losses (eg, missing clinically significant cancers or diagnosing clinically insignificant disease). Decision curve analyses (77) and prostate cancer risk calculators (16,17) can be helpful when managing the complex information for patient decision making regarding the need for biopsy after MRI (78).…”

Section: Recommendations For Mri-directed Biopsymentioning

confidence: 99%

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

Padhani¹,

Barentsz²,

Villeirs³

et al. 2019

Radiology

176

118

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he current version of the Prostate Imaging Reporting and Data System (PI-RADS) was formulated on experience gained from PI-RADS version 1, accumulated scientific evidence, and expert consensus (1). The release of PI-RADS version 2.1 is expected to further improve observer variability (2). A recent publication evaluated multiple clinical studies, systematic analyses, and professional guidelines on their use of multiparametric MRI in prostate cancer detection (3). It showed that the test performance of multiparametric MRI-directed biopsy in the detection of prostate cancer is superior to that of systematic transrectal US-guided biopsy. High-level evidence has now established multiple benefits of MRI-directed biopsy over systematic transrectal US-guided biopsy of the prostate (4). These benefits include (a) a reduction in the number of men who need to undergo biopsy (5-9); (b) a reduction in the number of diagnoses of clinically insignificant cancers that are unlikely to cause harm (4,10), with the potential to reduce overtreatment, treatment-related complications, and active surveillance rates (6); (c) improved detection of clinically significant prostate cancers, particularly in patients with prior negative transrectal US-guided biopsy findings (4,10); and (d) improved risk stratification of diagnosed cancers owing to greater precision in tumor grade and volume determinations, which helps direct disease management. All these advantages can be achieved with fewer targeted biopsy cores per patient, potentially reducing biopsy-related morbidity (6,8,11). The purpose of this article is to focus on how multiparametric MRI results can positively impact the health of men suspected of having clinically significant prostate cancer. Who Should Undergo MRI before Biopsy? Patients chosen for MRI before biopsy include biopsynaive men with elevated serum prostate-specific antigen (PSA) levels, abnormal digital rectal examination findings, or both, and men who are deemed to have persistent elevated risk of harboring clinically significant cancers despite prior negative or nonexplanatory systematic transrectal US biopsy findings. Indications for MRI should be based on the recommendations for screening and early diagnosis of the National Comprehensive Cancer Network and the European Association of Urology (12,13). Accordingly, biopsy-naive men with lower than average risk of prostate cancer should not undergo prostate biopsy or MRI. However, limiting the options to prespecified PSA thresholds is not recommended, as there are many factors (eg, symptoms, age, race, family history, PSA kinetics, digital rectal examination findings) that in

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Section: Recommendations For Mri-directed Biopsymentioning

confidence: 99%

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

Padhani¹,

Barentsz²,

Villeirs³

et al. 2019

Radiology

176

118

View full text Add to dashboard Cite

show abstract

“…Reducing false‐negative MRI results further remains a clinical priority, calling for risk‐adapted strategies for patient biopsy selection [2,3]. Multivariable risk‐prediction tools incorporating MRI results have been developed [4], but remain unvalidated.…”

Section: Figmentioning

confidence: 99%

Risk‐adapted biopsy decision based on prostate magnetic resonance imaging and prostate‐specific antigen density for enhanced biopsy avoidance in first prostate cancer diagnostic evaluation

Schoots

Padhani

2020

BJU International

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“…Few patients underwent mpMRI before biopsy in our cohort; however, mpMRI has emerged as an important prediction tool to identify clinically significant PCa, especially before a repeated biopsy, which has been recommended by the guidelines [ 14 , 15 ]. The Rotterdam app and web-based ERSPC-RC is one of the PCa risk prediction models incorporating mpMRI (PI-RADS 1-5) [ 20 ]; nevertheless, the predictor of the PI-RADS used in the Rotterdam app was the first version, and most of our MRI images were graded according to the PI-RADS v2 guidelines. Moreover, the issues of interobserver variability and heterogeneous definitions of abnormality in mpMRI interpretation remain to be explored, and these MRI risk prediction models need to be validated further.…”

Section: Discussionmentioning

confidence: 99%

Prostate Cancer Risk Calculator Apps in a Taiwanese Population Cohort: Validation Study

Chen

Chu

Lin³

et al. 2020

J Med Internet Res

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Background Mobile health apps have emerged as useful tools for patients and clinicians alike, sharing health information or assisting in clinical decision-making. Prostate cancer (PCa) risk calculator mobile apps have been introduced to assess risks of PCa and high-grade PCa (Gleason score ≥7). The Rotterdam Prostate Cancer Risk Calculator and Coral–Prostate Cancer Nomogram Calculator apps were developed from the 2 most-studied PCa risk calculators, the European Randomized Study of Screening for Prostate Cancer (ERSPC) and the North American Prostate Cancer Prevention Trial (PCPT) risk calculators, respectively. A systematic review has indicated that the Rotterdam and Coral apps perform best during the prebiopsy stage. However, the epidemiology of PCa varies among different populations, and therefore, the applicability of these apps in a Taiwanese population needs to be evaluated. This study is the first to validate the PCa risk calculator apps with both biopsy and prostatectomy cohorts in Taiwan. Objective The study’s objective is to validate the PCa risk calculator apps using a Taiwanese cohort of patients. Additionally, we aim to utilize postprostatectomy pathology outcomes to assess the accuracy of both apps with regard to high-grade PCa. Methods All male patients who had undergone transrectal ultrasound prostate biopsies in a single Taiwanese tertiary medical center from 2012 to 2018 were identified retrospectively. The probabilities of PCa and high-grade PCa were calculated utilizing the Rotterdam and Coral apps, and compared with biopsy and prostatectomy results. Calibration was graphically evaluated with the Hosmer-Lemeshow goodness-of-fit test. Discrimination was analyzed utilizing the area under the receiver operating characteristic curve (AUC). Decision curve analysis was performed for clinical utility. Results Of 1134 patients, 246 (21.7%) were diagnosed with PCa; of these 246 patients, 155 (63%) had high-grade PCa, according to the biopsy results. After confirmation with prostatectomy pathological outcomes, 47.2% (25/53) of patients were upgraded to high-grade PCa, and 1.2% (1/84) of patients were downgraded to low-grade PCa. Only the Rotterdam app demonstrated good calibration for detecting high-grade PCa in the biopsy cohort. The discriminative ability for both PCa (AUC: 0.779 vs 0.687; DeLong’s method: P<.001) and high-grade PCa (AUC: 0.862 vs 0.758; P<.001) was significantly better for the Rotterdam app. In the prostatectomy cohort, there was no significant difference between both apps (AUC: 0.857 vs 0.777; P=.128). Conclusions The Rotterdam and Coral apps can be applied to the Taiwanese cohort with accuracy. The Rotterdam app outperformed the Coral app in the prediction of PCa and high-grade PCa. Despite the small size of the prostatectomy cohort, both apps, to some extent, demonstrated the predictive capacity for true high-grade PCa, confirmed by the whole prostate specimen. Following our external validation, the Rotterdam app might be a good alternative to help detect PCa and high-grade PCa for Taiwanese men.

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

Cited by 38 publications

References 43 publications

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

Risk‐adapted biopsy decision based on prostate magnetic resonance imaging and prostate‐specific antigen density for enhanced biopsy avoidance in first prostate cancer diagnostic evaluation

Prostate Cancer Risk Calculator Apps in a Taiwanese Population Cohort: Validation Study

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