A multiparametric magnetic resonance imaging‐based risk model to determine the risk of significant prostate cancer prior to biopsy

Leeuwen, Pim J. van; Hayen, Andrew; Thompson, James; Moses, Daniel; Shnier, Ron; Böhm, Maret; Abuodha, Magdaline; Haynes, Anne‐Maree; Ting, Francis; Barentsz, Jelle O.; Roobol, Monique J.; Vass, Justin; Rasiah, K.; Delprado, Warick; Stricker, Phillip D.

doi:10.1111/bju.13814

Cited by 118 publications

(151 citation statements)

References 30 publications

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“…Mehralivand et al used an TRUS/MRI fusion‐guided biopsy and a 12‐core systematic biopsy as reference test. An ISUP Gleason grade group ≥2 was classified as clinically significant PCa.…”

Section: Discussionmentioning

confidence: 99%

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Püllen¹,

Radtke

Wiesenfarth

et al. 2019

BJU International

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Objectives To validate, in an external cohort, three novel risk models, including the recently updated European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator, that combine multiparametric magnetic resonance imaging (mpMRI) and clinical variables to predict clinically significant prostate cancer (PCa). Patients and Methods We retrospectively analysed 307 men who underwent mpMRI prior to transperineal ultrasound fusion biopsy between October 2015 and July 2018 at two German centres. mpMRI was rated by Prostate Imaging Reporting and Data System (PI‐RADS) v2.0 and clinically significant PCa was defined as International Society of Urological Pathology Gleason grade group ≥2. The prediction performance of the three models (MRI‐ERSPC‐3/4, and two risk models published by Radtke et al. and Distler et al., ModRad and ModDis) were compared using receiver‐operating characteristic (ROC) curve analyses, with area under the ROC curve (AUC), calibration curve analyses and decision curves used to assess net benefit. Results The AUCs of the three novel models (MRI‐ERSPC‐3/4, ModRad and ModDis) were 0.82, 0.85 and 0.83, respectively. Calibration curve analyses showed the best intercept for MRI‐ERSPC‐3 and ‐4 of 0.35 and 0.76. Net benefit analyses indicated clear benefit of the MRI‐ERSPC‐3/4 risk models compared with the other two validated models. The MRI‐ERSPC‐3/4 risk models demonstrated a discrimination benefit for a risk threshold of up to 15% for clinically significant PCa as compared to the other risk models. Conclusion In our external validation of three novel prostate cancer risk models, which incorporate mpMRI findings, a head‐to‐head comparison indicated that the MRI‐ERSPC‐3/4 risk model in particular could help to reduce unnecessary biopsies.

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Section: Discussionmentioning

confidence: 99%

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Püllen¹,

Radtke

Wiesenfarth

et al. 2019

BJU International

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“…However, increasing evidence shows that lesions with PI‐RADS category 3 should be monitored without immediate biopsy to avoid unnecessary biopsy . In combination with additional clinical parameters, such as previous biopsy history, PV and PI‐RADS score, nomograms have yielded higher CSPC detection rates …”

Section: Introductionmentioning

confidence: 99%

Detection rate of clinically significant prostate cancer in magnetic resonance imaging and ultrasonography‐fusion transperineal targeted biopsy for lesions with a prostate imaging reporting and data system version 2 score of 3–5

et al. 2018

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Objectives To evaluate the detection rates of clinically significant prostate cancer classified according to the prostate imaging reporting and data system scoring system using magnetic resonance imaging/ultrasound rigid fusion targeted biopsy. Methods A total of 339 patients underwent transperineal magnetic resonance imaging/ultrasound rigid fusion targeted biopsy in our institution between January 2015 and July 2017. Patients with prostate imaging reporting and data system category 1 or 2 and those with a pre‐biopsy prostate‐specific antigen value of >30 ng/mL were excluded from this study. Finally, 310 patients were recruited. Results The detection rates of clinically significant prostate cancer with prostate imaging reporting and data system category 3, 4, and 5 were 1.0% (1/98), 35.1% (47/134) and 73.1% (57/78), respectively. The factors affecting the detection of clinically significant prostate cancer with prostate imaging reporting and data system categories 4 and 5 were: (i) prostate imaging reporting and data system category 5; (ii) prostate volume <40 cc; (iii) no previous biopsy; (iv) lesion located in the peripheral zone; and (v) prostate‐specific antigen density >0.35 ng/mL/mL. Conclusions The detection rate of clinically significant prostate cancer on magnetic resonance imaging/ultrasound rigid fusion targeted biopsy is very low in patients with prostate imaging reporting and data system category 3; therefore, patients with this classification should not undergo targeted biopsy. Prostate‐specific antigen density, prostate volume, locations of suspected cancer and history of biopsy should be considered to predict the detection rate of clinically significant prostate cancer with prostate imaging reporting and data system categories 4 and 5.

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“…In this regard, a model combining mpMRI and age, PSA, DRE findings, prostate volume, previous biopsy, and Prostate Imaging – Reporting and Data System score as predictors for significant PCa was associated with an AUC of 0.88 and would eliminate 28% of biopsies while missing only 2.6% of significant PCa [68▪▪]. …”

Section: Determining the Need For Prostate Biopsymentioning

confidence: 99%

A multiparametric approach to improve upon existing prostate cancer screening and biopsy recommendations

Helfand

Conran

et al. 2017

Current Opinion in Urology

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Purpose of review To provide an overview of how genetic, serum, and urine biomarkers can help identify men at high risk for prostate cancer (PCa) and aggressive disease and men who would benefit from prostate biopsy. Recent findings Screening for PCa is controversial because of concerns about overdiagnosis and overtreatment of nonlife-threatening tumors. Therefore, an approach to screening that includes a detailed family history with genetic testing of risk single nucleotide polymorphisms and high-penetrance genetic variants should be considered. After an elevated serum prostate-specific antigen (PSA) level has been confirmed, obtaining additional information (family history, biomarkers, and imaging) should be considered before recommending a prostate biopsy. Summary There are now genetic tests that can help identify men who would benefit from PSA testing. Additional biomarker and imaging tests should be offered to those men who are confirmed to have elevated PSA values. These new biomarkers and imaging tests can improve the specificity of PSA testing while missing a small percentage of high-grade tumors. The path forward involves a multiparametric risk assessment based on clinical data and these new tests.

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A multiparametric magnetic resonance imaging‐based risk model to determine the risk of significant prostate cancer prior to biopsy

Cited by 118 publications

References 30 publications

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Detection rate of clinically significant prostate cancer in magnetic resonance imaging and ultrasonography‐fusion transperineal targeted biopsy for lesions with a prostate imaging reporting and data system version 2 score of 3–5

A multiparametric approach to improve upon existing prostate cancer screening and biopsy recommendations

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