The Value of PSA Density in Combination with PI-RADS™ for the Accuracy of Prostate Cancer Prediction

Distler, Florian; Radtke, Jan Philipp; Bonekamp, David; Kesch, Claudia; Schlemmer, Heinz Peter; Wieczorek, Kathrin; Kirchner, Marietta; Pahernik, Sascha; Hohenfellner, Markus; Hadaschik, Boris

doi:10.1016/j.juro.2017.03.130

Cited by 206 publications

(214 citation statements)

References 28 publications

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“…All the novel nomograms had high AUCs: ModDis (0.83; 95% CI 0.78–0.87), MRI‐ERSPC‐RC3/4 (0.82; 95% CI 0.78–0.87) and ModRad (0.85; 95% CI 0.81–0.89). Comparing the AUCs of our cohort with the published cohorts of the novel models, we found nearly identical AUCs for MRI‐ERSPC‐RC3/4 (0.82 vs 0.84–0.85), ModDis (0.83 vs 0.79) and ModRad (0.85 vs 0.81–0.83) .…”

Section: Discussionsupporting

confidence: 53%

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: Discussionsupporting

confidence: 53%

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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“…19 In agreement with these results, we found that PSAD was a significant predictor of benign pathology. Among patients with a prior negative biopsy who then underwent FB for abnormal mpMRI findings, we found that 132 of 285 patients (46.3%) had benign pathology.…”

Section: Discussionsupporting

confidence: 88%

“…Previously, some authors have suggested using the MRI-calculated PSAD in combination with the PI-RADS score for selecting patients for biopsy. 19 In agreement with these results, we found that PSAD was a significant predictor of benign pathology. During model development, PSAD (as either a continuous or categorical variable) was always removed from multivariate models in which PSA and prostate volume were included.…”

Section: Discussionsupporting

confidence: 88%

Multi‐institutional nomogram predicting benign prostate pathology on magnetic resonance/ultrasound fusion biopsy in men with a prior negative 12‐core systematic biopsy

Truong

Wang

Gordetsky

et al. 2017

Cancer

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False-positive mpMRI examinations may occur in up to 46.3% of patients with a prior negative biopsy. Thus, a multi-institutional nomogram has been developed and validated for predicting benign pathology after FB in patients with a prior negative biopsy, and this may help to reduce the number of unnecessary biopsies in the setting of abnormal mpMRI findings. Cancer 2018;124:278-85. © 2017 American Cancer Society.

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“…repeat biopsy setting, the negative predictive value of significant PC increased from 83 to 93%. By increasing the probability of ruling out CSPC, approximately 20% of unnecessary biopsies could have safely been avoided [13]. This is similar to our finding that 21% of biopsies could have been avoided using PIRADS < 3 and PSAD < 0.2 as the criteria for deciding not to perform a biopsy.…”

Section: Discussionsupporting

confidence: 86%

“…A study of 1040 subjects by Distler et al [13] showed that the negative predictive value of unsuspicious MRI for the presence of CSPC (PIRADS < 3) increased from 79 to 89% when PSAD was 0.15 ng/mL/mL or less. In a Lesions with a PIRADS score of 3 in the repeat biopsy group.…”

Section: Discussionmentioning

confidence: 99%

Use of Prostate Specific Antigen Density Combined with Multiparametric Magnetic Resonance Imaging Improves Triage for Prostate Biopsy

et al. 2019

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Background: Multi-parametric magnetic resonance imaging (mpMRI)-directed biopsy for prostate cancer (PC) diagnosis improves the detection of clinically significant prostate cancer (CSPC) and decreases the rate of over-diagnosis of insignificant disease. The aim of this study was to investigate the value of mpMRI combined with prostate specific antigen density (PSAD) in the decision making related to the biopsy. Methods: mpMRI and mpMRI/transrectal ultrasound fusion targeted biopsies with subsequent systematic biopsies were performed in 397 patients (223 biopsy-naïve and 174 with a previous biopsy). Detection rates of (CSPC) and insignificant PC were stratified using the PIRADS score, and the number of avoidable biopsies and missed (CSPC) were plotted against PSAD values of 0.1–0.5 ng/mL². Results: PIRADS <3 and PSAD <0.2 ng/mL² were the safest criteria for not performing a biopsy. When applied to the biopsy-naïve group, 21.5% (48/223) of the biopsies could have been avoided and 3.7% (3/82) of CSPC would have been missed. In the repeat biopsy group, 12.6% (22/174) of biopsies could have been avoided and 6.9% (4/58) of (CSPC) would have been missed. Conclusions: A combination of mpMRI and PSAD might reduce the number of biopsies performed with the cost of missing <4% of CSPC.

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The Value of PSA Density in Combination with PI-RADS™ for the Accuracy of Prostate Cancer Prediction

Cited by 206 publications

References 28 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

Multi‐institutional nomogram predicting benign prostate pathology on magnetic resonance/ultrasound fusion biopsy in men with a prior negative 12‐core systematic biopsy

Use of Prostate Specific Antigen Density Combined with Multiparametric Magnetic Resonance Imaging Improves Triage for Prostate Biopsy

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