The stanford prostate cancer calculator: Development and external validation of online nomograms incorporating PIRADS scores to predict clinically significant prostate cancer.

While multiparametric MRI (mpMRI) has high sensitivity for detection of clinically significant prostate cancer (CSC), false positives and negatives remain common. Calculators that combine mpMRI with clinical variables can improve cancer risk assessment, while providing more accurate predictions for individual patients. We sought to create and externally validate nomograms incorporating Prostate Imaging Reporting and Data System (PIRADS) scores and clinical data to predict the presence of CSC in men of all biopsy backgrounds.

Data from 2125 men undergoing mpMRI and MR fusion biopsy from 2014 to 2018 at Stanford, Yale, and UAB were prospectively collected. Clinical data included age, race, PSA, biopsy status, PIRADS scores, and prostate volume. A nomogram predicting detection of CSC on targeted or systematic biopsy was created.

Biopsy history, Prostate Specific Antigen (PSA) density, PIRADS score of 4 or 5, Caucasian race, and age were significant independent predictors. Our nomogram-the Stanford Prostate Cancer Calculator (SPCC)-combined these factors in a logistic regression to provide stronger predictive accuracy than PSA density or PIRADS alone. Validation of the SPCC using data from Yale and UAB yielded robust AUC values.

The SPCC combines pre-biopsy mpMRI with clinical data to more accurately predict the probability of CSC in men of all biopsy backgrounds. The SPCC demonstrates strong external generalizability with successful validation in two separate institutions. The calculator is available as a free web-based tool that can direct real-time clinical decision-making.

Urologic oncology. 2021 Jul 08 [Epub ahead of print]

Nancy N Wang, Steve R Zhou, Leo Chen, Robert Tibshirani, Richard E Fan, Pejman Ghanouni, Alan E Thong, Katherine J To'o, Kamyar Amirkhiz, Jeffrey W Nix, Jennifer B Gordetsky, Preston Sprenkle, Soroush Rais-Bahrami, Geoffrey A Sonn

Department of Urology, Stanford University School of Medicine, Stanford, CA., Department of Urology, Stanford University School of Medicine, Stanford, CA. Electronic address: ., Departments of Biomedical Data Science and Statistics, Stanford University, Stanford, CA., Department of Radiology, Stanford University School of Medicine, Stanford, CA., Department of Urology, Yale School of Medicine, New Haven, CT., Department of Urology, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center at UAB, University of Alabama at Birmingham, Birmingham, AL., Department of Urology, University of Alabama at Birmingham, Birmingham, AL; Department of Pathology, University of Alabama at Birmingham, Birmingham, AL., Department of Urology, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center at UAB, University of Alabama at Birmingham, Birmingham, AL; Department of Radiology, University of Alabama at Birmingham, Birmingham, AL., Department of Urology, Stanford University School of Medicine, Stanford, CA; Department of Radiology, Stanford University School of Medicine, Stanford, CA.

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