Optimizing detection of clinically significant prostate cancer through nomograms incorporating mri, clinical features, and advanced serum biomarkers in biopsy naïve men

Mohammad R. Siddiqui*, Eric V. Li, Sai K.S.R. Kumar, Anna Busza, Jasmine S. Lin, Ashorne K. Mahenthiran, Jonathan A. Aguiar, Parth V. Shah, Brandon Ansbro, Jordan M. Rich, Soliman A.S. Moataz, Mary Kate Keeter, Quan Mai, Xinlei Mi, Jeffrey J. Tosoian, Edward M. Schaeffer, Hiten D. Patel, Ashley E. Ross

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Purpose: To develop nomograms that predict the detection of clinically significant prostate cancer (csPCa, defined as ≥GG2 [Grade Group 2]) at diagnostic biopsy based on multiparametric prostate MRI (mpMRI), serum biomarkers, and patient clinicodemographic features. Materials and methods: Nomograms were developed from a cohort of biopsy-naïve men presenting to our 11-hospital system with prostate specific antigen (PSA) of 2–20 ng/mL who underwent pre-biopsy mpMRI from March 2018-June 2021 (n = 1494). The outcomes were the presence of csPCa and high-grade prostate cancer (defined as ≥GG3 prostate cancer). Using significant variables on multivariable logistic regression, individual nomograms were developed for men with total PSA, % free PSA, or prostate health index (PHI) when available. The nomograms were both internally validated and evaluated in an independent cohort of 366 men presenting to our hospital system from July 2021-February 2022. Results: 1031 of 1494 men (69%) underwent biopsy after initial evaluation with mpMRI, 493 (47.8%) of whom were found to have ≥GG2 PCa, and 271 (26.3%) were found to have ≥GG3 PCa. Age, race, highest PIRADS score, prostate health index when available, % free PSA when available, and PSA density were significant predictors of ≥GG2 and ≥GG3 PCa on multivariable analysis and were used for nomogram generation. Accuracy of nomograms in both the training cohort and independent cohort were high, with areas under the curves (AUC) of ≥0.885 in the training cohort and ≥0.896 in the independent validation cohort. In our independent validation cohort, our model for ≥GG2 prostate cancer with PHI saved 39.1% of biopsies (143/366) while only missing 0.8% of csPCa (1/124) with a biopsy threshold of 20% probability of csPCa. Conclusions: Here we developed nomograms combining serum testing and mpMRI to help clinicians risk stratify patients with elevated PSA of 2–20 ng/mL who are being considered for biopsy. Our nomograms are available at https://rossnm1.shinyapps.io/MynMRIskCalculator/ to aid with biopsy decisions.

Original languageEnglish (US)
Pages (from-to)588-595
Number of pages8
JournalProstate Cancer and Prostatic Diseases
Volume26
Issue number3
DOIs
StatePublished - Sep 2023

ASJC Scopus subject areas

  • Urology
  • Oncology
  • Cancer Research

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