Rotterdam mobile phone app including MRI data for the prediction of prostate cancer: A multicenter external validation

Abstract

Objectives: The Rotterdam Prostate Cancer Risk calculator (RPCRC) has been validated in the past years. Recently a new version including multiparametric magnetic resonance imaging (mpMRI) data has been released. The aim of our study was to analyze the performance of the mpMRI RPCRC app.

Methods: A series of men undergoing prostate biopsies were enrolled in eleven Italian centers. Indications for prostate biopsy included: abnormal Prostate specific antigen levels (PSA>4 ng/ml), abnormal DRE and abnormal mpMRI. Patients' characteristics were recorded. Prostate cancer (PCa) risk and high-grade PCa risk were assessed using the RPCRC app. The performance of the mpMRI RPCRC in the prediction of cancer and high-grade PCa was evaluated using receiver operator characteristics, calibration plots and decision curve analysis.

Results: Overall, 580 patients were enrolled: 404/580 (70%) presented PCa and out of them 224/404 (55%) presented high-grade PCa. In the prediction of cancer, the RC presented good discrimination (AUC = 0.74), poor calibration (p = 0.01) and a clinical net benefit in the range of probabilities between 50 and 90% for the prediction of PCa (Fig. 1). In the prediction of high-grade PCa, the RC presented good discrimination (AUC = 0.79), good calibration (p = 0.48) and a clinical net benefit in the range of probabilities between 20 and 80% (Fig. 1).

Conclusions: The Rotterdam prostate cancer risk App accurately predicts the risk of PCa and particularly high-grade cancer. The clinical net benefit is wide for high-grade cancer and therefore its implementation in clinical practice should be encouraged. Further studies should assess its definitive role in clinical practice.

Keywords: Magnetic resonance; Medical app; Nomogram; Prostate cancer.