Rotterdam mobile phone app including MRI data for the prediction of prostate cancer: A multicenter external validation. Issue 10 (October 2021)

• Record Type: Journal Article
• Authors: De Nunzio, Cosimo; Lombardo, Riccardo; Baldassarri, Valeria; Cindolo, Luca; Bertolo, Riccardo; Minervini, Andrea; Sessa, Francesco; Muto, Gianluca; Bove, Pierluigi; Vittori, Matteo; Bozzini, Giorgio; Castellan, Pietro; Mugavero, Filippo; Falsaperla, Mario; Schips, Luigi; Celia, Antonio; Bada, Maida; Porreca, Angelo; Pastore, Antonio; Al Salhi, Yazan; Giampaoli, Marco; Novella, Giovanni; Rizzetto, Riccardo; Trabacchin, Nicolo; Mantica, Guglielmo; Pini, Giovannalberto; Remmers, Sebastiaan; Antonelli, Alessandro; Tubaro, Andrea
• Is Part Of: European journal of surgical oncology. Volume 47:Issue 10(2021)
• Page Start: 2640
• Page End: 2645
• Publication Date: 2021-10
• Subjects: Prostate cancer -- Medical app -- Magnetic resonance -- Nomogram; Oncology -- Periodicals; Cancer -- Surgery -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- surgery -- Periodicals; Cancer -- Chirurgie -- Périodiques; Cancérologie -- Périodiques; Oncologie; Chirurgie (geneeskunde); Electronic journals; Electronic journals -- Sciences; Electronic journals -- Medicine; Electronic journals; 616.994059005
• DOI: 10.1016/j.ejso.2021.04.033
• Languages: English
• ISSNs: 0748-7983

Abstract

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.