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

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. A series of men undergoi...

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Veröffentlicht in:European journal of surgical oncology 2021-10, Vol.47 (10), p.2640-2645
Hauptverfasser: 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
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Sprache:eng
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Zusammenfassung: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. 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. 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). 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.
ISSN:0748-7983
1532-2157
DOI:10.1016/j.ejso.2021.04.033