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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Multiparametric MRI-based 5-year Risk Prediction Model for Biochemical Recurrence of Prostate Cancer after Radical
Stefano Luzzago1, Alberto Colombo1, Francesco A Mistretta1
1From the Department of Urology (S.L., F.A.M., E.D.T., M.L.P., M.F., O.D.C., G.M.), Division of Radiology (A.C., S.A., P.E.S., F.Z., M.B.), Department of Experimental Oncology (S.R., S.V.), Division of Pathology (N.F.), and Precision Imaging and Research Unit, Department of Medical Imaging and Radiation Sciences (G.P.), European Institute of Oncology (IEO), IRCCS, Via Giuseppe Ripamonti 435, 20141 Milan, Italy; Department of Oncology and Hematology-Oncology (S.L., F.A.M., N.F., O.D.C., G.M., G.P.) and Postgraduate School in Radiodiagnostics (E.R., L.D.M., E.D., A.S., R.M.), University of Milan, Milan, Italy; and Radiology and Radiotherapy Unit, Department of Precision Medicine, University of Campania L. Vanvitelli, Naples, Italy (A.C.).
Abstract:
Background Current predictive tools to estimate the risk of biochemical recurrence (BCR) after treatment of prostate cancer do not consider multiparametric MRI (mpMRI) information. Purpose To develop a risk prediction tool that considers mpMRI findings to assess the risk of 5-year BCR after radical prostatectomy. Materials and Methods In this retrospective single-center analysis in 1459 patients with prostate cancer who underwent mpMRI before radical prostatectomy (in 2012-2015), the outcome of interest was 5-year BCR (two consecutive prostate-specific antigen [PSA] levels > 0.2 ng/mL [0.2 µg/L]). Patients were randomly divided into training (70%) and test (30%) sets. Kaplan-Meier plots were applied to the training set to estimate survival probabilities. Multivariable Cox regression models were used to test the relationship between BCR and different sets of exploratory variables. The C-index of the final model was calculated for the training and test sets and was compared with European Association of Urology, University of California San Francisco Cancer of the Prostate Risk Assessment, Memorial Sloan-Kettering Cancer Center, and Partin risk tools using the partial likelihood ratio test. Five risk categories were created. Results The median duration of follow-up in the whole cohort was 59 months (IQR, 32-81 months); 376 of 1459 (25.8%) patients had BCR. A multivariable Cox regression model (referred to as PIPEN, and composed of PSA density, International Society of Urological Pathology grade group, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extraprostatic extension score, nodes) fitted to the training data yielded a C-index of 0.74, superior to that of other predictive tools (C-index 0.70 for all models; P ≤ .01) and a median higher C-index on 500 test set replications (C-index, 0.73). Five PIPEN risk categories were identified with 5-year BCR-free survival rates of 92%, 84%, 71%, 56%, and 26% in very low-, low-, intermediate-, high-, and very high-risk patients, respectively (all P < .001). Conclusion A five-item model for predicting the risk of 5-year BCR after radical prostatectomy for prostate cancer was developed and internally verified, and five risk categories were identified. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Aguirre and Ortegón in this issue.
