PURPOSE: We investigated the incremental value of magnetic resonance imaging in addition to clinical variables for predicting pathological outcomes and disease recurrence in patients with clinically high risk prostate cancer. MATERIALS AND METHODS: A total of 922 consecutive patients with clinically high risk prostate cancer underwent magnetic resonance imaging before radical prostatectomy. We created multivariate logistic regression and Cox proportional hazards models with clinical variables only or combined with magnetic resonance imaging data to predict pathological outcomes and biochemical recurrence. The models were compared using ROC curves and the Harrell concordance index. RESULTS: The proportion of patients with pathological extracapsular extension, seminal vesicle invasion and lymph node metastasis was 57.5%, 12.7% and 6.3%, respectively. The sensitivity and specificity of extracapsular extension, seminal vesicle invasion and lymph node metastasis detection were 43% and 84.2%, 34.9% and 93.8%, and 14.0% and 96.9%, respectively. The area under the ROC curve of the model with clinical variable and magnetic resonance imaging data was greater than that of the model with clinical variables alone to predict extracapsular extension and seminal vesicle invasion (0.734 vs 0.697, p=0.001 and 0.750 vs 0.698, p<0.001, respectively). The 5-year biochemical recurrence-free survival rate was 56.1%. To predict biochemical recurrence the concordance index of the multivariate model with clinical variables only and with clinical variables plus magnetic resonance imaging data was 0.563 and 0.599, respectively (p=0.003). CONCLUSIONS: Magnetic resonance imaging findings have incremental value in addition to clinical variables for predicting pathological outcomes and disease recurrence.
PURPOSE: We investigated the incremental value of magnetic resonance imaging in addition to clinical variables for predicting pathological outcomes and disease recurrence in patients with clinically high risk prostate cancer. MATERIALS AND METHODS: A total of 922 consecutive patients with clinically high risk prostate cancer underwent magnetic resonance imaging before radical prostatectomy. We created multivariate logistic regression and Cox proportional hazards models with clinical variables only or combined with magnetic resonance imaging data to predict pathological outcomes and biochemical recurrence. The models were compared using ROC curves and the Harrell concordance index. RESULTS: The proportion of patients with pathological extracapsular extension, seminal vesicle invasion and lymph node metastasis was 57.5%, 12.7% and 6.3%, respectively. The sensitivity and specificity of extracapsular extension, seminal vesicle invasion and lymph node metastasis detection were 43% and 84.2%, 34.9% and 93.8%, and 14.0% and 96.9%, respectively. The area under the ROC curve of the model with clinical variable and magnetic resonance imaging data was greater than that of the model with clinical variables alone to predict extracapsular extension and seminal vesicle invasion (0.734 vs 0.697, p=0.001 and 0.750 vs 0.698, p<0.001, respectively). The 5-year biochemical recurrence-free survival rate was 56.1%. To predict biochemical recurrence the concordance index of the multivariate model with clinical variables only and with clinical variables plus magnetic resonance imaging data was 0.563 and 0.599, respectively (p=0.003). CONCLUSIONS: Magnetic resonance imaging findings have incremental value in addition to clinical variables for predicting pathological outcomes and disease recurrence.
Authors: Jennifer Salerno; Antonio Finelli; Chris Morash; Scott C Morgan; Nicholas Power; Nichola Schieda; Masoom A Haider Journal: Can Urol Assoc J Date: 2016-10-13 Impact factor: 1.862
Authors: Dima Raskolnikov; Arvin K George; Soroush Rais-Bahrami; Baris Turkbey; Nabeel A Shakir; Chinonyerem Okoro; Jason T Rothwax; Annerleim Walton-Diaz; M Minhaj Siddiqui; Daniel Su; Lambros Stamatakis; Maria J Merino; Bradford J Wood; Peter L Choyke; Peter A Pinto Journal: J Endourol Date: 2014-10-14 Impact factor: 2.942
Authors: Benedict J Kang; Minhong Jeun; Gun Hyuk Jang; Sang Hoon Song; In Gab Jeong; Choung-Soo Kim; Peter C Searson; Kwan Hyi Lee Journal: Int J Nanomedicine Date: 2015-10-19