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- Title
MR-based prognostic nomogram for prostate cancer after radical prostatectomy.
- Authors
Zhang, Yu‐Dong; Wu, Chen‐Jiang; Bao, Mei‐Ling; Li, Hai; Wang, Xiao‐Ning; Liu, Xi‐Sheng; Shi, Hai‐Bin; Zhang, Yu-Dong; Wu, Chen-Jiang; Bao, Mei-Ling; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin
- Abstract
<bold>Purpose: </bold>To assess a magnetic resonance imaging (MRI)-based nomogram in the prediction of prostate cancer (PCa) biochemical recurrence (BCR) within 3 years after prostatectomy.<bold>Materials and Methods: </bold>Between 2009 and 2013, 205 patients with biopsy-confirmed PCa had MRI before prostatectomy. BCR was defined as a PSA failure (>0.2 ng/ml) after prostatectomy. MR features (cancer location, diameter, apparent diffusion coefficients [ADCs], PI-RADS v2 score, dynamic contrast-enhanced [DCE] type, and MR T-stage) were retrospectively evaluated for predicting 3-year BCR based on partial least square regression analysis. Second, imaging features were added to a popularized D'Amico and CAPRA scheme to determine imaging contribution to published nomograms. Lastly, a multivariable Cox regression analysis was employed to determine the independent risk factors of time to BCR.<bold>Results: </bold>Three-year BCR rate (median follow-up of 44.9 mo) was 25.4% (52/205). The area under receiver operating characteristic (ROC) curve (Az) for MR nomogram (0.909, 95% confidence interval [CI]: 0.861-0.944) was higher than popularized D'Amico (0.793, 95% CI: 0.731-0.846, P = 0.001) and CAPRA (0.809, 95% CI: 0.748-0.860, P = 0.001). The performance of D'Amico (Az: 0.901, 95% CI: 0.852-0.938, P < 0.001) and CAPRA (Az: 0.894, 95% CI: 0.843-0.932, P = 0.004) was significantly improved by adding MR findings. Tumor ADCs (hazard ratio [HR] = 1.747; P = 0.011), PI-RADS score (HR = 4.123; P = 0.039), pathological Gleason score (HR = 3.701; P = 0.004), and surgical-T3b (HR = 6.341; P < 0.001) were independently associated with time to BCR.<bold>Conclusion: </bold>Multiparametric MRI, when converted into a prognostic nomogram, can predict the clinical outcome in patients with PCa after prostatectomy.<bold>Level Of Evidence: </bold>3 J. Magn. Reson. Imaging 2017;45:586-596.
- Subjects
CHINA; CANCER relapse; DIAGNOSTIC imaging; LONGITUDINAL method; MAGNETIC resonance imaging; COMPUTERS in medicine; PROGNOSIS; PROSTATE tumors; PROSTATECTOMY; RESEARCH evaluation; STATISTICS; DATA analysis; TREATMENT effectiveness; DISEASE incidence; PREVENTION
- Publication
Journal of Magnetic Resonance Imaging, 2017, Vol 45, Issue 2, p586
- ISSN
1053-1807
- Publication type
journal article
- DOI
10.1002/jmri.25441