Joao Ricardo Alves1,2, Valdair F Muglia3, Fabiano R Lucchesi4, Raisa A O G Faria4, Cinthia Alcantara-Quispe5, Vinicius L Vazquez6, Rodolfo B Reis7, Eliney F Faria5. 1. Department of Urology, Barretos Cancer Hospital, Barretos, R. Antenor Duarte Vilela, 1331, Barretos, São Paulo, 14784-400, Brazil. joaoralves@hotmail.com. 2. Department of Urology, Base Hospital of Federal District, Brasilia, Brazil. joaoralves@hotmail.com. 3. Department of Radiology, University of Sao Paulo Hospital of Medical School, Ribeirão Preto, Brazil. 4. Department of Radiology, Barretos Cancer Hospital, Barretos, Brazil. 5. Department of Urology, Barretos Cancer Hospital, Barretos, R. Antenor Duarte Vilela, 1331, Barretos, São Paulo, 14784-400, Brazil. 6. Research and Education Institute, Barretos Cancer Hospital, Barretos, Brazil. 7. Department of Urology, University of Sao Paulo Hospital of Medical School, Ribeirão Preto, Brazil.
Abstract
INTRODUCTION: The objective of this study was to perform an independent external validation of the Giganti-Coppola nomogram (GCN), which uses clinical and radiological parameters to predict prostate extracapsular extension (ECE) on the final pathology of patients undergoing radical prostatectomy (RP). MATERIAL AND METHODS: Seventy-two patients diagnosed with prostate cancer (PCa), who were RP candidates from two institutions, were prospectively included. All patients underwent preoperative multi-parametric magnetic resonance imaging (mpMRI) at 1.5 T, without the use of an endorectal coil, with multiplanar images in T1WI, T2WI, DWI, and DCE. The AUC and a calibration graph were used to validate the nomogram, using the regression coefficients of the Giganti-Coppola study. RESULTS: The original nomogram had an AUC of 0.90 (p = 0.001), with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 5.1%, 47.1%, 100%, and 48%, respectively. The calibration graph showed an overestimation of the nomogram for ECE. CONCLUSION: The GCN has an adequate ability in predicting ECE; however, in our sample, it showed limited accuracy and overestimated likelihood of ECE in the final pathology of patients with PCa submitted to RP. KEY POINTS: • Knowledge of preoperative local staging of prostate cancer is essential for surgical treatment. Extracapsular extension increases the chance of positive surgical margins. • Imaging modalities such as mpMRI alone does not have suitable accuracy in local staging. • Giganti-Coppola's nomogram achieved an adequate ability in predicting ECE.
INTRODUCTION: The objective of this study was to perform an independent external validation of the Giganti-Coppola nomogram (GCN), which uses clinical and radiological parameters to predict prostate extracapsular extension (ECE) on the final pathology of patients undergoing radical prostatectomy (RP). MATERIAL AND METHODS: Seventy-two patients diagnosed with prostate cancer (PCa), who were RP candidates from two institutions, were prospectively included. All patients underwent preoperative multi-parametric magnetic resonance imaging (mpMRI) at 1.5 T, without the use of an endorectal coil, with multiplanar images in T1WI, T2WI, DWI, and DCE. The AUC and a calibration graph were used to validate the nomogram, using the regression coefficients of the Giganti-Coppola study. RESULTS: The original nomogram had an AUC of 0.90 (p = 0.001), with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 5.1%, 47.1%, 100%, and 48%, respectively. The calibration graph showed an overestimation of the nomogram for ECE. CONCLUSION: The GCN has an adequate ability in predicting ECE; however, in our sample, it showed limited accuracy and overestimated likelihood of ECE in the final pathology of patients with PCa submitted to RP. KEY POINTS: • Knowledge of preoperative local staging of prostate cancer is essential for surgical treatment. Extracapsular extension increases the chance of positive surgical margins. • Imaging modalities such as mpMRI alone does not have suitable accuracy in local staging. • Giganti-Coppola's nomogram achieved an adequate ability in predicting ECE.
Authors: Zhaoxia Zhang; Chenghao Zhanghuang; Jinkui Wang; Tao Mi; Jiayan Liu; Xiaomao Tian; Liming Jin; Dawei He Journal: Front Public Health Date: 2022-07-12