Hao Zi1, Lei Gao1,2, Zhaohua Yu1,2, Chaoyang Wang1,3, Xuequn Ren1,3, Jun Lyu4, Xiaodong Li5,6. 1. Institute of Evidence-Based Medicine and Knowledge Translation, Henan University, Kaifeng, Henan, China. 2. Department of Urology, Huaihe Hospital of Henan University, Kaifeng, Henan, China. 3. Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, Henan, China. 4. Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China. 5. Institute of Evidence-Based Medicine and Knowledge Translation, Henan University, Kaifeng, Henan, China. hndxhhyylxd@126.com. 6. Department of Urology, Huaihe Hospital of Henan University, Kaifeng, Henan, China. hndxhhyylxd@126.com.
Abstract
BACKGROUND: Our aim was to identify the independent prognostic factors in patients with primary urethral carcinoma (PUC) and to predict their overall survival (OS) and cancer-specific survival (CSS) at 3, 5, and 8 years. METHODS: Patients with PUC identified in the Surveillance, Epidemiology, and End Results (SEER) database were divided into training and validation cohorts. Nomograms were constructed based on the results of Cox regression analysis. The predictive performance of each nomogram was evaluated using the consistency index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration plots. Decision-curve analysis (DCA) was used to test the clinical value of the predictive models. RESULTS: Our study screened 822 patients with PUC. Multivariate analysis showed that the age at diagnosis, race, histology, American Joint Committee on Cancer (AJCC) stage, and surgery status were independent prognostic factors for CSS and age at diagnosis, race, histology, AJCC stage, surgery status, and chemotherapy for OS (all P < 0.05). We used these prognostic factors to construct nomograms. The C-indexes for OS and CSS were 0.713 and 0.741 in training cohorts and 0.714 and 0.738 in validation cohorts, respectively. The AUC and calibration plots demonstrated the good performance of both nomograms. The DCA indicated the presence of clinical net benefits in both the training and validation cohorts. CONCLUSION: We developed and validated nomograms for predicting OS and CSS in patients with PUC, which can help clinicians make treatment decisions.
BACKGROUND: Our aim was to identify the independent prognostic factors in patients with primary urethral carcinoma (PUC) and to predict their overall survival (OS) and cancer-specific survival (CSS) at 3, 5, and 8 years. METHODS:Patients with PUC identified in the Surveillance, Epidemiology, and End Results (SEER) database were divided into training and validation cohorts. Nomograms were constructed based on the results of Cox regression analysis. The predictive performance of each nomogram was evaluated using the consistency index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration plots. Decision-curve analysis (DCA) was used to test the clinical value of the predictive models. RESULTS: Our study screened 822 patients with PUC. Multivariate analysis showed that the age at diagnosis, race, histology, American Joint Committee on Cancer (AJCC) stage, and surgery status were independent prognostic factors for CSS and age at diagnosis, race, histology, AJCC stage, surgery status, and chemotherapy for OS (all P < 0.05). We used these prognostic factors to construct nomograms. The C-indexes for OS and CSS were 0.713 and 0.741 in training cohorts and 0.714 and 0.738 in validation cohorts, respectively. The AUC and calibration plots demonstrated the good performance of both nomograms. The DCA indicated the presence of clinical net benefits in both the training and validation cohorts. CONCLUSION: We developed and validated nomograms for predicting OS and CSS in patients with PUC, which can help clinicians make treatment decisions.
Authors: Omar Hyder; Hugo Marques; Carlo Pulitano; J Wallis Marsh; Sorin Alexandrescu; Todd W Bauer; T Clark Gamblin; Georgios C Sotiropoulos; Andreas Paul; Eduardo Barroso; Bryan M Clary; Luca Aldrighetti; Cristina R Ferrone; Andrew X Zhu; Irinel Popescu; Jean-Francois Gigot; Gilles Mentha; Shen Feng; Timothy M Pawlik Journal: JAMA Surg Date: 2014-05 Impact factor: 14.766
Authors: Giuseppe Lucarelli; Marco Spilotros; Antonio Vavallo; Silvano Palazzo; Carlos Miacola; Saverio Forte; Matteo Matera; Marcello Campagna; Ottavio Colamonico; Francesco Schiralli; Francesco Sebastiani; Federica Di Cosmo; Carlo Bettocchi; Giuseppe Di Lorenzo; Carlo Buonerba; Leonardo Vincenti; Giuseppe Ludovico; Pasquale Ditonno; Michele Battaglia Journal: Medicine (Baltimore) Date: 2016-05 Impact factor: 1.889