Quantitative risk stratification and individual comprehensive therapy for invasive bladder cancers in China |
| |
Authors: | Hai Tao Niu Shi Xiu Shao Zong Liang Zhang Shuai Wu Bo Cheng De Quan Pang Ya Jun E Sheng Guo Dong Guang Sun Ji Wu Chang |
| |
Affiliation: | (1) Department of Urology, The Affiliated Hospital of Medical College Qingdao University, 16 Jiangsu Road, Qingdao, 266003, China;(2) Department of Urology, The Affiliated Municipal Hospital of Medical College Qingdao University, Qingdao, 266003, China;(3) Department of Urology, The Central Hospital of Shengli Oil Field, Dondying, 257000, China;(4) Department of Oncology, North China Coal Medical College, Tangshan, 063000, China;(5) Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China |
| |
Abstract: | Background To evaluate the risk factors for invasive bladder cancer and to develop a predictive model for the improvement of individual comprehensive therapy for invasive bladder cancers. Materials and methods The records of 356 patients with invasive bladder cancer, operated on at three Chinese medical institutes, were reviewed. The Cox proportional hazards regression model was used to assess the clinical and pathological variables affecting disease-free survival (DFS). The regression coefficients determined by Cox regression analysis were used to construct a predictive index (PI). PI was used to categorize the patients into different risk groups. Kaplan–Meier survival curves followed with log-rank test were plotted to compare the difference. Results Tumor configuration (RR = 1.60, P = 0.01), multiplicity (RR = 1.41, P = 0.04), histological subtype (RR = 2.13, P < 0.01), tumor stage (RR = 2.50, P < 0.01), tumor grade (RR = 2.35, P < 0.01), node status (RR = 2.48, P < 0.01), and neoadjuvant chemotherapy (RR = 0.46, P = 0.02), had independent prognostic significance for DFS. PI = 0.47 × (configuration) + 0.34 × (multiplicity) + 0.76 × (tumor histological subtype) + 0.92 × (stage) + 0.86 × (grade) + 0.91 × (node status) − 0.79 × (neoadjuvant chemotherapy). The range of PI was −0.32 to 6.52, which was equally divided into three risk groups with significant differences on Kaplan–Meier curves and a log-rank test (P < 0.01). Meanwhile, the patient’s probability of survival could be calculated by PI. Conclusions Seven factors (tumor configuration, multiplicity, histological subtype, tumor stage, tumor grade, node status, neoadjuvant chemotherapy) affect the prognosis after radical cystectomy (RC) for invasive bladder cancer. PI can be used to optimize the individual comprehensive therapy. Given fewer perioperative complications, fast recovery from surgery and relatively satisfactory quality of life, ureterocutaneostomy, and ileal conduit are suitable for the patients with short expected life spans. An erratum to this article can be found at |
| |
Keywords: | Bladder cancer Multivariate analysis Predictive index Individual comprehensive therapy |
本文献已被 PubMed SpringerLink 等数据库收录! |
|