Quantitative risk stratification and individual comprehensive therapy for invasive bladder cancers in China

Abstract

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. 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. 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 x (configuration) + 0.34 x (multiplicity) + 0.76 x (tumor histological subtype) + 0.92 x (stage) + 0.86 x (grade) + 0.91 x (node status) - 0.79 x (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. 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.