Predictors of Outcome in Bladder Cancer

Abstract

Tumor stage and grade have largely been responsible for directing treatment algorithms in bladder cancer. However, the considerable heterogeneity of tumor biology in bladder cancer is incompletely characterized by stage and grade alone, and recent efforts to improve predictive models in bladder cancer may significantly improve accuracy and calibration. This article addresses how current nomograms and risk tables may be best used to individualize bladder cancer management.

PPM1D is Associated With Prognosis of Bladder Cancer in the Chinese Population

“…Factually, the major methods for evaluating the diagnostic and prognostic value remain to be cystoscopy and histopathological analysis in bladder cancer [17]. In clinical, pTNM stage, tumor size and histological grade were usually used to evaluate clinical outcome of bladder cancer [18]. Unfortunately, these prognosticators cannot accurately predict the clinical outcome [19,20].…”

Fibrous sheath interacting protein 1 overexpression is associated with unfavorable prognosis in bladder cancer: a potential therapeutic target

“… 1 , 2 Clinical and pathological data suggest that UCC is characterized by two distinct phenotypes with high- and low-grade differentiation. 3 , 4 Previous studies reported that UCC shows excellent prognosis with no signs of muscle invasion in ~75% of the patients (cancer in situ, T a , and T 1 ), whereas the rest of the patients present with aggressive form of UCC that invades the intrinsic muscular layers and is associated with a poor prognosis. 5 , 6 There are several known risk factors for bladder cancer, including genetics, diets, smoking, environmental and occupational exposure, gender, and so on.…”