Clinical markers of morbidity, mortality and survival in bladder cancer patients treated with radical cystectomy. A systematic review

Context: Radical cystectomy and pelvic lymph node dissection (RC and PLND) are an essential part of the treatment paradigm in high risk bladder cancer. However, these patients have high rates of morbidity and mortality related both to the treatment and to the disease.Objective: To provide overview of current literature about clinical markers that can be used to predict and improve BC-patient outcomes at the time of RC and PLND and to study if they are properly validated.Evidence acquisition: A systematic literature search was conducted according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria between January 1990 and October 2018 to identify English written original and review articles relevant to this topic. Prospective and retrospective studies were included.Evidence synthesis: There are several risk factors identified from non-randomised trials that can be improved before surgery to reduce perioperative mortality and morbidity. These include poor nutritional status, anaemia, renal function and smoking. Preoperative nomograms have also been developed to help decision-making and to inform patients about the risks of surgery. They can be used to estimate risk of postoperative mortality after RC and PLND with accuracy varying from 70 to 86%. These nomograms are largely based on retrospective data. Likewise, nomograms developed to calculate estimates about patient's overall and cancer specific survival have the same limitations.Conclusion: Clinical markers to predict morbidity, mortality and survival in patients with bladder cancer treated with RC and PLND may help to improve patient outcomes and treatment decision-making, but available data come from small retrospective trials and have not been properly validated. Prospective, multi-centre studies are needed to implement and disseminate predictive clinical markers and nomograms such that they can be utilised in treatment decision-making in daily practice.