A population based assessment of perioperative mortality after cystectomy for bladder cancer

Abstract

Purpose: Large variability exists in the rates of perioperative mortality after cystectomy. Contemporary estimates range from 0.7% to 5.6%. We tested several predictors of perioperative mortality and devised a model for individual perioperative mortality prediction.

Materials and methods: We relied on life tables to quantify 30, 60 and 90-day mortality rates according to age, gender, stage (localized vs regional), grade, type of surgery (partial vs radical cystectomy), year of cystectomy and histological bladder cancer subtype. We fitted univariable and multivariable logistic regression models using 5,510 patients diagnosed with bladder cancer and treated with partial or radical cystectomy within 4 SEER (Surveillance, Epidemiology, and End Results) registries between 1984 and 2004. We then externally validated the model on 5,471 similar patients from 5 other SEER registries.

Results: At 30, 60 and 90 days the perioperative mortality rates were 1.1%, 2.4% and 3.9%, respectively. Age, stage and histological subtype represented statistically significant and independent predictors of 90-day mortality. The combined use of these 3 variables and of tumor grade resulted in the most accurate model (70.1%) for prediction of individual probability of 90-day mortality after cystectomy.

Conclusions: The accuracy of our model could potentially be improved with the consideration of additional parameters such as surgical and hospital volume or comorbidity. While better models are being developed and tested we suggest the use of the current model in individual decision making and in informed consent considerations because it provides accurate predictions in 7 of 10 patients.