Semi-competing risk model to predict perioperative and oncologic outcomes after radical cystectomy.

Background: To utilize a semi-competing risk model to predict perioperative and oncologic outcomes after radical cystectomy and to compare the findings with the univariate Cox regression model.

Methods: We reviewed the Institutional Review Board approved database of radical cystectomy of 316 patients who had undergone robot-assisted radical cystectomy (RARC) or open radical cystectomy between 2006 and 2016. Demographic data, perioperative outcomes, complications, metastasis, and survival were analyzed. The Bayesian variable selection method was utilized to obtain models for each hazard function in the semi-competing risks.

Results: Of 316 patients treated, 48% and 18% experienced any or major complication respectively within 30 days. Intracorporeal RARC was associated with decreased metastasis risk. Extracorporeal RARC was associated with marginally decreased risks of overall complications or major complications. Patients with advanced cancer had an increased risk of metastasis, death after metastasis and death after complication. Positive nodes were associated with an increased risk of death without overall or major complications and increased risk of death after metastasis occurs. When a serious complication was taken into account there was no significant difference in mortality, irrespective of disease stage.

Conclusions: A semi-competing risk model provides relatively more accurate information in comparison to Cox regression analysis in predicting risk factors for complications and metastasis in patients undergoing radical cystectomy.