PURPOSE: The existing literature suggests that the postoperative mortality (POM) rate in radical cystectomy (RC) patients does not exceed 3%. We sought to develop and externally validate a reference table that quantifies POM after RC. METHODS: We identified 12,274 patients treated with RC, between 1998 and 2007, within the Nationwide Inpatient Sample database. A total of 6188 (50.4%) randomly selected patients was used as the development cohort. Logistic regression analysis for prediction of POM adjusted for: age, sex, race, Charlson comorbidity index (CCI), urinary diversion type, year of surgery, annual hospital caseload, location/teaching status of hospital, region and bed size of hospital. The reference table was developed by using stepwise variable removal to identify the most accurate and parsimonious model. The model was externally validated in 6086 (49.6%) patients. RESULTS:POM occurred in 2.4% of patients. POM proportion increased with increasing age (≤59: 0.6% vs. 60-69: 1.6% vs. 70-79: 3.1% vs. ≥80: 4.6%, P < 0.001), and higher CCI (CCI 0: 1.7% vs. CCI 1: 3.0% vs. CCI 2: 4.2% vs. CCI 3: 4.3% vs. CCI ≥ 4: 12.1%, P < 0.001). In multivariable analyses, only age and CCI remained as independent predictors of POM, after stepwise variable removal. The discrimination accuracy of the reference table in predicting POM was 70%. CONCLUSIONS: Age and CCI represent the foremost determinants of POM after RC. The developed reference table is capable of predicting POM after RC, in an individualized fashion. The accuracy of the model is good (70%), and it is highly generalizable.
RCT Entities:
PURPOSE: The existing literature suggests that the postoperative mortality (POM) rate in radical cystectomy (RC) patients does not exceed 3%. We sought to develop and externally validate a reference table that quantifies POM after RC. METHODS: We identified 12,274 patients treated with RC, between 1998 and 2007, within the Nationwide Inpatient Sample database. A total of 6188 (50.4%) randomly selected patients was used as the development cohort. Logistic regression analysis for prediction of POM adjusted for: age, sex, race, Charlson comorbidity index (CCI), urinary diversion type, year of surgery, annual hospital caseload, location/teaching status of hospital, region and bed size of hospital. The reference table was developed by using stepwise variable removal to identify the most accurate and parsimonious model. The model was externally validated in 6086 (49.6%) patients. RESULTS: POM occurred in 2.4% of patients. POM proportion increased with increasing age (≤59: 0.6% vs. 60-69: 1.6% vs. 70-79: 3.1% vs. ≥80: 4.6%, P < 0.001), and higher CCI (CCI 0: 1.7% vs. CCI 1: 3.0% vs. CCI 2: 4.2% vs. CCI 3: 4.3% vs. CCI ≥ 4: 12.1%, P < 0.001). In multivariable analyses, only age and CCI remained as independent predictors of POM, after stepwise variable removal. The discrimination accuracy of the reference table in predicting POM was 70%. CONCLUSIONS: Age and CCI represent the foremost determinants of POM after RC. The developed reference table is capable of predicting POM after RC, in an individualized fashion. The accuracy of the model is good (70%), and it is highly generalizable.
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