Discriminative Ability of Commonly Used Indexes to Predict Adverse Outcomes After Radical Cystectomy: Comparison of Demographic Data, American Society of Anesthesiologists, Modified Charlson Comorbidity Index, and Modified Frailty Index

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Abstract

Micro-Abstract

Given the high rate of adverse events after radical cystectomy, we evaluated the discriminative ability of commonly used comorbidity indexes and demographic factors for perioperative complications in patients undergoing radical cystectomy. We found the predictive ability of these factors to be universally poor, highlighting the need for newer models built to identify patients with a greater risk of adverse events after radical cystectomy.

Background:

The American Society of Anesthesiologists physical status classification system, modified Charlson Comorbidity Index (mCCI), and modified Frailty Index have been associated with complications after urologic surgery. No study has compared the predictive performance of these indexes for postoperative complications after radical cystectomy (RC) for bladder cancer.

Materials and Methods:

Data from 1516 patients undergoing elective RC for bladder cancer were extracted from the 2005 to 2011 American College of Surgeons National Surgical Quality Improvement Program for a retrospective review. The perioperative outcome variables assessed were occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, discharge to a higher level of care, and mortality. Patient comorbidity indexes and demographic data were assessed for their discriminative ability in predicting perioperative adverse outcomes using an area under the curve (AUC) analysis from the receiver operating characteristic curves.

Results:

The most predictive comorbidity index for any adverse event was the mCCI (AUC, 0.511). The demographic factors were the body mass index (BMI; AUC, 0.519) and sex (AUC, 0.519). However, the overall performance for all predictive indexes was poor for any adverse event (AUC < 0.52). Combining the most predictive demographic factor (BMI) and comorbidity index (mCCI) resulted in incremental improvements in discriminative ability compared with that for the individual outcome variables.

Conclusion:

For RC, easily obtained patient mCCI, BMI, and sex have overall similar discriminative abilities for perioperative adverse outcomes compared with the tabulated indexes, which are more difficult to implement in clinical practice. However, both the demographic factors and the comorbidity indexes had poor discriminative ability for adverse events.

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