Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.
Despite the increased morbidity and mortality of radical cystectomy in elderly individuals with bladder cancer numerous studies show that surgery can provide a survival benefit. We sought to better identify patients at substantial risk for postoperative mortality.
We evaluated 220 consecutive patients 75 years old or older treated with radical cystectomy for bladder cancer at a single institution from 2000 to 2008. The analytical cohort comprised 169 patients with complete preoperative data available. A Cox proportional hazards model was used to determine the value of precystectomy clinical information to predict 90-day survival after radical cystectomy. Results were used to create a nomogram predicting the probability of 90-day survival after radical cystectomy. The model was then subjected to 200 bootstrap resamples for internal validation.
Of the 220 patients 28 (12.7%) died within 90 days of surgery. Older age (HR 2.30, 95% CI 1.22-4.32) and lower preoperative albumin (HR 2.50, 95% CI 1.40-4.45) were significant predictors of 90-day mortality. We developed a nomogram based on patient age, clinical stage, Charlson comorbidity index and albumin to predict the likelihood of 90-day mortality with 75% accuracy. Internal validation showed a bootstrap adjusted concordance index of 71%.
We developed a nomogram that provides individualized risk estimations to predict the probability of 90-day mortality, potentially enhancing preoperative counseling and providing clinicians with an added tool to individualize treatment decisions in this challenging patient population. These data suggest that albumin is a strong predictor of postoperative mortality and show the importance of assessing this variable before surgery.
Written by:
Morgan TM, Keegan KA, Barocas DA, Ruhotina N, Phillips SE, Chang SS, Penson DF, Clark PE, Smith JA Jr, Cookson MS. Are you the author?
Reference: J Urol. 2011 Sep;186(3):829-34.
doi: 10.1016/j.juro.2011.04.089
PubMed Abstract
PMID: 21788035
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