• 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • br Table br Univariate and


    Table 2
    Univariate and multivariable logistic regression predictors of continent diversion. Statistically significant if bold
    OR CI P
    OR CI P
    Ref − − Female
    zip code of residence
    Not insured
    Ref − − Private/Managed Care
    Ref − − South/southeast
    Nonacademic facility
    Ref − − Academic program
    Ref − − Urban
    Ref − − Open
    Ref − − Positive
    Fig. 1. Temporal trend of continent diversion after radical cystectomy from 2004 to 2013 in the United States.
    of 14.5% is similar to previous national database study esti-mates of 8% to 19% [11−14]. While confirming prior stud-ies that 2-Guanidinoethylmercaptosuccinic Acid cancer care is becoming increasingly centralized to high-volume centers [15,16], we identified a declining rate of CD across most subgroups suggesting that the decline in CD usage cannot be entirely explained by an aging, increasingly comorbid population. We also showed that at a facility level, high-volume centers that continue to perform a large percentage of RC using the traditional open approach have significantly higher rates of CD compared to high-volume, predominantly robotic centers.
    There are important disparities that may predict the type of diversion a patient receives. Our study suggests that those on Medicare, who earn less, and do not live in a met-ropolitan county are more likely to receive an ID. Despite guidelines by the American Urologic Association on mus-cle-invasive bladder cancer, recommending clinicians dis-cuss all forms of UD with a patient undergoing RC [17]. There may be barriers related to care access that prohibit certain populations in the United States from receiving their choice of UD. Socioeconomic status is an important driver of bladder cancer outcomes [18,19] and appears to impact type of UD as well.
    Interestingly, even in academic centers and high-volume facilities, both of which were positively associated with undergoing CD, the overall rate of CD declined. To further investigate this finding, we analyzed the phenomenon of regionalization of bladder cancer treatment and changes in surgical approach. RC with UD is one of the most complex urologic procedures with significant morbidity and 
    mortality [2]. Improved outcomes at high-volume centers have been described [20], and our study confirms that for patients with bladder cancer who require RC, some degree of regionalization occurred during the study period. While overall, a MIS approach had a higher rate of CD compared to open RC, when we assessed high-volume hospitals per-forming a large proportion of RC with an open approach compared to high-volume MIS facilities, the open centers had a higher CD rate. This suggests that while national trends are indicating an increase in the utilization of the MIS approach for RC and a decline in CD rates, the rela-tionship between the 2 surgical techniques is complex and volume-dependent [21]. Further study is needed to deter-mine if the uptake of robotic surgery is contributing to the decline in utilization of CD.
    A changing patient demographic may be contributing to the rise in ID rates. Compared to 2004 to 2006, there was an increasing mean age and patients with at least 1 comor-bidity in the 2010 to 2013 period. Despite previous research showing no difference in complication rates comparing ID with orthotopic neobladder in elderly patients [22], we demonstrated that older patients and those with more comorbidities continue to be more likely to undergo ID diversion. Our study emphasizes that better education is needed so that appropriately selected patients are offered all UD options with a thorough discussion of the risks and benefits of each.
    We believe our study adds to the current literature due to the extent of variables assessed, despite groups previously looking at trends in UD using the Nationwide Inpatient
    Table 3
    Trends in population characteristics. Statistically significant if bold
    Year of diagnosis
    Age (mean)
    Charlson comorbidity index
    % of no high school graduates in patient’s zip code of residence
    Median income
    Facility type
    Nonacademic facility
    Academic program
    Facility location
    Hospital volume
    County description