Abstract
Objective
To investigate the modified frailty index (mFI) as a pre-operative predictor of post-operative complications following radical cystectomy in bladder cancer patients.
Materials and Methods
Patients undergoing radical cystectomy (RC) were identified from the National Surgical Quality Improvement Program (NSQIP) participant use files (2011-2013). The mFI was defined in prior studies with 11 variables based on mapping the Canadian Study of Health and Aging Frailty Index to NSQIP comorbidities and activities of daily living (ADL)s. Modified frailty index groups were determined by the number of risk factors per patient (0, 1, 2, ≥3). Univariate, χ2, independent sample t-test, and logistic regression analyses were performed when appropriate. A sensitivity analysis was performed to determine the mFI value at which Clavien 4 and 5 complications would reach significance.
Results
Of the 2679 cystectomy patients identified, 31% percent of patients had a mFI of 0, 44% had a mFI of 1, 21% had a mFI of 2, and 4% had a mFI ≥ 3. Overall, 59% of patients experienced a Clavien complication. When stratified at a cutoff of mFI >=2, the overall complication rate was not different (61.7% vs. 58.3%, p=0.1319), but the mFI2 or greater group had a significantly higher rate of Clavien grade 4 or 5 complications (14.6% vs. 8.3%, p<0.001) and overall mortality rate (3.5% vs. 1.8%, p=0.0128) in the 30-day post-operative period. The multivariate logistic regression model showed independent predictors of Clavien grade 4 or 5 complications were age >80 years old (OR, 1.58 [1.11-2.27]), mFI2 (odds ratio [OR], 1.84 [1.28-2.64]), and mFI3 (OR, 2.58 [1.47-4.55]).
Conclusions
Among patients undergoing radical cystectomy, the mFI can identify those patients at greatest risk for severe complications and mortality. Given that bladder cancer is increasing in prevalence particularly among the elderly, pre-operative risk stratification is crucial to inform decision making about surgical candidacy.
Keywords: Bladder Cancer, Frailty, Radical Cystectomy, Perioperative Outcomes
1.1 Introduction
In 2015, 74,000 new cases of bladder cancer will be diagnosed and 16,000 deaths will occur due to this disease [1]. Bladder cancer is primarily a disease of older patients with approximately 9 out of 10 people with bladder cancer over the age of 55 and a mean age of muscle-invasive bladder cancer at diagnosis is 73 years of age [1]. It is estimated that the number of individuals over 65 in the United States will almost double in the next 35 years to more than 88 million by 2050 [2]. As a result, the burden of bladder cancer on the US healthcare system will continue to rise over the next few decades as America’s population continues to age and thus increased utilization of surgery will be necessary to treat advanced cancers of the genitourinary tract.
The preferred treatment for muscle-invasive bladder cancer is radical cystectomy (RC) with pelvic lymph node dissection. However, the rates of perioperative complications ranges from 28% to 64% with 30 day mortality rates from 1.1% to 5.2% in patients undergoing this procedure [3-13]. In light of significant perioperative morbidity and mortality, it is important to identify patient-level factors which may be used in preoperative risk stratification and to help guide the decision making process about whether to proceed with radical cystectomy, as there is a subset of patients that would benefit from bladder sparing radiation therapy [14]. Furthermore, identification of modifiable risk factors may allow for interventions aimed at mitigating specific perioperative complications.
While chronologic age has been a good predictor of adverse postoperative outcomes following surgeries in various specialties, studies have identified frailty as a more accurate predictor of adverse postoperative outcomes in cohorts of patients undergoing gynecological oncology and bariatric surgery [15, 16]. Therefore, a frailty index is an objective measure that could be used for peri-operative risk stratification. Frailty can be defined as a biologic syndrome of decreased reserve and resistance to stressors, resulting from cumulative declines across multiple physiologic systems, and causing vulnerability to adverse outcomes [17]. One of the first assessments created to assess frailty was the Fried Frailty phenotype which defined frailty to include at least 3 of the following: unintentional weight loss, self-reported exhaustion, weak grip strength, slow walking speed, and low physical activity [17]. Subsequently, a widely accepted and validated index of frailty used to operationalize the phenotype stated above was created and termed the Canadian Study of Health and Aging Frailty Index (CSHA-FI). This index incorporates 70 deficits, including symptoms, signs, disabilities, and diseases, to calculate a measure of frailty [18]. However, identifying and quantifying 70 items for each patient provides a barrier to the practical use of the CSHA-FI in patient populations. As a result, a modified frailty index (mFI) containing 11 variables that were selected by mapping the CSHA-FI items onto the existing National Surgical Quality Improvement Program (NSQIP) preoperative variables was created, and it was first utilized in colectomy patients as a successful predictor of ICU-level complications and mortality [19]. The mFI is a modification of a comorbidity index that incorporates specific comorbidities of interest with an assessment of functional status in its calculation.
Currently there is no literature to support the use of the mFI in patients undergoing cystectomy. Therefore, our objective was to investigate the mFI as a pre-operative predictor of post-operative complications following radical cystectomy.
1.2 Patients and Methods
Approval for this research was secured from The Johns Hopkins Medicine Institutional Review Board.
1.2.1 Patient Cohort
Patients undergoing cystectomy were identified from the National Surgical Quality Improvement Program (NSQIP) participant use files (2011-2013). Briefly, the NSQIP dataset is a national prospectively maintained registry run by the American College of Surgeons (ACS). Unlike a claims-based dataset, all data are abstracted prospectively by nurses to verify clinical information. A three year interval was selected to allow for the maturation of the NSQIP dataset (which was small and undersampled prior to 2011) and to reflect a contemporaneous cohort of bladder cancer patients. Additionally, the data for readmissions and reoperations was only available after 2011.
Patients undergoing radical cystectomy (RC) for bladder cancer were identified based on Current Procedure Terminology (CPT) codes for RC (51570, 51575, 51580, 51585, 51590, 51595, 51596, and 51597) and the International Classification of Diseases (ICD9) codes for bladder cancer (188 and 188.x). This was a similar methodology to prior urologic studies using NSQIP(20). The mFI was defined as in prior studies based on mapping the Canadian Study of Health and Aging Frailty Index to NSQIP comorbidities and activities of daily living (ADL)s (see Table 1)(18). Eleven variables from the CSHA-FI were matched with the preoperative comorbidities in NSQIP to create the mFI (Table 1). Modified frailty index groups were determined by the number of risk factors per patient (0, 1, 2, ≥3).
Table 1.
Risk factors used to calculate the modified frailty index and incidence in cohort.
| Risk Factor | Score | No. in Cohort |
|---|---|---|
|
Functional health status prior to surgery: partially
or totally dependent |
1 | 39 (1.5%) |
| Diabetes Mellitus Type II | 1 | 529 (19.8%) |
| Chronic Obstructive Pulmonary Disease | 1 | 230 (8.6%) |
| Congestive Heart Failure | 1 | 18 (0.67%) |
|
History of myocardial infarction within past 6
months |
1 | 3 (0.11%) |
|
Prior cardiac surgery, percutaneous coronary
intervention, or angina within past month |
1 | 92 (3.43%) |
| Hypertension | 1 | 1660 (62.0%) |
| Impaired sensorium | 1 | 0 |
| History of transient ischemic attack | 1 | 10 (0.37%) |
| History of cerebrovascular accident | 1 | 5 (0.19%) |
|
Peripheral vascular disease requiring surgery or
active claudication present |
1 | 12 (0.45%) |
The risk factors above were chosen by mapping the Canadian Study of Health and Aging Frailty Index to NSQIP comorbidities and activities of daily living [19]. The number of comorbidities a patient exemplified was tallied, and this total value was used as the mFI score. The incidence of each comorbidity is listed.
1.2.2 Statistical Analysis
Primary outcomes of interest included the presence of Clavien 4 (life-threatening complication requiring ICU management) or 5 (death) complications within 30 days of surgery. Secondary outcomes of interest included having a complication of any type within 30 days of surgery, specific complications (septic shock, ventilator dependence for >48 hours, unplanned intubation, myocardial infarction [MI], acute renal failure requiring dialysis [ARF], cardiac arrest requiring cardiopulmonary resuscitation [CA], surgical site infection [SSI], deep vein thrombosis [DVT], pulmonary embolism [PE]) as well as operative time, hospital length of stay (LOS), re-operation, and re-admission within 30 days of surgery.
Univariate χ2 and independent sample t-test were utilized to compare baseline demographic information for categorical and continuous variables as appropriate. Additional univariate analyses were performed to compare basic complication outcomes according to mFI. A sensitivity analysis was performed to determine the mFI group threshold at which the rate of Clavien 4 or 5 complications became significantly higher. A multivariate logistic regression model was then created using all variables that had p<0.10 in the univariate logistic regression analysis. This multivariate model contained age, gender, race, smoking status, and the mFI score to predict the likelihood of having a Clavien grade 4 or 5 complication. All Statistical analysis was performed using SAS®, version 9.1. A p-value of <0.05 was considered statistically significant.
1.3 Results
In total, 2679 patients were identified as having undergone radical cystectomy for bladder cancer in the National Surgical Quality Improvement Program from 2011-2013.
1.3.1 Cohort Demographics
Demographics data for this cohort is listed in Table 2. Thirty-one percent of patients had a mFI of 0, 44% had a mFI of 1, 21% had a mFI of 2, and 4% had a mFI ≥ 3. There was no significant difference in gender (p=0.24) or race (p=0.2151) between the mFI groups. Higher mFI group status was associated with a higher pre-operative BMI, pre-operative creatinine, and ASA classification (all p <0.001). As the mFI group number increased, patients were more likely to be smokers with 9.6% smokers in the mFI0 group, 7.8% in the mFI1 group, 9.0% in the mFI2 group, and 33.3% in the mFI3 group (p<0.001). Higher mFI group status was also associated with older age; mean age of 65.0 for mFI0, 70.1 for mFI1, 70.7 for mFI2, and 72.8 for mFI3 (p<0.001).
Table 2.
Baseline demographics stratified by modified frailty index
| Characteristic | mFI = 0 | mFI = 1 | mFI = 2 | mFI >= 3 | p-value |
|---|---|---|---|---|---|
| N | 843 (31.5%) |
1176 (43.9%) | 555 (20.7%) | 105 (3.9%) | |
| Mean Age (SD) | 65.0 (11.9) | 70.1 (10.1) | 70.7 (9.7) | 72.8 (9.0) | p<0.001 |
| Gender | |||||
| - Female | 180 | 217 (18.5 %) | 99 (17.8%) | 17 (16.2%) | P=0.24 |
| - Male | (21.4%) 663 (78.6%) |
959( 81.5%) | 456 (82.2%) | 88 (83.8%) | |
| Race | |||||
| - Caucasian | 676 | 974 (82.8 %) | 468 (84.3%) | 85 (80.9%) | P=0.2151 |
| - Non-Caucasian | (80.2%) 167 (19.8%) |
202 (17.2%) | 87 (15.7%) | 20 (19.1%) | |
| BMI (SD) | 26.9 (5.2) | 29.0 (5.9) | 30.0 (6.4) | 29.8 (6.6) | p<0.001 |
| Pre-op | 1.07 (0.61) | 1.20 (0.65) | 1.23 (0.75) | 1.31 (0.59) | p<0.001 |
| Creatinine (SD) | |||||
| Smoking Status | |||||
| - Smoker | 81 (9.6%) | 92 (7.8%) | 50 (9.0%) | 35 (33.3%) | p<0.001 |
| - Non-smoker | 762 (90.4%) |
1084 (92.2%) | 505 (91.0%) | 70 (66.7%) | |
| ASA Class | |||||
| - Class 1 | 14 (1.7%) | 1 (0.09%) | 0 | 0 | p<0.001 |
| - Class 2 | 339 | 258 (22.0%) | 64 (11.6%) | 4 (3.8%) | |
| - Class 3 | (40.3%) | 850 (72.4%) | 451 (81.4%) | 76 (72.4%) | |
| - Class 4 | 469 (55.7%) 20 (2.4%) |
65 (5.5%) | 39 (7.0%) | 25 (23.8%) |
In higher mFI groups, there were older patients with higher BMIs pre-operative creatinines, and ASA classification that were more likely to be smokers. There was no difference in gender and race between the mFI groups.
1.3.2 Peri-operative Outcomes
Table 3 shows peri-operative outcomes stratified by an mFI cutoff greater than or equal to 2. There was a significant difference in mean operative time (352.1 vs. 353.6 min, p<0.01) and length of hospital stay (10.0 vs. 11.0 days. p<0.01) between groups. There was no significant difference in surgical site infections rate (5.0% vs. 5.8%, p=0.4169), 30-day readmission rate (20.3% vs. 21.1%, p=0.6548), 30-day reoperation rate (5.9% vs. 7.1%, p=0.2563), and overall complication rate (61.7% vs. 58.3%, p=0.1319) between groups. Several types of complications were more common in the mFI2 or greater group including respiratory (5.2% vs. 9.7%, p<0.001), cardiovascular (2.2% vs. 4.4%, p=0.0024), and renal (1.7% vs. 3.2%, p=0.0240) complications. Notably, the mFI2 or greater group had a significantly higher rate of Clavien grade 4 or 5 complications (14.6% vs. 8.3%, p<0.001) within 30 days of surgery and overall mortality rate (3.5% vs. 1.8%, p=0.0128).
Table 3.
Peri-operative outcomes stratified with cutoff of modified frailty index>=2.
| Characteristic | mFI < 2 | mFI >= 2 | p-value |
|---|---|---|---|
| OR Time (min, with 95% CI) |
352.1 (347-358) |
353.6 (344-363) |
p<0.01 |
| Hospital Length of Stay (LOS) |
10.0 (9.7- 10.4) |
11.0 (10.2- 11.8) |
p<0.01 |
| Surgical Site | |||
| Infection | 100 | 38 (5.8%) | p=0.4169 |
| - Yes | (5.0%) | 622 | |
| - No | 1919 | ||
| Respiratory | |||
| Complication | 105 | 64 (9.7%) | p<0.001 |
| - Yes | (5.2%) | 596 | |
| - No | 1914 | ||
| Renal Complication | |||
| - Yes | 35 (1.7%) | 21 (3.2%) | p=0.0240 |
| - No | 1984 | 639 | |
| CV Complication | |||
| - Yes | 44 (2.2%) | 29 (4.4%) | p=0.0024 |
| - No | 1975 | 631 | |
| 30-day | |||
| Readmissions | 401 | 137 | p=0.6548 |
| - Yes | (20.3%) | (21.1%) | |
| - No | 1572 | 511 | |
| 30-day | |||
| Reoperations | 119 | 47 (7.1%) | p=0.2563 |
| - Yes | (5.9%) | 613 | |
| - No | 1900 | ||
| Overall Mortality | |||
| - Yes | 37 (1.8%) | 23 (3.5%) | p=0.0128 |
| - No | 1982 | 637 | |
| Overall | |||
| Complications (Any grade) |
1178 (58.3%) |
407 (61.7%) |
p=0.1319 |
| - Yes | 841 | 253 | |
| - No | |||
| Clavien grade 4 or 5 complication |
p<0.001 | ||
| - Yes | 168 | 96 | |
| - No | (8.3%) | (14.6%) | |
| 1851 | 564 |
The patients in the higher frailty group had a higher rate of Clavien grade 4 or 5 complications, higher overall mortality, longer OR times, longer hospital length of stays,.more respiratory, renal, and cardiovascular complications. There was no difference in overall complication rates, 30-day readmission, and 30-day reoperation rates between the two groups.
1.3.3 Multivariate Logistic Regression Model
The multivariate logistic regression model showed age >80 years old (OR, 1.58 [1.11-2.27]), mFI2 (odds ratio [OR], 1.84 [1.28-2.64]), and mFI3 (OR, 2.58 [1.47-4.55]) are independent predictors of the likelihood of Clavien grade 4 or 5 complications with mFI3 being the strongest predictor (Table 4). While age groups <80 years old, mFI1 status, gender, race, and smoking status were not associated with Clavien grade 4 or 5 complications.
Table 4.
Logistic regression model.
| Characteristic | Clavien 4 or 5 Complications | Death | ||
|---|---|---|---|---|
| Age | ||||
| - <50 | Ref | Ref | ||
| - 50-59 | 0.99 [0.46-2.16] | 0.997 | 0.60 [0.07-5.18] | 0.64 |
| - 60-69 | 0.89 [0.57-1.37] | 0.58 | 0.55 [0.20-1.51] | 0.24 |
| - 70-79 | 0.86 [0.62-1.19] | 0.36 | 0.92 [0.47-1.83] | 0.82 |
| - >80 | 1.58 [1.11-2.27] | 0.0121 | 2.72 [1.40-5.31] | 0.0033 |
| Gender | ||||
| - Female | Ref | Ref | ||
| - Male | 1.23 [0.87-1.74] | 0.24 | 0.69 [0.38-1.26] | 0.23 |
| mFI | ||||
| - mFI0 | Ref | Ref | ||
| - mFI1 | 1.16 [0.83-1.62] | 0.39 | 0.66 [0.34-1.28] | 0.22 |
| - mFI2 | 1.84 [1.28-2.64] | 0.0010 | 1.24 [0.62-2.45] | 0.55 |
| - mFI3 | 2.58 [1.47-4.55] | 0.0010 | 2.07 [0.78-5.49] | 0.14 |
| Race | ||||
| - Non-Caucasian | Ref | Ref | ||
| - Caucasian | 1.01 [0.72-1.42] | 0.96 | 0.79 [0.42-1.49] | 0.47 |
| Smoking Status | ||||
| - Non-Smoker | Ref | Ref | ||
| - Smoker | 1.15 [0.86-1.54] | 0.36 | 1.70 [0.96-3.03] | 0.07 |
The model showed age >80 years old, mFI2 status, and mFI3 status are independent predictors of the likelihood of Clavien grade 4 or 5 complications with mFI3 being the strongest predictor.
1.4 Discussion
As the bladder cancer patient population continues to age, it is increasingly important to identify those patients at increased risk of severe complications and mortality in the perioperative period. Risk stratification is especially important for radical cystectomy, as the majority of patients experience at least one post-operative complication within 30 days of surgery [7, 8, 21]. Furthermore, the severity of complications varies greatly and is something that could potentially be predicted pre-operatively.
Physicians are required to use their subjective judgment and clinical experience to estimate the patient’s probability of having a severe adverse event following RC. However, Revenig et al have demonstrated that surgeons place too much importance on age when trying to assess frailty [22]. Due to this potential bias of age in making decisions about surgical candidacy, there is a need for objective measures of frailty that can be used by urologists to risk stratify patients pre-operatively undergoing radical cystectomy.
In this large cohort study of urothelial carcinoma patients undergoing radical cystectomy, we report that the mFI can serve as an objective tool to identify patients at a greater risk of severe (Clavien grade 4 or 5) post-operative complications including mortality. Moreover, the mFI score is indeed a stronger predictor of high-grade adverse outcomes than age. Our findings also show that for patients younger than 80 years old, age should not be used as a predictor of severe post-operative complications. Instead, these patients of lower chronological age represent a group that would benefit greatly from the use of the mFI score, instead of age, for pre-operative risk stratification, patient counseling, and determination of surgical candidacy.
The need for more information than age alone to determine postoperative outcomes in bladder cancer patients, has been previously demonstrated by studies showing that the patient’s Charlson comorbidity index, Elixhauser index, Eastern Cooperative Oncology Group (ECOG) performance status are independent predictors of 90 day mortality rates and 5 year all-cause mortality following radical cystectomy [3, 23]. While these other comorbidity indices have predictive utility, the advantage of the mFI is due to its combination of the following factors: objective measure, contains only 11 variables, takes into account functional status and medical comorbidities, and can be easily calculated during a single clinical encounter. The inclusion of the pre-operative functional status of the patient is important, as it has been shown to be an independent predictor of complication rates in urological surgery patients [7].
For this study, a mFI score of 2 represents a cut-off at which the high-grade post-operative complication and mortality rates significantly increased among patients. These types of cut-offs provide clinical utility when creating future guidelines for taking care of patients who are of questionable surgical candidacy. While a score above this cut-off would not be an absolute or relative contraindication to radical cystectomy, it would serve as an important clinical indicator that this patient may want to strongly consider other potential treatment options outside of radical cystectomy if oncological principles for treatment of bladder cancer would not be compromised with these alternative treatment options. At our center, preserving oncologic efficacy is of primary importance in the treatment of muscle-invasive bladder cancer. However, the decision to proceed with cystectomy is an individualized decision for each patient, and it is vital that patients have a comprehensive understanding of the oncologic efficacy of each treatment option available to them and the risk of low and high-grade complication rates in similar patients to appropriately weigh the risks and benefits. In some instances, patients may decide to choose treatments with equivalent or lower oncologic efficacy for the benefit of a lower high-grade complication rate. It is important to note that while the mFI can serve as a useful tool in pre-operative counseling and decision-making, there are several other factors including age, BMI, ASA class, and patient expectations that should still be taken into account when making a decision to proceed with radical cystectomy.
The use of mFI to risk stratify patients pre-operatively could play in important role in the reimbursement scheme used in pay for performance (P4P) models. Advocates of the P4P model argue the model incentivizes healthcare providers to provide the best quality of care for patients in order to improve overall patient outcomes [24]. The P4P reimbursement schemes are constructed to financially penalize providers for patients that experience post-operative complications. However, the insurance companies are failing to acknowledge that each patient is not equivalent in their likelihood of having a post-operative complication. By doing so, the insurance companies are incentivizing provides to avoid performing procedures, such as radical cystectomies, that have high perioperative complication rates. The mFI could be utilized to identify patients with a higher likelihood of adverse events for whom the urologist would face lower penalties or even no penalties at all for complications. The addition of this risk stratification in the reimbursement scheme would be in the best interest of the patient, as it would create more appropriate incentives for urologists. The information in order to calculate the mFI is not readily available at non-NSQIP facilities, which decreases the feasibility of using this method at those centers.
In this study, we found that gender is not associated with the rate of Clavien grade 4 or 5 complications following RC. This is consistent with Siergrist et al., which found that gender was not a significant predictor of the rate of both major (Clavien grade 3-5) and minor (Clavien grade 1 or 2) complications in the perioperative period [25]. However, a recent meta-analysis of 17 studies showed female gender is associated with a higher rate of cancer specific death (CSD), which we are not able to investigate this finding due to the limitations of the NSQIP database [26]. Previously it has been suggested this gender difference is due to women presenting with more advanced disease along with sociodemographic differences and the association of gender with CSD disappears when controlling for these confounders [27]. Nevertheless, the importance of gender in post-operative outcomes and mortality requires further investigation to elucidate potential associations and confounding factors.
There are several limitations to our study including that it is a retrospective analysis of prospectively collected data in the NSQIP database. Additional limitations of the database include a follow-up period limited to 30 days post-operatively along with the lack of recording gastrointestinal complications, which are common in the radical cystectomy population [5,8,10,12,21]. Moreover, the NSQIP database does not provide information about the volume of cystectomies performed at the institutions, the quality of training of the surgeons, the type of urinary diversion performed, the histopathological staging of the bladder cancer, and whether the patient underwent neoadjuvant chemotherapy, which could all greatly affect the complication rates associated with this radical cystectomy. Additionally, the use of the mFI does not take into account the factors associated with the physical phenotype of frailty described earlier. Moreover, in the NSQIP database, there is no measure taking into account the patient’s quality of life post-operatively, which is often an important factor for patients determining whether to proceed with surgery. Future studies are warranted to investigate the ability of frailty to prospectively predict post-operative complications and mortality rates. In spite of these limitations, it is important to recognize the NSQIP data set provides a large, multi-center database with patient heterogeneity that removes the biases associated with single-center studies [15].
1.5 Conclusions
The modified frailty index is a strong predictor of high-grade post-operative complications and mortality following radical cystectomy, and it has the potential to be a very important objective tool for risk stratification and perioperative counseling of bladder cancer patients.
Highlights.
Applying the modified frailty index to assess surgical candidacy of radical cystectomy patients
Higher mFI score correlates with higher rate of Clavien grade 4 and 5 complications.
MFI score of 2 or greater represents potential threshold for surgical candidacy.
Can use the mFI pre-operatively to risk stratify patients.
Acknowledgments
Funding: This study was funded through a grant from the Johns Hopkins Greenberg Bladder Cancer Institute.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Conflict of Interest: Nothing to disclose
References
- 1.What are the key statistics about bladder cancer? [Internet] [cited 2015 Mar 2]. Available from: http://www.cancer.org/cancer/bladdercancer/detailedguide/bladder-cancer-key-statistics.
- 2.U.S. Census Bureau DIS 2008 National Population Projections: Summary Tables. [cited 2015 Mar 2]; Available from: http://www.census.gov.ezproxy.welch.jhmi.edu/population/projections/data/national/2008/summarytables.html.
- 3.Schiffmann J, Gandaglia G, Larcher A, et al. Contemporary 90-day mortality rates after radical cystectomy in the elderly. Eur J Surg Oncol. 2014;40(12):1738–45. doi: 10.1016/j.ejso.2014.10.004. [DOI] [PubMed] [Google Scholar]
- 4.Aziz A, May M, Burger M, et al. Prediction of 90-day Mortality After Radical Cystectomy for Bladder Cancer in a Prospective European Multicenter Cohort. Eur Urol. 2013;66:156–63. doi: 10.1016/j.eururo.2013.12.018. [DOI] [PubMed] [Google Scholar]
- 5.Stimson CJ, Chang SS, Barocas DA, et al. Early and late perioperative outcomes following radical cystectomy: 90-day readmissions, morbidity and mortality in a contemporary series. J Urol. 2010;184(4):1296–300. doi: 10.1016/j.juro.2010.06.007. [DOI] [PubMed] [Google Scholar]
- 6.Zakaria AS, Santos F, Dragomir A, Tanguay S. Postoperative mortality and complications after radical cystectomy for bladder cancer in Quebec : A population-based analysis during the years 2000-2009. 2014 Aug;8:259–67. doi: 10.5489/cuaj.1997. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Patel HD, Ball MW, Cohen JE, Kates M, Pierorazio PM, Allaf ME. Morbidity of Urologic Surgical Procedures: An Analysis of Rates, Risk Factors, and Outcomes. Urology. 2015;85(3):552–60. doi: 10.1016/j.urology.2014.11.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Shabsigh A, Korets R, Vora KC, et al. Defining Early Morbidity of Radical Cystectomy for Patients with Bladder Cancer Using a Standardized Reporting Methodology. Eur Urol. 2009;55(1):164–76. doi: 10.1016/j.eururo.2008.07.031. [DOI] [PubMed] [Google Scholar]
- 9.Stein JP, Lieskovsky G, Cote R, et al. Radical cystectomy in the treatment of invasive bladder cancer: long-term results in 1,054 patients. J Clin Oncol. 2001;19(3):666–75. doi: 10.1200/JCO.2001.19.3.666. [DOI] [PubMed] [Google Scholar]
- 10.Quek ML, Stein JP, Daneshmand S, et al. A critical analysis of perioperative mortality from radical cystectomy. J Urol. 2006;175(3):886–9. doi: 10.1016/S0022-5347(05)00421-0. [DOI] [PubMed] [Google Scholar]
- 11.Mayr R, May M, Martini T, et al. Predictive capacity of four comorbidity indices estimating perioperative mortality after radical cystectomy for urothelial carcinoma of the bladder. BJU Int. 2012;110(6B):0–5. doi: 10.1111/j.1464-410X.2012.10938.x. [DOI] [PubMed] [Google Scholar]
- 12.Schiavina R, Borghesi M, Guidi M, et al. Perioperative complications and mortality after radical cystectomy when using a standardized reporting methodology. Clin Genitourin Cancer. 2013;11(2):189–97. doi: 10.1016/j.clgc.2012.12.003. [DOI] [PubMed] [Google Scholar]
- 13.Isbarn H, Jeldres C, Zini L, et al. A Population Based Assessment of Perioperative Mortality After Cystectomy for Bladder Cancer. J Urol [Internet]. American Urological Association. 2009;182(1):70–7. doi: 10.1016/j.juro.2009.02.120. [DOI] [PubMed] [Google Scholar]
- 14.Kaufman D, Shipley W, Griffin P, Heney N, Althausen A, Efird JT. Selective Bladder Preservation by Combination Treatment of Invasive Bladder Cancer. N Engl J Med. 1993;329(19):1377–82. doi: 10.1056/NEJM199311043291903. [DOI] [PubMed] [Google Scholar]
- 15.Kolbe N, Carlin AM, Bakey S, Louwers L, Horst HM, Rubinfeld I. Assessing Risk of Critical Care Complications and Mortality in the Elective Bariatric Surgery Population Using a Modified Frailty Index. Obes Surg. 2014:1–7. doi: 10.1007/s11695-014-1532-3. [DOI] [PubMed] [Google Scholar]
- 16.Uppal S, Igwe E, Rice LW, Spencer RJ, Rose SL. Frailty index predicts severe complications in gynecologic oncology patients. Gynecol Oncol. 2015:1–4. doi: 10.1016/j.ygyno.2015.01.532. [DOI] [PubMed] [Google Scholar]
- 17.Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146–56. doi: 10.1093/gerona/56.3.m146. [DOI] [PubMed] [Google Scholar]
- 18.Searle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr. 2008;8:24. doi: 10.1186/1471-2318-8-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Obeid NM, Azuh O, Reddy S, et al. Predictors of critical care-related complications in colectomy patients using the National Surgical Quality Improvement Program: exploring frailty and aggressive laparoscopic approaches. J Trauma Acute Care Surg. 2012;72(4):878–83. doi: 10.1097/TA.0b013e31824d0f70. [DOI] [PubMed] [Google Scholar]
- 20.Johnson DC, Nielsen ME, Matthews J, et al. Neoadjuvant chemotherapy for bladder cancer does not increase risk of perioperative morbidity. BJU Int. 2013:1–8. doi: 10.1111/bju.12585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Novara G, De Marco V, Aragona M, et al. Complications and mortality after radical cystectomy for bladder transitional cell cancer. J Urol. 2009;182(3):914–21. doi: 10.1016/j.juro.2009.05.032. [DOI] [PubMed] [Google Scholar]
- 22.Revenig LM, Canter DJ, Henderson MA, et al. Preoperative quantification of perceptions of surgical frailty. J Surg Res. 2015;193(2):583–9. doi: 10.1016/j.jss.2014.07.069. [DOI] [PubMed] [Google Scholar]
- 23.Boorjian S a., Kim SP, Tollefson MK, et al. Comparative performance of comorbidity indices for estimating perioperative and 5-year all cause mortality following radical cystectomy for bladder cancer. J Urol. 2013;190(1):55–60. doi: 10.1016/j.juro.2013.01.010. [DOI] [PubMed] [Google Scholar]
- 24.Gonzalez CM, Penson D, Kosiak B, Dupree J, Clemens JQ. Pay for Performance: Rationale and Potential Implications for Urology. J Urol. 2007;178(2):402–8. doi: 10.1016/j.juro.2007.03.095. [DOI] [PubMed] [Google Scholar]
- 25.Siegrist T, Savage C, Shabsigh A, Cronin A, Donat SM. Analysis of gender differences in early perioperative complications following radical cystectomy at a tertiary cancer center using a standardized reporting methodology. Urol Oncol. 2010;28(1):112–7. doi: 10.1016/j.urolonc.2009.04.012. [DOI] [PubMed] [Google Scholar]
- 26.Liu S, Yang T, Na R, et al. The impact of female gender on bladder cancer-specific death risk after radical cystectomy: a meta-analysis of 27,912 patients. Int Urol Nephrol. 2015;47(6):951–8. doi: 10.1007/s11255-015-0980-6. [DOI] [PubMed] [Google Scholar]
- 27.Shariat SF, Sfakianos JP, Droller MJ, Karakiewicz PI, Meryn S, Bochner BH. The effect of age and gender on bladder cancer: A critical review of the literature. BJU Int. 2010;105(3):300–8. doi: 10.1111/j.1464-410X.2009.09076.x. [DOI] [PMC free article] [PubMed] [Google Scholar]