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© 2023 The Authors. Société Internationale d'Urologie Journal, published by the Société Internationale d'Urologie, Canada.

Key Words Competing Interests Article Information

Frailty, bladder cancer, TURBT, postoperative 
complications, risk assessment

None declared. Received on August 15, 2022 
Accepted on October 22, 2022

Soc Int Urol J. 2023;4(3):187–194

DOI: 10.48083/NQEF6409

187SIUJ.ORG SIUJ  •  Volume 4, Number 3  •  May 2023

ORIGINAL RESEARCH

A Prospective Evaluation of Different Frailty Indices 
in Patients Undergoing Transurethral Resection of 
Bladder Tumor
Neebal Abunaser,1 Adnan El- Achkar,2 Mohamad K. Abou Chaar,1 Ali Ababneh,1 Sattam A. Halaseh,1  
Ala’a Farkouh,1 Ramiz Abo-Hijleh,3 Awni D. Shahait,4 Samer Salah,5 Mohammed Shahait1

1 Surgery Department, King Hussein Cancer Center, Amman, Jordan 2 Surgery Department, American University of Beirut Medical Center, Beirut, Lebanon  
3 Radiation Oncology Department, King Hussein Cancer Center, Amman, Jordan 4 Surgery Department, Wayne State University, Michigan, United States  
5 Medical Department, King Hussein Cancer Center, Amman, Jordan

Abstract

Background Most studies investigating the relationship between preoperative frailty and postoperative outcomes 
among bladder cancer patients only assess frailty retrospectively in patients who have undergone radical cystectomy. 
Transurethral resection of bladder tumor (TURBT) is a commonly performed procedure in outpatient settings for a 
large number of bladder cancer patients. The prevalence of frailty among bladder cancer patients and its impact on 
postoperative complications and mortality are not well studied. 

Methods To assess the prevalence of frailty among bladder cancer patients planned for TURBT at a tertiary cancer 
center using the modified frailty index (mFI) and Risk Analysis Index (RAI) and further assess the impact of these 
indices on 30-day postoperative complications and mortality rates. 

Results Between May 2020 and March 2021, 343 consecutive patients were enrolled. The mean age of the cohort was 
64.8 ± 13.1 years, 86.6% were male, and 82% had non–muscle-invasive bladder cancer (NMIBC). The majority of the 
cohort (92%) was found to have low American Society of Anesthesiologists (ASA) score class (I + II), while 35.3% were 
labeled as frail using mFI 2+, and 32.1% based on RAI (III, IV). The 30-day readmission, postoperative complications, 
and mortality rates in this cohort were 3.8%, 2.3%, and 6.6%, respectively. RAI was a better indicator of mortality 
compared to mFI. As such, patients with low RAI score (I, II) had 0.054 odds for 30-day mortality compared to the 
patients with high RAI score (III, IV) (OR 0.054; CI 95%, 0.004 to 0.784; P = 0.033).

Conclusion Frailty, as measured by Risk Analysis Index, is an independent predictor of early mortality in patients 
undergoing TURBT. Preoperative frailty assessment may improve risk stratification and patient counseling prior to 
surgery. 

Introduction
Frailty, a state of decreased homeostatic reserve, is characterized by dysregulation across multiple physiologic and 
molecular pathways, and a limited ability to compensate for and recover from stressors. It is particularly relevant 
to the perioperative period, during which patients are subject to high levels of stress and inflammation. Surgery is a 
major stressor, and current preoperative evaluation methods fail to assess the physiological reserve of patients with 
the same chronological age. Frailty has been shown to be an independent predictor of prolonged length of stay in 
hospital and increased postoperative complications[1]. Frailty is an age-independent index, which is more prevalent in 
elderly due to an increase in comorbidities and functional decline. The routine implementation of a frailty assessment 
could provide a more comprehensive and individualized perioperative risk stratification[1–4].

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Most studies investigating the relationship between 
preoperative frailty and postoperative outcome only 
assess frailty retrospectively, and the actual benefit 
from a routine frailty assessment followed by an indi-
vidualized treatment plan is lacking[5–7]. In muscle-in-
vasive bladder cancer (MIBC), Fried Frailty Criteria 
(FFC) including grip strength, gait speed, exhaustion, 
physical activity, and shrinking was predictive of high-
grade complications in patients undergoing radical 
cystectomy. Performance status, tumor size, and extent 
of resection are perioperative factors associated with 
postoperative complications and mortality in patients 
undergoing transurethral resection of bladder tumor 
(TURBT)[8]. The prevalence of frailty varies widely 
between different cohorts, yet frailty is one of the most 
significant factors affecting outcomes. Modified frailty 
index (mFI) and Risk Analysis Index (RAI) are frailty 
assessment scores that involve 11 and 15 items, respec-
tively, which include important factors such as func-
tional status, chronic obstructive pulmonary disease 
(COPD), and recent pneumonia as well as activities of 
daily living. Both indices have been used previously to 
predict MM, but they have never been assessed prospec-
tively in patients undergoing TURBT[8–10].

In this study we aim to assess the prevalence of frailty 
among bladder cancer patients planned for staging 
and restaging TURBT using mFI and RAI, and assess 
the impact of frailty indices on 30-day postoperative 
complications and mortality[8]. 

Methods
This is a prospective observational study of bladder 
cancer patients planned for staging and restaging 
TURBT at a tertiary cancer center that seeks to assess 
t he preva lence of frailt y preoperatively and its 
relationship to 30-day postoperative complications and 
mortality rates.

Between May 2020 and March 2021, 343 bladder 
cancer patients who were planned for staging TURBT 

Abbreviations 
ASA American Society of Anesthesiologists 
AUC area under the curve 
CI confidence interval
mFI modified frailty index 
MIBC muscle-invasive bladder cancer 
NMIBC non–muscle-invasive bladder cancer 
OS overall survival
RAI Risk Analysis Index 
ROC receiver operating characteristic 
TURBT transurethral resection of bladder tumor

or restaging TURBT were identified. We prospectively 
collected mFI and RAI for those patients with blad-
der cancer who were planned for staging and restaging 
TURBT and collected the 30-day postoperative compli-
cations and mortality rates after the planned proce-
dure. All patients were mandated to have a negative 
COVID-19 PCR test result 24 hours before the surgery. 
Participants were enrolled before the surgical interven-
tion. During the encounter, a member of the treatment 
team filled out the required information for the frailty 
scale. Patients received a unique identifier number that 
was maintained in our research database in a secure, 
encrypted, password-locked file and on an institution-
ally secured and managed device. 30-day postoperative 
complications and mortality were collected prospec-
tively from the hospital administrative database. The 
database is linked to the national population census, and 
any death incident is captured without specific cause of 
death. As part of the routine follow-up for outpatient 
procedures in our institution, all patients receive calls 
on days 1, 7, and 28 post-discharge, any events such as 
admission in another facility, or intervention usually 
documented in the patients’ chart. 

The mFI was proposed and validated by Chimukangara  
et al., and the following variables were included: COPD 
or recent pneumonia, congestive heart failure, func-
tional status (not independent), hypertension requiring 
medications, and diabetes mellitus. This was an abridged 
version of the 11-item mFI. The score is calculated by  
the number of listed comorbidities, and it’s catego-
rized as 0, 1, and 2+. The higher the score, the sicker the 
patient[9].

RAI assessment is based on 15-item survey relying 
on patients’ reporting and includes 4 items to evaluate 
activities of daily living and other 11 variables, which 
overall predicts 6-month mortality based on analysis of 
Minimum Data Set Mortality Risk Index-Revised. The 
score is classified into 4 groups: Class I: ≤ 15; Class II: 
16–25; Class III: 26–35; and Class IV: ≥ 36[10].

Univariate analyses were performed using the 
chi-square and unpaired Student t test for categorical 
and continuous variables, respectively. A receiver oper-
ating characteristic (ROC) curve was generated with 
a 95% confidence interval (CI) for the area under the 
curve (AUC). Multivariate logistic regression analy-
sis adjusting for preoperative variables was performed 
to identify predictors of mortality. Univariate Cox 
regression analysis was performed to identify correla-
tion between mFI, RAI, and stage of cancer with over-
all survival (OS). Kaplan-Meier survival was utilized to 
determine OS and stage-specific survival. A P-value < 
0.05 was considered statistically significant. All analy-
ses were performed using SPSS (IBM Corp. Released 
2017. IBM SPSS Statistics for Windows, Version 25.0. 

188 SIUJ  •  Volume 4, Number 3  •  May 2023 SIUJ.ORG

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Armonk, New  York: IBM Corp.). This study was 
approved by the institutional review board at King 
Hussein Cancer Center, Amman, Jordan (Protocol 
number: 20-KHCC-43).

Results
In total, 343 bladder cancer patients participated in the 
study. The mean age of the cohort was 64.8 ± 13.1 years, 
86.6% were male, and 87.5% had non–muscle-invasive 
bladder cancer (NMIBC). Of the cohort, 92% were found 
to have low American Society of Anesthesiologists (ASA) 
class (I + II). Overall, 60.9% of the patients had stage 0 
disease, 21.9% had stage 1, and only 5.8% had metastatic 
disease. Preoperatively, among the 343 patients, 129 
(37.6%) received intravesical treatment with either 
Bacillus Calmette-Guérin (BCG) or chemotherapy such 
as mitomycin.

Patients with MIBC were more likely to have a higher 
ASA class, were more frail based on both RAI and mFI 
scores, and had lower preoperative hemoglobin and 
preoperative albumin levels. All these factors might 
explain why these patients had a higher mortality rate 
compared to NMIBC (Table 1). 

Tables 2 and 3 display the prevalence of frailty, and 
operative and postoperative outcomes using the mFI 
and RAI, respectively. While 35.3% of the patients were 
labeled as frail using mFI 2+, 32.1% were labeled frail 
based on RAI (III, IV). The 30-day readmission, postop-
erative complications, and overall mortality rates in the 
entire cohort were 3.8%, 2.3%, and 6.6%, respectively. 
Table 4 summarizes the recorded complications in our 
cohort.

RAI was a better indicator of the mortality compared 
to mFI (AUC, 0.832; P = 0.049; and AUC, 0.672;  
P = 0.063, respectively), as shown in Figure 1. RAI at a 
cutoff of 26.5 has 81.0% sensitivity and 57.8% specificity 
in predicting post-TURBT mortality identified by ROC. 
As such, patients with a low RAI score (I, II) had 0.054 
odds for mortality compared to patients with a high RAI 
score (III, IV) (95% CI, 0.004–0.784; P = 0.033), using 
logistic regression analysis. 

As illustrated in Figure 2, Kaplan-Meier curve shows 
OS difference between different cancer stages and 
invasiveness. Similarly, Figures 3 and 4 show Kaplan-
Meier curves for OS by mFI and RAI classifications. 
Cox regression analysis showed that MIBC status had 
a hazard ratio (HR) of 0.051 (95% CI 0.013 to 0.202;  
P < 0.001), and other factors such as mFI and RAI did 
not have a significant impact on OS. 

Discussion
In this study, using both R AI and mFI to assess 
the relationship between preoperative frailty and 

TABLE 1. 

Patients' characteristics, and operative and 
postoperative outcomes based on muscular 
invasiveness 

N (%)

Non–muscle-
invasive bladder 

cancer
300 (87.5%)

Muscle-invasive 
bladder cancer

43 (12.5%)

Gender

 Male 260 (86.7%) 37 (86.0%)

 Female 40 (13.3%) 6 (14.0%)

Age, mean ± SD 
(years)

64.8 ± 13.1 64.7 ± 14.1

BMI, mean ± SD 
(kg/m2)

28.9 ± 5.3 27.2 ± 5.5

ASA class

I + II 281 (93.7%) 35 (81.4%)

≥ III 19 (6.3%) 8 (18.6%)

Previous 
intravesical 
treatment

109 (36.3%) 20 (46.5%)

Re-TURBT 109 (36.3%) 20 (46.5%)

Previous 
radiotherapy

0 (0.0%) 2 (4.7%)

30-day 
complications

8 (2.7%) 0 (0.0%)

All-cause 
mortality 

4 (1.4%) 17 (40.5%)

Readmission 10 (3.3%) 3 (7.0%)

RAI

 I (1–15) 1 (0.3%) 0 (0.0%)

 II (16–25) 216 (72.0%) 16 (37.2%)

 III (26–35) 55 (18.3%) 5 (11.6%)

 IV (≥36) 28 (9.3%) 22 (51.2%)

mFI

 0 114 (38.0%) 9 (20.9%)

 1 82 (27.3%) 17 (39.5%)

 +2 104 (34.7%) 17 (39.5%)

Preoperative 
hemoglobin, mean 
± SD (g/dL)

14.9 ± 8.1 12.8 ± 1.6

Hypoalbuminemia 
(<3.5 g/dL)

4 (1.3%) 6 (14.0%)

EBL, mean ± SD 
(mL)

9.4 ± 34.9 26.5 ± 46.3

ASA: American Society of Anesthesiologists; BMI: body mass index; 
EBL: estimated blood loss; mFI: modified frailty index; RAI: Risk 
Analysis Index; SD: standard deviation; TURBT: transurethral resection 
of bladder tumor.

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A Prospective Evaluation of Different Frailty Indices in Patients Undergoing Transurethral Resection of Bladder Tumor

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TABLE 2. 

Patients' characteristics, and operative and postoperative outcomes of the different 5-Item mFI 

N (%) All 343
mFI = 0

123 (35.9%)
mFI = 1

99 (28.9%)
mFI ≥ 2+

121 (35.3%)
P-value

Gender 0.451

Male 297 (86.6%) 109 (31.8%) 87 (25.4%) 101 (29.4%)

Female 46 (13.4%) 14 (4.1%) 12 (3.5%) 20 (5.8%)

Age, mean ± SD (years) 64.8 ± 13.1 59.1 ± 10.1 64.9 ± 11.5 70.6 ± 9.1 0.034

BMI, mean ± SD (kg/m2) 28.7 ± 5.3 28.0 ± 5.8 28.9 ± 5.1 29.3 ± 5.0 0.165

ASA class <0.001

I + II 316 (92.1%) 123 (35.9%) 91 (26.5%) 102 (29.7%)

≥ III 27 (7.9%) 0 (0.0%) 8 (2.3%) 19 (5.5%)

Clinical cancer stage 0.089

0 209 (60.9%) 78 (22.7%) 63 (18.4%) 68 (19.8%)

I 75 (21.9%) 30 (8.7%) 18 (5.2%) 27 (7.9%)

II 21 (6.1%) 3 (0.9%) 11 (3.2%) 7 (2.0%)

III 2 (0.6%) 1 (0.3%) 1 (0.3%) 0 (0.0%)

IV 20 (5.8%) 5 (1.5%) 5 (1.5%) 10 (2.9%)

Previous intravesical 
treatment

129 (37.6%) 45 (13.1%) 37 (10.8%) 47 (13.7%) 0.934

Previous radiotherapy 2 (0.6%) 0 (0.0%) 0 (0.0%) 2 (0.6%) 0.158

30-day complications 8 (2.3%) 6 (1.7%) 0 (0.0%) 2 (0.6%) 0.047

All-cause mortality 21 (6.6%) 4 (1.3%) 3 (0.9%) 14 (4.4%) 0.009

Readmission 13 (3.8%) 6 (1.7%) 4 (1.2%) 3 (0.9%) 0.611

RAI <0.001

I (1–15) 1 (0.3%) 1 (0.3%) 0 (0.0%) 0 (0.0%)

II (16–25) 232 (67.6%) 116 (33.8%) 69 (20.1%) 47 (13.7%)

III (26–35) 60 (17.5%) 5 (1.5%) 21 (6.1%) 34 (9.9%)

IV (≥ 36) 50 (14.6%) 1 (0.3%) 9 (2.6%) 40 (11.7%)

Preoperative hemoglobin, 
mean ± SD (g/dL)

14.6 ± 7.7 14.8 ± 1.8 15.6 ± 13.9 13.6 ± 1.8 0.147

Hypoalbuminemia (<3.5 g/dL) 10 (2.9%) 2 (0.6%) 3 (0.9%) 5 (1.5%) 0.507

EBL, mean ± SD (mL) 11.5 ± 36.2 9.7 ± 29.5 11.9 ± 21.8 12.8 ± 49.5 0.792

ASA: American Society of Anesthesiologists; BMI: body mass index; EBL: estimated blood loss; mFI: modified frailty index; RAI: Risk Analysis Index;  
SD: standard deviation.

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postoperative outcomes among bladder cancer patients 
who underwent staging and restaging TURBT, our 
results revealed that although mFI labeled a higher 
percentage of patients as frail in comparison to RAI, RAI 
was better in predicting mortality rates post-TURBT. 
However, frailty as assessed by RAI and mFI was not a 
predictor of overall survival.

Frailty index is used as a predictor of postoperative 
mortality. Previous studies have found an association 
between high mFI and postoperative complications 
and mortality in patients with MIBC, as patients with 

TABLE 3. 

Patients' characteristics, and operative and postoperative outcomes of the different RAI classes 

N (%) All
I (0–15)
1 (0.3%)

II (15–25)
232 (67.6%)

III (26–35)
60 (17.5%)

IV (> 35)
50 (14.6%)

P-value

Gender 0.085

Male 297 (86.6%) 0 (0.0%) 201 (58.6%) 53 (15.5%) 43 (12.5%)

Female 46 (13.4%) 1 (0.3%) 31 (9.0%) 7 (2.0%) 7 (2.0%)

Age, mean ± SD (years) 64.8 ± 13.1 33.0 ± 0.0 60.8 ± 41.2 74.6 ± 6.2 72.3 ± 14.4 0.012

BMI, mean ± SD (kg/m2) 28.7 ± 5.3 28.1 ± 0.0 29.2 ± 5.4 26.8 ± 5.4 28.7 ± 5.3 0.034

ASA class 0.001

I + II 316 (92.1%) 1 (0.3%) 222 (64.7%) 53(15.5%) 40 (11.7%)

≥ III 27 (7.9%) 0 (0.0%) 10 (2.9%) 7 (2.0%) 10 (2.9%)

Clinical cancer stage <0.001

0 209 (60.9%) 1 (0.3%) 152 (44.3%) 36 (10.5%) 20 (5.8%)

I 75 (21.9%) 0 (0.0%) 53 (15.5%) 15 (4.4%) 7 (2.0%)

II 21 (6.1%) 0 (0.0%) 10 (2.9%) 3 (0.9%) 8 (2.3%)

III 2 (0.6%) 0 (0.0%) 0 (0.0%) 1 (0.3%) 1 (0.3%)

IV 20 (5.8%) 0 (0.0%) 6 (1.7%) 1 (0.3%) 13 (3.8%)

Previous intravesical 
treatment

129 (37.6%) 0 (0.0%) 92 (26.8%) 18 (5.2%) 19 (5.5%) 0.475

Previous radiotherapy 2 (0.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 2 (0.6%) 0.008

30-day complications 8 (2.3%) 0 (0.0%) 6 (1.7%) 1 (0.3%) 1 (0.3%) 0.973

All-cause mortality 21 (6.6%) 0 (0.0%) 4 (1.3%) 3 (0.9%) 14 (4.4%) <0.001

Readmission 13 (3.8%) 0 (0.0%) 9 (2.6%) 3 (0.9%)1 1 (0.3%) 0.611

Preoperative hemoglobin, 
mean ± SD (g/dL)

14.6 ± 7.7 11.0 ± 0.0 15.3 ± 9.1 13.6 ± 1.7 12.9 ± 2.0 0.115

Hypoalbuminemia (<3.5 g/dL) 10 (2.9%) 0 (0.0%) 0 (0.0%) 3 (0.9%) 7 (2.0%) <0.001

EBL, mean ± SD (mL) 11.5 ± 36.2 5.0 ± 0.0 10.6 ± 38.5 9.4 ± 15.2 18.2 ± 42.7 0.550

ASA: American Society of Anesthesiologists; BMI: body mass index; EBL: estimated blood loss; mFI: modified frailty index; RAI: Risk Analysis Index;  
SD: standard deviation.

TABLE 4. 

Postoperative complications 

n (%)

Overall rate 8 (2.3)

Urine retention 2 (0.6)

Pneumonia 1 (0.3)

Hematuria 2 (0.6)

Urinary tract infection 1 (0.3)

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A Prospective Evaluation of Different Frailty Indices in Patients Undergoing Transurethral Resection of Bladder Tumor

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FIGURE 1. 

Receiver operating characteristic (ROC) curves for  
Risk Analysis Index (RAI) with an area under curve 
(AUC) = 0.832, P = 0.049, and modified frailty index 
(mFI) with AUC = 0.672, P = 0.063.

FIGURE 4.

Kaplan-Meier curve for overall survival for bladder 
cancer by Risk Analysis Index (RAI) classification (I-IV); 
log-rank test for survival was significant (P < 0.001). 
Mean follow-up period (months): RAI Class 1, 6.7;  
class 2, 30.5; class 3, 29.3; class 4, 30.7.

FIGURE 3.

Kaplan-Meier curve for overall survival for bladder 
cancer by modified frailty index (mFI) classification; 
log-rank test for survival was significant (P = 0.001). 
Mean follow-up period (months): mFI 0, 30.7; mFI 1, 
26.9; mFI +2, 32.7.

FIGURE 2.

Kaplan-Meier curve for overall survival for bladder 
cancer by invasiveness and stage; log-rank test for 
survival was significant (P < 0.001). Mean follow-up 
period (months): NMIBC, 31.1; MIBC, 21.3; stage IV, 25.6; 
unknown, 38.2. MIBC: muscle-invasive bladder cancer; 
NMIBC: non–muscle-invasive bladder cancer.

Pa
tie

nt
s 

A
liv

e 
(%

)

Follow-up Period (Months)

1.0

0.8

0.6

0.4

0.2

0.0

50.00 100.00 150.00 200.00 250.00.00

Cancer Stages
NMIBC
MIBC (Stage II+III)

Stage IV
Unknown Stage

ROC Curve

1 - Speci�city 

Se
ns

iti
vi

ty

1.0

0.8

0.6

0.4

0.2

0.0 0.2 0.4 0.6 0.8 1.0
0.0

Source of Curve
RAI mFI Reference Line

1.0

0.8

0.6

0.4

0.2

0.0

50.00 100.00 150.00 200.00 250.00.00

mFI
0 1 +2

Pa
tie

nt
s 

A
liv

e 
(%

)

Follow-up Period (Months)

1.0

0.8

0.6

0.4

0.2

0.0

50.00 100.00 150.00 200.00 250.00.00

RAI
I II IVIII

Pa
tie

nt
s 

A
liv

e 
(%

)

Follow-up Period (Months)

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Clavien-Dindo grade ≥ 3 at 30 and 90 days postopera-
tively had significantly higher mFI compared to patients 
with Clavien-Dindo grade < 3—odds ratio of mFI for 
serious complications within 30 days was 1.5 (95% CI 
1.1 to 2.1; P = 0.010) and for 90 days was 1.5 (95% CI 1.1 
to 2.1; P = 0.008)[9]. Another study that assessed frailty 
among 2679 bladder cancer patients who underwent 
radical cystectomy concluded that mFI can identify 
those patients at greatest risk for severe complications 
and mortality. When stratified at a cutoff of mFI > 2, 
the overall complication rate was not different (61.7% vs. 
58.3%; P = 0.1), but mFI ≥ 2 group had a significantly 
higher rate of Clavien-Dindo grade 4 or 5 complica-
tions (14.6% vs. 8.3%; P < 0.001) and overall mortality 
rate (3.5% vs. 1.8%; P = 0.01) in the 30-day postoperative 
period[11–13]. 

Our results in the context of TURBT are consistent 
with these prior studies in the context of radical cystec-
tomy. However, because of the low number of compli-
cations in our TURBT cohort, there was no association 
between frailty and postoperative complications. Our 
study showed that the prevalence of frailty in patients 
with MIBC was higher than in patients with NMIBC, 
hence the higher mortality rate after TURBT. Therefore, 
a different workflow for TURBT in patients with suspi-
cious MIBC might be needed, where a senior urologist 
might be involved early on in these cases intraopera-
tively and define the goal of the procedure, which may 
involve resection of minimum tissue to establish diag-
nosis, without resecting the whole intravesical tumor, or 
considering computed tomography (CT)-guided biopsy 
to establish diagnosis[14]. Recently, there has been 
heightened interest in incorporating magnetic resonance 
imaging (MRI) in the staging of bladder cancer, as such 
preliminary data from the BladderPath trial showed that 
it might be feasible to direct patients with possible MIBC 
to multiparametric MRI (mpMRI) for staging instead of 
TURBT[15].

It is noteworthy that the 30-day overall mortality 
rate in our cohort was higher than the observed rate in 
the National Surgical Quality Improvement Program 
database[16]. This might be explained by several factors 
such as our institutional database being able to capture 
death more accurately than complications and readmis-
sions to other hospitals and the fact that large numbers 
of patients in this cohort were operated during the first 
wave of COVID-19. 

There are few studies in the literature that use frailty 
indices prospectively in perioperative planning and 
management, and even fewer studies examining bladder 

cancer surgical therapies specifically[3–5]. This is the 
first prospective study that examined the prevalence 
of frailty in bladder cancer patients who underwent 
TURBT and used two different tools to assess frailty. In 
this study, RAI was better than mFI in predicting 30-day 
mortality rates post-TURBT. 

Preoperative counseling of bladder cancer patients 
before TURBT usually entails the anticipated oncolog-
ical outcomes, procedural comorbidities, as well as the 
need for second-look TURBT in high-grade tumors 
or in instances of inadequate pathology for complete 
staging[17]. However, surgeons might face challenges 
using tools such as different postoperative risk calcula-
tors, as these calculators use complex formulas requir-
ing extensive clinical history documentation that might 
limit their applicability during clinical encounters. On 
the other hand, the RAI score is a simple tool that can 
be rapidly computed by urologists without delaying the 
patient encounter[18]. 

There are several limitations to our study including 
a small sample size and lack of data on tumor size and 
characteristics. Complications were collected prospec-
tively using our institutional database; however, we 
cannot exclude the possibility that other complications 
were missed, as some patients may have sought urgent 
help in other centers. The low number of complications 
observed in this cohort affected to the ability to study the 
correlation between frailty and postoperative complica-
tions. Other frailty measures such as hand grip using 
manometry were not used in this study due logistical 
and funding issues. In addition, this data was collected 
during the first wave of the COVID-19 pandemic, 
and we cannot exclude the influence of COVID-19 on 
the mortality rate. Finally, we cannot exclude referral 
bias to our center. In order to better predict complica-
tion rates, larger, well-designed multicenter studies are 
needed to prospectively examine the efficacy of frailty 
indices preoperatively in diverse patient categories 
and for different therapies. Nevertheless, despite these 
limitations, our study represents a robust cross-sectional 
analysis that correlates preoperative frailty to important 
30-day postoperative outcomes

Conclusion
Frailty, as measured by Risk Analysis Index, is an 
independent predictor of adverse early mortality in 
patients undergoing TURBT. Preoperative frailty 
assessment may improve risk stratification and patient 
counseling prior to surgery.

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194 SIUJ  •  Volume 4, Number 3  •  May 2023 SIUJ.ORG

 ORIGINAL RESEARCH

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