Literature DB >> 36093535

Incidence, prognostic factors and survival in bladder cancer patients: a population-based study.

Shun-De Wang1,2, Cheng-Guo Ge2, Jun-Yong Zhang2.   

Abstract

Background: The aim of this study was to investigate the incidence, epidemiologic characteristics, prognostic factors and survival of patients with bladder cancer.
Methods: Bladder cancer patients diagnosed between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox proportional hazards regression analyses were used to identify the independent prognostic factors for overall survival. Kaplan-Meier survival analysis and nomogram analysis were constructed based on the identified independent prognostic factors.
Results: A total of 95,329 eligible bladder cancer patients were included in this study. Eight independent risk factors, including age, histologic type, race, tumor, node and metastasis (TNM) stage, American Joint Committee on Cancer (AJCC) stage, surgery, tumor metastasis and summary stage, were recognized by using multivariate logistic regression models. By comprising these factors, a predictive nomogram was constructed to predict the 1-, 3-, and 5-year overall survival possibilities. The concordance index and calibration curve showed that the nomogram had robust and accurate performance. Conclusions: Bladder cancer is the most common cancer of the urinary system, but the overall incidence has been decreasing yearly since 1992. Our results demonstrate eight factors significantly associated with overall survival in bladder cancer patients. Based on these factors, we established and validated a nomogram, which has the potential to provide an individualized prediction of overall survival in patients with bladder cancer. 2022 Translational Cancer Research. All rights reserved.

Entities:  

Keywords:  Bladder cancer (BC); Surveillance, Epidemiology, and End Results (SEER); multivariate; overall survival (OS)

Year:  2022        PMID: 36093535      PMCID: PMC9459577          DOI: 10.21037/tcr-22-46

Source DB:  PubMed          Journal:  Transl Cancer Res        ISSN: 2218-676X            Impact factor:   0.496


Introduction

Bladder cancer (BC) is the 10th most common cancer in the world and the 13th leading cause of cancer-related death (1), with nearly 549,000 new cases and 200,000 deaths each year (2). Previous studies have shown that multiple factors, such as sex, age, smoking, and race, can affect the survival probability of BC (3-5). Study shows that the incidence of BC is three to four times higher in men than in women (6). The incidence of BC increases with age: more than 90% of patients are over 55 years old, with an average age of approximately 73 years (1). Whites are more likely to develop BC than people of other races (7). Survival probability is a prediction of the likelihood that a patient will continue to survive (8-10). Because each survival probability is a prediction based on finite conditions, the survival probability can only be used as a reference, and the survival probability cannot provide a definite answer. The purpose of this study was to understand the incidence, prognostic factors, and survival trends in BC patients. This study was based on a larger population derived from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute. We also characterized independent prognostic factors associated with BC and sought to build prognostic nomograms that could assist clinicians in evaluating prognosis. We present the following article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-46/rc).

Methods

Data source

The data for this study were obtained retrospectively from the SEER database. To extract data, select cases, and define variables, SEER*Stat (version 8.3.9.2) was used. The case listing was created using the incidence-SEER 18 Registers Research Data + Hurricane Katrina Impacted Louisiana Cases, Nov 2018 Sub (1975-2016 varying). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Patient identification

Patients diagnosed with malignant BC by histology between 2010 and 2015 were included in this study. shows the inclusion and exclusion criteria for this study.
Table 1

Inclusion and exclusion criteria of population selection and classification

Inclusion criteria
   Patients diagnosed with malignant bladder cancer
   The histologic type of patients should be available
   The survival time and vital status should be available
   Clinicopathological information for the age at diagnosis, race, surgery, tumor stage and other baseline information should be available
Exclusion criteria
   Patients with bladder cancer found during an autopsy or on a death certificate
   Unknown ethnicity
   Unknown survival time
   Unknown AJCC-stage
   Unknown summary stage
   Unknown surgical status
   Unknown TNM-T/N/M stage
   Unknown age
   Unknown vital status

AJCC, American Joint Committee on Cancer; TNM, tumor, node, metastasis.

AJCC, American Joint Committee on Cancer; TNM, tumor, node, metastasis. Variables from the selected cohort included sex, race, age at diagnosis, histologic type, TNM-T, TNM-N, TNM-M, AJCC stage, surgery of primary site, bone metastasis, brain metastasis, liver metastasis, lung metastasis, summary stage, survival months, and vital status. The main endpoint was overall survival (OS). The age at diagnosis was divided into five subgroups: <50, 51–60, 61–70, 71–80, and >80 years. We classified the histological type into transitional cell carcinoma, squamous cell carcinoma, adenocarcinoma, neuroendocrine carcinoma and other epithelial tumors of the bladder using the ICD-0-3 morphological code.

Statistical analysis

The incidence rates of BC were calculated per 100,000 person-years and age-adjusted to the 2,000 US Standard Population [19 age groups, United States Bureau of the Census, Current Population Reports, Publication 25-1130 (Census P25-1130)] using SEER*Stat (version 8.3.9.2). Annual percentage changes (APCs) were calculated using the weighted least squares method. Estimated OS was calculated with the Kaplan-Meier method and compared by the log-rank test. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors associated with OS in BC patients. All statistical analyses were performed in R (Version 4.1.1, R Foundation; R packages: rms, survival, survminer, ggplot2). Statistical significance was set at a two-sided P value <0.05.

Nomogram construction

R 4.1.1 was used to construct a nomogram based on the results of multivariate analysis of the Cox proportional hazards model. The maximum score for each variable was set to 100. We also built calibration curves to identify whether the predicted and actual survival were in agreement.

Results

Baseline characteristics

A total of 95,329 eligible BC patients from 2010 to 2015 were included in this study. shows the comparison of baseline characteristics and chi-square test results for patients with BC clustered by age. Of all patients, 4,139 (4.30%) patients were aged less than 51 years, 12,536 (13.20%) patients were aged 51–60 years, 25,979 (27.30%) patients were aged 61–70 years, 28,868 (30.20%) patients were aged 71–80 years and 23,807 (25.00%) patients were aged over 80 years. According to the chi-square test, sex (P<0.001), race (P<0.001), diagnosis year (P<0.001), histologic type (P<0.001), TNM-T (P<0.001), TNM-N (P<0.001), TNM-M (P<0.001), AJCC stage (P<0.001), surgery (P<0.001), bone metastasis (P<0.001), brain metastasis (P=0.045), and summary stage (P<0.001) were all factors that were significantly different among age groups, except for liver metastasis (P=0.851) and lung metastasis (P=0.101).
Table 2

Baseline characteristics

FactorsALL, n (%)Age group, n (%)P value
<51 years51–60 years61–70 years71–80 years>80 years
Total95,329 (100.00)4,139 (4.30)12,536 (13.20)25,979 (27.30)28,868 (30.20)23,807 (25.00)
Gender<0.001
   Male73,059 (76.64)3,072 (4.20)96,006 (13.10)20,236 (27.80)22,515 (30.80)17,630 (24.10)
   Female22,270 (23.36)1,067 (4.80)2,930 (13.20)5,743 (25.80)6,353 (28.50)6,177 (27.70)
Race<0.001
   White85,577 (89.77)3,593 (4.20)10,951 (12.70)23,260 (27.20)26,071 (30.50)21,702 (25.40)
   Black5,443 (5.71)342 (6.30)987 (18.10)1,615 (29.70)1,497 (27.50)1,002 (18.40)
   API3,997 (4.19)178 (4.50)534 (13.40)1,014 (25.40)1,222 (30.50)1,049 (26.20)
   AIAN312 (0.33)26 (8.30)64 (20.50)90 (28.80)78 (25.00)54 (17.30)
Diagnosis year<0.001
   201015,561 (16.32)740 (4.80)2,113 (13.50)4,174 (26.80)4,667 (30.00)3,867 (24.90)
   201115,543 (16.30)731 (4.70)2,034 (13.10)4,214 (27.10)4,636 (29.80)3,928 (25.30)
   201215,994 (16.78)720 (4.50)2,068 (12.90)4,336 (27.10)4,828 (30.20)4,042 (25.30)
   201315,822 (16.60)674 (4.30)2,027 (12.80)4,418 (27.90)4,724 (29.90)3,979 (25.10)
   201416,174 (16.97)631 (3.90)2,195 (13.60)4,395 (27.20)4,916 (30.30)4,037 (25.00)
   201516,235 (17.03)643 (4.00)2,099 (12.90)4,442 (27.30)5,097 (31.40)3,954 (24.40)
Histologic type<0.001
   Tcc91,963 (96.47)3,900 (4.20)12,049 (13.10)25,147 (27.30)27,915 (30.40)22,952 (25.00)
   Scc1,265 (1.33)82 (6.50)182 (14.40)279 (22.10)360 (28.50)362 (28.50)
   Ac 845 (0.89)121 (14.30)174 (20.60)223 (26.40)185 (21.90)142 (16.80)
   Nec788 (0.83)20 (2.50)86 (10.90)209 (26.60)247 (31.30)226 (28.70)
   Oet468 (0.49)16 (3.40)45 (9.60)121 (25.90)161 (34.40)125 (26.70)
TNM-T<0.001
   Ta46,421 (48.70)2,444 (5.30)6,579 (14.10)13,257 (28.60)13,991 (30.10)10,150 (21.90)
   Tis4,052 (4.25)131 (3.20)468 (11.50)1,103 (27.20)1,350 (33.40)100 (24.70)
   T01 (0.00)0 (0.00)0 (0.00)1 (0.00)0 (0.00)0 (0.00)
   T123,616 (24.77)776 (3.30)2,774 (11.70)6,161 (26.10)7,248 (30.70)6,657 (28.20)
   T214,382 (15.09)427 (3.00)1,664 (11.50)3,478 (24.20)4,154 (28.90)4,659 (32.40)
   T33,977 (4.17)219 (5.50)607 (15.30)1,192 (30.00)1,252 (31.40)707 (17.80)
   T42,880 (3.02)142 (4.90)444 (15.40)787 (27.30)873 (30.30)634 (22.00)
TNM-N<0.001
   N091,377 (95.85)3,875 (4.20)11,751 (12.90)24,772 (27.10)27,756 (30.40)23,223 (25.40)
   N11,544 (1.62)105 (6.80)295 (19.10)487 (31.50)426 (27.60)231 (15.00)
   N21,938 (2.03)129 (6.70)400 (20.60)569 (29.30)544 (28.10)296 (15.30)
   N3470 (0.49)60 (6.40)90 (19.10)151 (32.10)142 (30.20)57 (12.10)
TNM-M<0.001
   M092,977 (97.53)4,016 (4.30)12,170 (13.10)25,376 (27.30)28,161 (30.30)23,254 (25.00)
   M12,352 (2.47)123 (5.20)366 (15.60)603 (25.60)707 (30.10)553 (23.50)
AJCC stage<0.001
   Stage 0a46,421 (48.70)2,444 (5.30)6,579 (14.10)13,257 (28.60)13,991 (30.10)10,150 (21.90)
   Stage 0is4,052 (4.25)131 (3.20)468 (11.60)1,103 (27.20)1,350 (33.30)1,000 (24.70)
   Stage I23,054 (24.18)737 (3.20)2,675 (11.60)6,025 (26.10)7,093 (30.80)6,524 (28.30)
   Stage II12,275 (12.88)335 (2.70)1,309 (10.70)2,886 (23.60)3,541 (28.80)4,204 (34.20)
   Stage III3,896 (4.09)164 (4.20)501 (12.90)1,080 (27.70)1,253 (32.20)898 (23.00)
   Stage IV5,631 (5.91)328 (5.80)1,007 (17.80)1,628 (28.90)1,640 (29.20)1,031 (18.30)
Surgery<0.001
   TURBT84,713 (88.86)3,523 (4.20)10,656 (12.60)22,477 (26.50)25,568 (30.20)22,489 (26.50)
   PC1,265 (1.33)95 (7.50)202 (16.00)327 (25.80)359 (28.40)282 (22.30)
   RC9,351 (9.81)521 (5.60)1,678 (17.80)3,175 (34.00)2,941 (31.50)1,036 (11.10)
Metastasis
   Bone94,491 (99.12)4096 (4.30)12,378 (13.10)25,760 (27.30)28,625 (30.30)23,632 (25.00)<0.001
   Brain95,266 (99.93)4135 (4.30)12,525 (13.10)25,954 (27.30)28,853 (30.30)23,799 (25.00)0.045
   Liver94,852 (99.50)4115 (4.30)12,468 (13.10)25,856 (27.30)28,752 (30.30)23,688 (25.00)0.851
   Lung94,552 (99.18)4,100 (4.30)12,419 (13.10)25,798 (27.30)28,627 (30.30)13,608 (25.00)0.101
Summary stage<0.001
   In situ49,517 (51.94)2,535 (5.10)6,932 (14.00)14,111 (28.50)15,056 (30.40)10,883 (22.00)
   Localized35,803 (37.56)1,094 (3.10)4,047 (11.30)9,065 (25.30)10,767 (30.10)10,830 (30.20)
   Regional6,967 (7.31)343 (4.90)1,064 (15.30)1,992 (28.60)2,140 (30.70)1,428 (20.50)
   Distant3,042 (3.19)167 (5.50)493 (16.20)811 (26.60)905 (29.80)666 (21.90)

AIAN, American Indian/Alaska Native; API, Asian or Pacific Islander; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors.

AIAN, American Indian/Alaska Native; API, Asian or Pacific Islander; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors. Males accounted for approximately 70% of the patients in each group. Patients over 61 years old accounted for approximately 80% of the sample in each group. Based on TNM stage, summary stage and AJCC-stage system, most patients were in the early stage of cancer (in situ, localized, AJCC-stage 0a, AJCC-stage 0is, AJCC-stage I, AJCC-stage II, TaN0M0 and T1N0M0); therefore, more than 80% of patients underwent transurethral resection of bladder tumor (TURBT). According to histological type, transitional cell carcinoma accounted for more than 90% of patients in each group. The incidence of brain metastases was the lowest compared to other distant organ metastases.

Cox proportional hazards model

Univariate and multivariate risk analyses of OS are shown in . Univariate risk analyses revealed that sex, age, histologic type, race, TNM stage, AJCC stage, surgery, tumor metastasis and summary stage were significant prognostic factors of OS. Variables in univariate risk analyses with a P value of less than 0.01 were included in multivariate risk analyses. The results indicated that age, histologic type, race, TNM stage, AJCC stage, surgery, tumor metastasis and summary stage were independent prognostic factors for OS.
Table 3

Cox proportional-danger model analysis of bladder cancer patients

FactorsUnivariate analysisMultivariate analysis
HR (95% CI)P valueHR (95% CI)P value
Gender<0.001
   MaleReferenceReference
   Female1.070 (1.043–1.098)<0.0010.981 (0.956–1.007)0.154
Age<0.001
   0–50 yearsReferenceReference
   51–60 years1.391 (1.268–1.527)<0.0011.330 (1.212–1.460)<0.001
   61–70 years1.738 (1.593–1.897)<0.0011.734 (1.589–1.892)<0.001
   71–80 years2.830 (2.597–3.083)<0.0012.748 (2.612–3.102)<0.001
   >81 years5.814 (5.340–6.330)<0.0015.693 (5.226–6.202)<0.001
Histologic type<0.001
   TccReferenceReference
   Scc3.056 (2.849–3.278)<0.0011.821 (1.696–1.956)<0.001
   Ac 1.804 (1.638–1.987)<0.0011.097 (0.994–1.211)0.067
   Nec3.718 (3.420–4.043)<0.0011.244 (1.142–1.356)<0.001
   Oet1.548 (1.352–1.773)<0.0011.201 (1.046–1.379)0.009
Race<0.001
   WhiteReferenceReference
   Black1.327 (1.270–1.386)<0.0011.270 (1.215–1.328)<0.001
   API0.900 (0.849–0.955)<0.0010.844 (0.796–0.896)<0.001
   AIAN1.170 (0.970–1.413)0.1011.117 (0.926–1.349)0.248
TNM-T<0.001
   TaReferenceReference
   Tis1.405 (1.319–1.497)<0.0011.255 (1.166–1.351)<0.001
   T0*
   T11.965 (1.907–2.025)<0.0015.729 (4.571–7.181)<0.001
   T24.949 (4.805–5.098)<0.0016.156 (4.988–7.599)<0.001
   T34.784 (4.574–5.004)<0.0018.059 (6.520–9.962)<0.001
   T48.483 (8.098–8.888)<0.0019.524 (7.703–11.774)<0.001
TNM-N<0.001
   N0ReferenceReference
   N13.400 (3.197–3.615)<0.0010.953 (0.849–1.030)0.172
   N24.876 (4.632–5.134)<0.0011.269 (1.163–1.384)<0.001
   N35.368 (4.850–5.941)<0.0011.063 (0.939–1.204)0.332
TNM-M<0.001
   M0ReferenceReference
   M18.824 (8.438–9.228)<0.0010.996 (0.884–1.123)0.951
  AJCC stage<0.001
   Stage 0aReferenceReference
   Stage 0is1.405 (1.319–1.497)<0.001
   Stage I1.872 (1.815–1.930)<0.0010.257 (0.214–0.307)<0.001
   Stage II4.434 (4.297–4.575)<0.0010.640 (0.546–0.750)<0.001
   Stage III4.569 (4.364–4.783)<0.0010.564 (0.509–0.625)<0.001
   Stage IV9.549 (9.209–9.902)<0.001
Surgery<0.001
   TURBTReferenceReference
   PC1.201 (1.097–1.315)<0.0010.519 (0.472–0.571)<0.001
   RC1.595 (1.544–1.648)<0.0010.528 (0.507–0.551)<0.001
Tumor metastasis
   Bone<0.001
    NoReferenceReference
    Yes9.716 (9.047–10.435)<0.0011.448 (1.324–1.584)<0.001
   Brain<0.001
    NoReferenceReference
    Yes12.727 (9.936–16.301)<0.0011.930 (1.501–2.482)<0.001
   Liver<0.001
    NoReferenceReference
    Yes12.104 (11.298–13.619)<0.0011.638 (1.473–1.821)<0.001
   Lung<0.001
    NoReferenceReference
    Yes9.466 (8.788–10.196)<0.0011.193 (1.088–1.307)<0.001
Summary stage<0.001
   In situReferenceReference
   Localized2.492 (2.429–2.557)<0.0011.212 (1.059–1.387)0.005
   Regional4.972 (4.797–5.153)<0.0011.412 (1.175–1.697)<0.001
   Distant14.457 (13.843–15.098)<0.0012.057 (1.653–2.558)<0.001

*, there was only one T0 stage patient, the result is not informative. AIAN, American Indian/Alaska Native; API, Asian or Pacific Islander; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy.

*, there was only one T0 stage patient, the result is not informative. AIAN, American Indian/Alaska Native; API, Asian or Pacific Islander; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy.

Incidence of BC

The trend in the incidence of BC has decreased since 1992, with an APC of −0.59 (95% CI: −0.79 to −0.39, P<0.05) (). This trend was more remarkable among male patients (), white patients (), patients aged less than 70 years () and patients with in situ and localized tumor stage (). The overall annual age-adjusted incidences of BC from 1992 to 2018 were 20.7, 20.2, 20.1, 20.2, 20.5, 20.6, 20.7, 20.7, 0.8, 20.3, 20.9, 21, 20.9, 20.4, 20.9, 20.3, 19.9, 20.4, 19.4, 19.6, 19, 19, 18.7, 18.5, 17.8, and 16.8/100,000 persons, respectively.
Figure 1

Annual age-adjusted incidence of bladder cancer decreased from 1992 to 2018 (A), and stratified by sex (B), race (C), age (D), and tumor stage (E).

Annual age-adjusted incidence of bladder cancer decreased from 1992 to 2018 (A), and stratified by sex (B), race (C), age (D), and tumor stage (E).

Kaplan-Meier survival analysis

To evaluate the impact of different factors on the OS of BC patients, Kaplan-Meier survival analysis was performed in all patients. As shown in , the overall survival decreases significantly as the age of diagnosis increases. shows the survival probability of patients of four races except for black patients was > 50% at 80 months. Asian or Pacific Islander patients had the highest survival probability, followed by white and American Indian/Alaska Native patients. shows that once the summary stage starts to progress, the overall survival decreases significantly. AJCC stage IV had the worst survival probability, and the survival probability for AJCC stage 0a-I patients was >50% at 80 months (). Neuroendocrine carcinoma of the bladder has the worst survival probability, while transitional cell carcinoma of the bladder has the best survival probability (). shows that patients who underwent radical cystectomy had the worst survival probability, which was associated with the fact that most of the patients in this group were in an advanced stage of cancer.
Figure 2

Kaplan-Meier survival curves for overall patients with bladder cancer in different conditions: age (A), race (B), summary stage (C), AJCC stage (D), histologic type (E), surgery (F). API, Asian or Pacific Islander; AIAN, American Indian/Alaska Native; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy.

Kaplan-Meier survival curves for overall patients with bladder cancer in different conditions: age (A), race (B), summary stage (C), AJCC stage (D), histologic type (E), surgery (F). API, Asian or Pacific Islander; AIAN, American Indian/Alaska Native; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy. shows the survival probability for patients with five histologic types of BC (transitional cell carcinoma, squamous cell carcinoma, adenocarcinoma, neuroendocrine carcinoma and other epithelial tumors of the bladder) after undergoing different surgical approaches. Patients with transitional cell carcinoma have the highest survival probability after TURBT, in contrast to BC patients with the other four histologic types. Patients with squamous cell carcinoma have the highest survival probability after partial cystectomy, which is similar to adenocarcinoma.
Figure 3

Kaplan-Meier survival curves for different histologic types in different surgeries of bladder cancer patients. Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy.

Kaplan-Meier survival curves for different histologic types in different surgeries of bladder cancer patients. Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy. shows that neuroendocrine carcinoma of the bladder had the worst survival probability among male patients, but among female patients, both neuroendocrine carcinoma of the bladder and squamous cell carcinoma of the bladder had a lower survival probability. shows significant differences in survival probability among the four ethnic groups of BC patients, and this was more remarkable in female patients.
Figure 4

Kaplan–Meier survival for different histologic types (A) and races (B) in bladder cancer patients by sex. API, Asian or Pacific Islander; AIAN, American Indian/Alaska Native; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors.

Kaplan–Meier survival for different histologic types (A) and races (B) in bladder cancer patients by sex. API, Asian or Pacific Islander; AIAN, American Indian/Alaska Native; Tcc, transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors.

Prognostic nomogram

A nomogram was constructed based on the Cox proportional hazard model to predict the 1-, 3-, and 5-year OS in BC patients (). Each subgroup variable was assigned a corresponding score to construct this nomogram. A scoring system was used to assign a score from 0 to 100 to each subgroup variable based on its contribution. These scores are added to the registered variables to generate a total score for the bottom scale, which was then converted to predict the corresponding OS.
Figure 5

Nomogram of prediction for 1-, 3- and 5-year overall survival of bladder cancer. API, Asian or Pacific Islander; AIAN, American Indian/Alaska Native; Tcc, Transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy.

Nomogram of prediction for 1-, 3- and 5-year overall survival of bladder cancer. API, Asian or Pacific Islander; AIAN, American Indian/Alaska Native; Tcc, Transitional cell carcinoma; Scc, squamous cell carcinoma; Ac, adenocarcinoma; Nec, neuroendocrine carcinoma; Oet, other epithelial tumors; TURBT, transurethral resection of bladder tumor; PC, partial cystectomy; RC, radical cystectomy.

Validation of the nomogram

The calibration curve was used to validate the model’s ability to predict 1-, 3-, and 5-year OS in BC patients. As shown in , a perfect correlation between nomogram prediction and observed outcomes demonstrated the great reliability of our nomogram. The C-index is 0.768, which is greater than 0.7. These results suggested that the newly established nomogram was considerably accurate.
Figure 6

Calibration curves of the nomogram-predicted 1- (A), 3- (B) and 5-year (C) overall survival.

Calibration curves of the nomogram-predicted 1- (A), 3- (B) and 5-year (C) overall survival.

Discussion

BC is the ninth most common cancer in the world and one of the most common cancers of the urinary system (2,11). Although our results showed that the overall incidence of BC showed a downward trend, there was still an increasing trend in patients aged >80 years. Despite the fact that we now have more treatment options available for BC patients, including molecular targeted drugs, neoadjuvant chemotherapy, and immunotherapy, older patients do not seem to benefit from these promising therapies. In this study, we obtained data from 95,329 BC patients, and by the Kaplan-Meier method, we found that the OS of BC patients not only had racial differences but was also related to TNM stage, histological type, and surgery. Meanwhile, a subgroup analysis was performed and showed that OS differed by histological type in patients of different sexes or after different surgical procedures and that OS also differed between female patients of different races. We found that the number of men with BC was much higher than the number of women, and most patients were aged over 50 years. Most BCs were transitional cell carcinoma. Several studies have previously been performed to illustrate why BC is more likely to occur in men (2,12-15): one reason is the interaction of estrogen, androgens and the liver, and another reason is related to smoking, which increases the risk of BC because more men smoke than women (13,16). In addition, older patients are susceptible to BC due to degeneration of the body’s immune system, leading to an increase in cancer incidence year by year (17-19). Additionally, the decline in bladder function and the development of benign prostatic hyperplasia in male patients as they aged leads to chronic urinary retention (20), which increases exposure to carcinogens and increases the risk of developing BC. We used univariate and multivariate risk analyses to evaluate various risk factors that have a significant impact on OS in patients with BC. Multivariate analyses showed that all factors, except sex and TNM-M stage, had a significant effect on overall survival in bladder cancer, which is consistent with published studies (6,13,21). OS was lowest for patients who underwent radical cystectomy due to the higher tumor stage (T2–4), with or without lymph nodes or distant metastases, with approximately 76% of patients being older than 60 years. In contrast, patients who underwent TURBT had the best OS; although more than 80% of this group of patients were older than 60 years, these patients tended to have an earlier tumor stage. Our findings showed that the risk of death increased with age and tumor stage (TNM stage, AJCC stage). A review of the literature shows that as patients age, immunity and physical function decline, which exacerbates the impact of the disease on patients to some extent (22-24). In addition, as patients age, exposure to carcinogens may increase (24), which may affect patient OS. As tumor grading increases, the chances of tumor cell spreading and metastasis increase, which makes treatment more difficult. The nomogram is widely used to predict OS in oncology patients (25-28). It has been proven that multivariate prediction models predict cancer outcomes more accurately than the cancer stage system (29,30). Our nomogram incorporates more risk factors, which to some extent increases its personalized prediction, and decisions about follow-up and surveillance of cancer patients are made based on risk. Patients predicted to be at higher risk need to receive more intensive follow-up and more accurate treatments, and the inclusion of more risk factors allows us to make more reliable predictions. The C-index of the nomogram was 0.768, indicating that the nomogram is an accurate model for predicting OS. There are certain shortcomings in this study. First, the SEER database includes less than 30% of the U.S. population, indicating that the scope of the database is not large enough. For example, due to the limited number of patients with TNM-T0 stage, we lacked additional data to analyses the survival differences in patients with T0 stage. Therefore, our survival analyze for this period did not provide additional results. Second, we did not include other factors that may affect OS, such as economic conditions (31), marital status (32), genetic factors (33-35), posttreatment care status (36,37), and patient physical status. The inclusion of these factors would further make the nomogram more accurate. Finally, chemotherapy, radiotherapy and other novel therapy strategies may affect the OS of BC patients. However, some of the SEER data do not provide this important information. Therefore, more studies are needed to identify risk factors that affect OS in BC patients.

Conclusions

Our study showed that the overall incidence of BC has been decreasing year by year since 1992. Meanwhile, we found that age, race, histologic type, tumor stage, and organ metastasis were independent predictors of OS in BC patients. To better predict the 1-, 3-, and 5-year OS in BC patients, we constructed a nomogram based on specific characteristics. The C-index was satisfactory in internal validation. This prediction tool will help physicians assess individualized survival predictions and could provide better surveillance strategies for BC patients. The article’s supplementary files as
  37 in total

1.  Cancer statistics, 2019.

Authors:  Rebecca L Siegel; Kimberly D Miller; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2019-01-08       Impact factor: 508.702

2.  Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study.

Authors:  D Dong; M-J Fang; L Tang; X-H Shan; J-B Gao; F Giganti; R-P Wang; X Chen; X-X Wang; D Palumbo; J Fu; W-C Li; J Li; L-Z Zhong; F De Cobelli; J-F Ji; Z-Y Liu; J Tian
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Review 3.  Bladder Cancer Incidence and Mortality: A Global Overview and Recent Trends.

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Journal:  Eur Urol       Date:  2016-06-28       Impact factor: 20.096

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Authors:  Liliana Vartolomei; Mihai Dorin Vartolomei; Shahrokh F Shariat
Journal:  Eur Urol Focus       Date:  2019-12-11

Review 5.  Gender and Bladder Cancer: A Collaborative Review of Etiology, Biology, and Outcomes.

Authors:  Jakub Dobruch; Siamak Daneshmand; Margit Fisch; Yair Lotan; Aidan P Noon; Matthew J Resnick; Shahrokh F Shariat; Alexandre R Zlotta; Stephen A Boorjian
Journal:  Eur Urol       Date:  2015-09-04       Impact factor: 20.096

6.  An overview of patients with urothelial bladder cancer over the past two decades: a Surveillance, Epidemiology, and End Results (SEER) study.

Authors:  Yan Zang; Xiao Li; Yifei Cheng; Feng Qi; Ningli Yang
Journal:  Ann Transl Med       Date:  2020-12

7.  Clinical benefits of a multivariate prediction model for bladder cancer: a decision analytic approach.

Authors:  Andrew J Vickers; Angel M Cronin; Michael W Kattan; Mithat Gonen; Peter T Scardino; Matthew I Milowsky; Guido Dalbagni; Bernard H Bochner
Journal:  Cancer       Date:  2009-12-01       Impact factor: 6.860

8.  Ethnicity and survival in bladder cancer: a population-based study based on the SEER database.

Authors:  Wei Fang; Zhi-Yan Yang; Ting-Yu Chen; Xian-Feng Shen; Chao Zhang
Journal:  J Transl Med       Date:  2020-03-30       Impact factor: 5.531

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Authors:  Kalyan Saginala; Adam Barsouk; John Sukumar Aluru; Prashanth Rawla; Sandeep Anand Padala; Alexander Barsouk
Journal:  Med Sci (Basel)       Date:  2020-03-13

10.  Development and Validation of Autophagy-Related Gene Signature and Nomogram for Predicting Survival in Oral Squamous Cell Carcinoma.

Authors:  Chen Hou; Hongshi Cai; Yue Zhu; Shuojin Huang; Fan Song; Jinsong Hou
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