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van den Brandt PA. Diabetes and the risk of bladder cancer subtypes in men and women: results from the Netherlands Cohort Study. Eur J Epidemiol 2024; 39:379-391. [PMID: 38492115 PMCID: PMC11101497 DOI: 10.1007/s10654-024-01100-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/10/2024] [Indexed: 03/18/2024]
Abstract
Meta-analyses have shown modest positive associations between diabetes mellitus (DM) and bladder cancer risk, but results are heterogeneous. This might be due to lack of distinction between bladder cancer subtypes, between sexes, and possibly between Type 2 and Type 1 DM (T2DM and T1DM). The relationship of T2DM (and secondarily T1DM) characteristics with risk of bladder cancer subtypes (invasive versus noninvasive) was investigated in the Netherlands Cohort Study. In 1986, 120,852 men and women aged 55-69 years provided information on DM and lifestyle data. After 20.3 years of follow-up, multivariable case-cohort analyses were based on 1020 invasive and 1088 noninvasive bladder cancer cases, and 4267 subcohort members with complete data on DM and confounders. While T2DM was not associated with noninvasive bladder cancer, it was statistically significantly associated with invasive bladder cancer risk: the multivariable-adjusted was HR = 1.57 (95% CI 1.04-2.37), comparing participants with T2DM versus without DM. The association was only significant in women, and women showed a stronger association [HR = 2.19 (95% CI 1.10-4.34)] between T2DM and invasive bladder cancer than men [HR = 1.42 (95% CI 0.88-2.30)]; interaction by sex was nonsignificant. Associations were stronger positive in those whose age at diagnosis of T2DM was 55+ years, and in those diagnosed with T2DM less than five years before baseline. T2DM participants using antidiabetic medication had higher invasive bladder cancer risk than those without DM. Exploratory age-sex-adjusted analyses suggested a positive association between T1DM and invasive bladder cancer, but this was based on few cases. These findings suggest that T2DM and possibly T1DM are positively associated with invasive bladder cancer risk.
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Affiliation(s)
- Piet A van den Brandt
- GROW- School for Oncology and Reproduction, Department of Epidemiology, Maastricht University Medical Centre, PO Box 616, 6200 MD, Maastricht, The Netherlands.
- CAPHRI- School for Public Health and Primary Care, Department of Epidemiology, Maastricht University Medical Centre, Maastricht, The Netherlands.
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Xu S, Huang J. Machine learning algorithms predicting bladder cancer associated with diabetes and hypertension: NHANES 2009 to 2018. Medicine (Baltimore) 2024; 103:e36587. [PMID: 38277522 PMCID: PMC10817101 DOI: 10.1097/md.0000000000036587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 11/20/2023] [Indexed: 01/28/2024] Open
Abstract
Bladder cancer is 1 of the 10 most common cancers in the world. However, the relationship between diabetes, hypertension and bladder cancer are still controversial, limited study used machine learning models to predict the development of bladder cancer. This study aimed to explore the association between diabetes, hypertension and bladder cancer, and build predictive models of bladder cancer. A total of 1789 patients from the National Health and Nutrition Examination Survey were enrolled in this study. We examined the association between diabetes, hypertension and bladder cancer using multivariate logistic regression model, after adjusting for confounding factors. Four machine learning models, including extreme gradient boosting (XGBoost), Artificial Neural Networks, Random Forest and Support Vector Machine were compared to predict for bladder cancer. Model performance was assessed by examining the area under the subject operating characteristic curve, accuracy, recall, specificity, precision, and F1 score. The mean age of bladder cancer group was older than that of the non-bladder cancer (74.4 years vs 65.6 years, P < .001), and men were more likely to have bladder cancer. Diabetes was associated with increased risk of bladder cancer (odds ratio = 1.24, 95%confidence interval [95%CI]: 1.17-3.02). The XGBoost model was the best algorithm for predicting bladder cancer; an accuracy and kappa value was 0.978 with 95%CI:0.976 to 0.986 and 0.01 with 95%CI:0.01 to 0.52, respectively. The sensitivity was 0.90 (95%CI:0.74-0.97) and the area under the curve was 0.78. These results suggested that diabetes is associated with risk of bladder cancer, and XGBoost model was the best algorithm to predict bladder cancer.
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Affiliation(s)
- Siying Xu
- Department of Urology, Wuhan Fourth Hospital, Wuhan, China
| | - Jing Huang
- Department of Urology, Wuhan Fourth Hospital, Wuhan, China
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Jubber I, Ong S, Bukavina L, Black PC, Compérat E, Kamat AM, Kiemeney L, Lawrentschuk N, Lerner SP, Meeks JJ, Moch H, Necchi A, Panebianco V, Sridhar SS, Znaor A, Catto JWF, Cumberbatch MG. Epidemiology of Bladder Cancer in 2023: A Systematic Review of Risk Factors. Eur Urol 2023; 84:176-190. [PMID: 37198015 DOI: 10.1016/j.eururo.2023.03.029] [Citation(s) in RCA: 133] [Impact Index Per Article: 66.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/01/2023] [Accepted: 03/24/2023] [Indexed: 05/19/2023]
Abstract
CONTEXT Bladder cancer (BC) is common worldwide and poses a significant public health challenge. External risk factors and the wider exposome (totality of exposure from external and internal factors) contribute significantly to the development of BC. Therefore, establishing a clear understanding of these risk factors is the key to prevention. OBJECTIVE To perform an up-to-date systematic review of BC's epidemiology and external risk factors. EVIDENCE ACQUISITION Two reviewers (I.J. and S.O.) performed a systematic review using PubMed and Embase in January 2022 and updated it in September 2022. The search was restricted to 4 yr since our previous review in 2018. EVIDENCE SYNTHESIS Our search identified 5177 articles and a total of 349 full-text manuscripts. GLOBOCAN data from 2020 revealed an incidence of 573 000 new BC cases and 213 000 deaths worldwide in 2020. The 5-yr prevalence worldwide in 2020 was 1 721 000. Tobacco smoking and occupational exposures (aromatic amines and polycyclic aromatic hydrocarbons) are the most substantial risk factors. In addition, correlative evidence exists for several risk factors, including specific dietary factors, imbalanced microbiome, gene-environment risk factor interactions, diesel exhaust emission exposure, and pelvic radiotherapy. CONCLUSIONS We present a contemporary overview of the epidemiology of BC and the current evidence for BC risk factors. Smoking and specific occupational exposures are the most established risk factors. There is emerging evidence for specific dietary factors, imbalanced microbiome, gene-external risk factor interactions, diesel exhaust emission exposure, and pelvic radiotherapy. Further high-quality evidence is required to confirm initial findings and further understand cancer prevention. PATIENT SUMMARY Bladder cancer is common, and the most substantial risk factors are smoking and workplace exposure to suspected carcinogens. On-going research to identify avoidable risk factors could reduce the number of people who get bladder cancer.
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Affiliation(s)
- Ibrahim Jubber
- Academic Urology Unit, University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
| | - Sean Ong
- EJ Whitten Foundation Prostate Cancer Research Centre, Epworth HealthCare, Melbourne, Australia; Department of Surgery, University of Melbourne, Melbourne, Australia
| | | | - Peter C Black
- Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Eva Compérat
- Department of Pathology, Medical University of Vienna, Vienna, Austria
| | - Ashish M Kamat
- Department of Urology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Nathan Lawrentschuk
- EJ Whitten Foundation Prostate Cancer Research Centre, Epworth HealthCare, Melbourne, Australia; Department of Surgery, University of Melbourne, Melbourne, Australia; Department of Surgery, Royal Melbourne Hospital, Melbourne, Australia
| | - Seth P Lerner
- Scott Department of Urology, Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Joshua J Meeks
- Departments of Urology and Biochemistry, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
| | - Holger Moch
- Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Andrea Necchi
- Department of Medical Oncology, IRCCS San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Valeria Panebianco
- Department of Radiological Sciences, Oncology, and Pathology, Sapienza University of Rome, Rome, Italy
| | - Srikala S Sridhar
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Ariana Znaor
- Cancer Surveillance Branch, International Agency for Research on Cancer, Lyon, France
| | - James W F Catto
- Academic Urology Unit, University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Marcus G Cumberbatch
- Academic Urology Unit, University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
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