Dataset Information

Clinical features and predictive biomarkers for bladder cancer in patients with type 2 diabetes presenting with haematuria.

ABSTRACT:

Aims

To identify clinical features and protein biomarkers associated with bladder cancer (BC) in individuals with type 2 diabetes mellitus presenting with haematuria.

Materials and methods

Data collected from the Haematuria Biomarker (HaBio) study was used in this analysis. A matched sub-cohort of patients with type 2 diabetes and patients without diabetes was created based on age, sex, and BC diagnosis, using approximately a 1:2 fixed ratio. Randox Biochip Array Technology and ELISA were applied for measurement of 66 candidate serum and urine protein biomarkers. Hazard ratios and 95% confidence intervals were estimated by chi-squared and Wilcoxon rank sum test for clinical features and candidate protein biomarkers. Diagnostic protein biomarker models were identified using Lasso-based binominal regression analysis.

Results

There was no difference in BC grade, stage, and severity between individuals with type 2 diabetes and matched controls. Incidence of chronic kidney disease (CKD) was significantly higher in patients with type 2 diabetes (p = 0.008), and CKD was significantly associated with BC in patients with type 2 diabetes (p = 0.032). A biomarker model, incorporating two serum (monocyte chemoattractant protein 1 and vascular endothelial growth factor) and three urine (interleukin 6, cytokeratin 18, and cytokeratin 8) proteins, predicted incidence of BC with an Area Under the Curve (AUC) of 0.84 in individuals with type 2 diabetes. In people without diabetes, the AUC was 0.66.

Conclusions

We demonstrate the potential clinical utility of a biomarker panel, which includes proteins related to BC pathogenesis and type 2 diabetes, for monitoring risk of BC in patients with type 2 diabetes. Earlier urology referral of patients with type 2 diabetes will improve outcomes for these patients.

Trial registration

http://www.isrctn.com/ISRCTN25823942.

SUBMITTER: Tonry CL

PROVIDER: S-EPMC9542076 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Clinical features and predictive biomarkers for bladder cancer in patients with type 2 diabetes presenting with haematuria.

Tonry Claire L CL Evans Raymond M RM Ruddock Mark W MW Duggan Brian B McCloskey Oonagh O Maxwell Alexander P AP O'Rourke Declan D Boyd Ruth E RE Watt Joanne J Reid Cherith N CN Curry David J DJ Stevenson Michael M Young Margaret K MK Jamison Catherine S CS Gallagher Joe J Fitzgerald Stephen P SP Lamont John J Watson Chris J CJ

Diabetes/metabolism research and reviews 20220522 6

<h4>Aims</h4>To identify clinical features and protein biomarkers associated with bladder cancer (BC) in individuals with type 2 diabetes mellitus presenting with haematuria.<h4>Materials and methods</h4>Data collected from the Haematuria Biomarker (HaBio) study was used in this analysis. A matched sub-cohort of patients with type 2 diabetes and patients without diabetes was created based on age, sex, and BC diagnosis, using approximately a 1:2 fixed ratio. Randox Biochip Array Technology and EL ...[more]

PMID: 35578575

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Project description:IntroductionHaematuria is a common red flag symptom of urinary tract cancer. Bladder cancer (BC) is the most common cancer to present with haematuria. Women presenting with haematuria are often underdiagnosed. Currently, no gender-specific tests are utilized in clinical practice. Considerable healthcare resources are needed to investigate causes of haematuria and this study was set up to help identify markers of BC. The aim of the study was to define biomarker algorithms in haematuria patients using an expanded panel of biomarkers to diagnose BC and investigate if the algorithms are gender-specific.Materials and methodsA total of n=675 patients with a history of haematuria were recruited from Northern Ireland hospitals. Patients were collected on a 2:1 ratio, non-BC (control) n=474: BC n=201. A detailed clinical history, urine and blood samples were collected. Biomarkers, known to be involved in the pathobiology underlying bladder carcinogenesis were investigated. Biomarkers differentially expressed between groups were investigated using Wilcoxon rank sum and linear regression.ResultsBiomarkers were gender specific. Two biomarker-algorithms were identified to triage haematuria patients; male - u_NSE, s_PAI-1/tPA, u_midkine, u_NGAL, u_MMP-9/TIMP-1 and s_prolactin (u=urine; s=serum); sensitivity 71.8%, specificity 72.8%; AUROC 0.795; and female urine biomarkers - IL-12p70, IL-13, midkine and clusterin; sensitivity 83.7%, specificity 79.7%; AUROC 0.865. Addition of the clinical variable infection to both algorithms increased both AUROC to 0.822 (DeLong p=0.014) and to 0.923 (DeLong p=0.004) for males and females, respectively. Combining clinical risk factors with biomarker algorithms would enable application of the algorithms to triage haematuria patients.ConclusionUsing gender-specific biomarker algorithms in combination with clinical risks that are associated with BC would allow clinicians to better manage haematuria patients and potentially reduce underdiagnosis in females. In this study, we demonstrate, for the first time, that blood and urine biomarkers are gender-specific when assessing risk of BC in patients who present with blood in their urine. Combining biomarker data with clinical factors could improve triage when referring patients for further investigations.

Project description:ObjectivePatients with type 1 diabetes (T1DM) and type 2 diabetes (T2DM) can present with diabetic ketoacidosis (DKA) as the first manifestation. Differentiating types of newly diagnosed diabetes could provide appropriate long-term management. Therefore, we conducted this study to compare clinical characteristics and outcomes between initially diagnosed type 1 and type 2 diabetes mellitus patients presenting with DKA.Materials and methodsA retrospective study was conducted on adult patients who presented with DKA as the first diagnosis of diabetes in our tertiary hospital between January 2005 and December 2019. Demographic data, precipitating causes, laboratory investigations, treatment, and outcomes were obtained by chart review. The primary outcome was to compare the clinical characteristics of initially diagnosed patients with T1DM and T2DM who presented with DKA.ResultsA total of 100 initially diagnosed diabetic patients who presented with DKA were analyzed (85 T2DM patients and 15 T1DM patients). Patients with T1DM were younger than patients with T2DM (mean age 33 ± 16.2 vs. 51 ± 14.5 years, p value < 0.001). Patients with T2DM had a higher body mass index, family history of diabetes, precipitating factors, plasma glucose, and lower renal function than those with T1DM. There was no difference in resolution time or DKA management between T1DM and T2DM patients. The overall mortality rate of DKA was 4%.ConclusionIn this population, most adult patients who presented with DKA had T2DM. Older age, obesity, a family history of diabetes, and the presence of precipitating factors were strong predictors of T2DM. We can implement the same clinical management for DKA in both T1DM and T2DM patients. However, T2DM patients had longer hospitalization than T1DM patients. After DKA resolution for 12 months, more than half of patients with T2DM could discontinue insulin. Therefore, the accurate classification of the type of diabetes leads to appropriate treatment.

Dataset Information

Clinical features and predictive biomarkers for bladder cancer in patients with type 2 diabetes presenting with haematuria.

Aims

Materials and methods

Results

Conclusions

Trial registration

Publications

Clinical features and predictive biomarkers for bladder cancer in patients with type 2 diabetes presenting with haematuria.

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