Risk prediction of bladder cancer among person with diabetes: A derivation and validation study
Martin C. S. Wong, Junjie Huang, Harry H. X. Wang, Sarah T. Y. Yau, Jeremy Y. C. Teoh, Peter K. F. Chiu, Chi‐Fai Ng, Eman Yee‐Man Leung- Endocrinology
- Endocrinology, Diabetes and Metabolism
- Internal Medicine
Abstract
Aims
This study aimed to devise and validate a clinical scoring system for risk prediction of bladder cancer to guide urgent cystoscopy evaluation among people with diabetes.
Methods
People with diabetes who received cystoscopy from a large database in the Chinese population (2009–2018). We recruited a derivation cohort based on random sampling from 70% of all individuals. We used the adjusted odds ratios (aORs) for independent risk factors to devise a risk score, ranging from 0 to 5: 0–2 ‘average risk’ (AR) and 3–5 ‘high risk’ (HR).
Results
A total of 5905 people with diabetes, among whom 123 people with BCa were included. The prevalence rate in the derivation (n = 4174) and validation cohorts (n = 1731) was 2.2% and 1.8% respectively. Using the scoring system constructed, 79.6% and 20.4% in the derivation cohort were classified as AR and HR respectively. The prevalence rate in the AR and HR groups was 1.57% and 4.58% respectively. The risk score consisted of age (18–70: 0; >70: 2), male sex (1), ever/ex‐smoker (1) and duration of diabetes (≥10 years: 1). Individuals in the HR group had 3.26‐fold (95% CI = 1.65–6.44, p = 0.025) increased prevalence of bladder than the AR group. The concordance (c‐) statistics was 0.72, implying a good discriminatory capability of the risk score to stratify high‐risk individuals who should consider earlier cystoscopy.
Conclusions
The risk prediction algorithm may inform urgency of cystoscopy appointments, thus allowing a more efficient use of resources and contributing to early detection of BCa among people planned to be referred.