Diabet Med. 2023 Aug 14:e15199. doi: 10.1111/dme.15199. Online ahead of print.
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 diabetes patients.
METHODS: Diabetes patients who received cystoscopy from a large database in a 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 5,905 diabetes patients, among which 123 patients with BCa were included. The prevalence rate in the derivation (n=4,174) and validation cohorts (n=1,731) was 2.2 and 1.8%. Using the scoring system constructed, 79.6% and 20.4% in the derivation cohort were classified as AR and HR. The prevalence rate in the AR and HR groups was 1.57% and 4.58%. The risk score consisted of age (18-70: 0; >70: 2), male (1), ever/ex-smoker (1), duration of diabetes (≥ 10 years: 1). Individuals in the HR group had 3.26-fold (95% CI=1.65 to 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 patients planned to be referred.
PMID:37577820 | DOI:10.1111/dme.15199
