糖尿病患者膀胱癌风险预测:一项推导和验证性研究
Risk prediction of bladder cancer among diabetes patients: a derivation and validation study.
发表日期:2023 Aug 14
作者:
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
来源:
MOLECULAR & CELLULAR PROTEOMICS
摘要:
本研究旨在设计和验证一种临床评分系统,用于预测糖尿病患者膀胱癌的风险,以指导紧急膀胱镜检查评估。从中国人群(2009-2018年)的大型数据库中选择接受膀胱镜检查的糖尿病患者作为研究对象。我们从所有病人中随机抽样形成一个建模队列。使用独立危险因素的调整后的比值比(aORs)设计了一个包含0到5分的风险评分系统,0-2分为“平均风险”(AR),3-5分为“高风险”(HR)。共选取5905名糖尿病患者,其中包括123名膀胱癌患者。建模队列(n=4174)和验证队列(n=1731)的患病率分别为2.2%和1.8%。根据构建的评分系统,建模队列中79.6%的患者被分类为AR组,20.4%的患者被分类为HR组。AR组和HR组的患病率分别为1.57%和4.58%。风险评分包括年龄(18-70岁:0分;>70岁:2分)、男性(1分)、现在或曾经吸烟(1分)、糖尿病持续时间(≥10年:1分)。HR组的患者与AR组相比,患膀胱癌的比例增加3.26倍(95% CI=1.65 to 6.44, p=0.025)。协调统计值为0.72,表明风险评分具备良好的判别能力,可用于筛选高风险个体,提前考虑膀胱镜检查。该风险预测算法可帮助确定膀胱镜检查的紧急程度,从而更有效地利用资源,有助于早期发现确定要转诊的膀胱癌患者。本文受版权保护,版权所有。
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.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).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.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.This article is protected by copyright. All rights reserved.