Complex Disease and Genome Epidemiology Branch, Department of Public Health, Graduate School of Public Health, Seoul National University, Seoul, Korea.
Department of Epidemiology, Graduate School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, Korea.
Investig Clin Urol. 2020 Mar;61(2):188-199. doi: 10.4111/icu.2020.61.2.188. Epub 2020 Feb 12.
Well-validated risk prediction models help to stratify individuals on the basis of their disease risks and to guide health care professionals in decision-making. The incidence of nephrolithiasis has been increasing in Korea. Racial differences in the distribution of and risk for nephrolithiasis have been reported in Asia but no population-specific nephrolithiasis models have been developed. We aimed to develop a simplified nephrolithiasis prediction model for the Korean population by using data from general medical practice.
This was a prospective, population-based cohort study in Korea. A total of 497,701 participants from the National Health Insurance Service-National Sample Cohort (NHIS-NSC) were enrolled from 2002 to 2010. A Cox proportional hazards model was used.
During a median follow-up time of 8.5 years (range, 2.0-8.9 years) and among 497,701 participants, there were 15,783 cases (3.2%) of nephrolithiasis. The parsimonious model included age, sex, income grade, alcohol consumption, body mass index, total cholesterol, fasting blood glucose, and medical history of diseases. The Harrell's C-statistic was 0.806 (95% confidence interval [CI], 0.790-0.821) and 0.805 (95% CI, 0.782-0.827) in the derivation and validation cohorts, respectively.
The results of the present study imply that nephrolithiasis risk can be predicted by use of data from general medical practice and based on predictors that clinicians and individuals from the general population are likely to know. This model comprises modifiable risk factors and can be used to identify those at higher risk who can modify their lifestyle to lower their risk for nephrolithiasis. This study also offers an opportunity for external validation or updating of the model through the incorporation of other risk predictors in other settings.
经过良好验证的风险预测模型有助于根据个体的疾病风险对其进行分层，并为医疗保健专业人员的决策提供指导。韩国的肾结石发病率一直在上升。亚洲已经报道了肾结石的分布和风险存在种族差异，但尚未开发出针对特定人群的肾结石模型。我们旨在使用来自普通医疗实践的数据为韩国人群开发简化的肾结石预测模型。
这是一项在韩国进行的前瞻性、基于人群的队列研究。共有 497701 名来自国家健康保险服务-国家样本队列（NHIS-NSC）的参与者于 2002 年至 2010 年入组。采用 Cox 比例风险模型。
在中位随访时间为 8.5 年（范围，2.0-8.9 年）的 497701 名参与者中，有 15783 例（3.2%）发生肾结石。简约模型包括年龄、性别、收入等级、饮酒、体重指数、总胆固醇、空腹血糖和疾病史。Harrell's C 统计量在推导队列和验证队列中分别为 0.806（95%置信区间[CI]，0.790-0.821）和 0.805（95% CI，0.782-0.827）。
本研究结果表明，肾结石风险可以通过使用普通医疗实践的数据和临床医生及普通人群可能了解的预测因素来预测。该模型包含可改变的危险因素，可用于识别风险较高的人群，以便其改变生活方式以降低肾结石风险。本研究还为通过在其他环境中纳入其他风险预测因素来对该模型进行外部验证或更新提供了机会。
