Development of Risk Prediction Equations for Incident Chronic Kidney Disease
Development of Risk Prediction Equations for Incident Chronic Kidney Disease
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DOI：
10.1001/jama.2019.17379
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发表时间：
2019-12-03
影响因子：
120.7
通讯作者：
Woodward, Mark
中科院分区：
文献类型：
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作者：
Nelson, Robert G.;Grams, Morgan E.;Woodward, Mark
重要性早期识别个体发展为慢性肾脏病（CKD）的高风险可以通过加强监测和更好地管理潜在的健康状况来改善临床护理。目的开发评估工具来识别个体发展为CKD的高风险，通过降低估计肾小球滤过率（eGFR）来定义。CKD预后联盟的34个多国队列的个体水平数据分析，包括来自28个国家的5222711名个体。数据收集自1970年4月至2017年1月。进行了2阶段分析，首先对每项研究进行单独分析，然后使用加权平均值进行总体总结。由于糖尿病状态的临床变量通常存在差异，因此分别为糖尿病患者和非糖尿病患者开发了模型。还在9个外部队列中测试了辨别力和校准（n = 2 253 540）.暴露人口统计学和临床因素.主要结果和测量事件eGFR小于60 mL/min/1.73 m（2）.结果在4 441 084名无糖尿病的参与者中（平均年龄，54岁，38%为女性），在平均4.2年的随访期间，发生了660856例（14.9%）eGFR降低的事件。在781627例糖尿病患者（平均年龄62岁，13%为女性）中，313646例（40%）发生在平均3.9年的随访期间。eGFR降低的5年风险方程包括年龄、性别、人种/种族、eGFR、心血管疾病史、吸烟史、高血压、体重指数和白蛋白尿浓度。对于糖尿病患者，模型还包括糖尿病药物，血红蛋白A（1c）以及两者之间的相互作用。风险方程的5年预测概率的中位C统计量在无糖尿病队列中为0.845（四分位距[IQR]，0.789-0.890），在糖尿病队列中为0.801（IQR，0.750-0.819）。校准分析显示，13个研究人群中有9个（69%）的观测风险与预测风险的斜率在0.80至1.25之间。在9个外部验证队列的18个研究人群中，歧视相似;校准显示18例中有16例（89%）从34个多国队列的500多万人中开发的预测慢性肾脏疾病发病风险的方程显示出高的区分度和变量校准，不同的人群。需要进一步研究以确定是否使用这些方程来识别处于发展慢性肾脏疾病风险中的个体将改善临床护理和患者结局。
IMPORTANCE Early identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions.OBJECTIVE To develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR).DESIGN, SETTING, AND PARTICIPANTS Individual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540).EXPOSURES Demographic and clinical factors.MAIN OUTCOMES AND MEASURES Incident eGFR of less than 60 mL/min/1.73 m(2).RESULTS Among 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A(1c), and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25.CONCLUSIONS AND RELEVANCE Equations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.