Maziarz Marlena, Black R Anthony, Fong Christine T, Himmelfarb Jonathan, Chertow Glenn M, Hall Yoshio N
Kidney Research Institute, Department of Medicine, Department of Biostatistics, and.
Biomedical Informatics Consult Team, Institute of Translational Health Sciences, University of Washington, Seattle, Washington; and.
J Am Soc Nephrol. 2015 Jun;26(6):1434-42. doi: 10.1681/ASN.2014060546. Epub 2014 Dec 4.
The capacity of risk prediction to guide management of CKD in underserved health settings is unknown. We conducted a retrospective cohort study of 28,779 adults with nondialysis-requiring CKD who received health care in two large safety net health systems during 1996-2009 and were followed for ESRD through September of 2011. We developed and evaluated the performance of ESRD risk prediction models using recently proposed criteria designed to inform population health approaches to disease management: proportion of cases followed and proportion that needs to be followed. Overall, 1730 persons progressed to ESRD during follow-up (median follow-up=6.6 years). ESRD risk for time frames up to 5 years was highly concentrated among relatively few individuals. A predictive model using five common variables (age, sex, race, eGFR, and dipstick proteinuria) performed similarly to more complex models incorporating extensive sociodemographic and clinical data. Using this model, 80% of individuals who eventually developed ESRD were among the 5% of cohort members at the highest estimated risk for ESRD at 1 year. Similarly, a program that followed 8% and 13% of individuals at the highest ESRD risk would have included 80% of those who eventually progressed to ESRD at 3 and 5 years, respectively. In this underserved health setting, a simple five-variable model accurately predicts most cases of ESRD that develop within 5 years. Applying risk prediction using a population health approach may improve CKD surveillance and management of vulnerable groups by directing resources to a small subpopulation at highest risk for progressing to ESRD.
在医疗服务不足的环境中,风险预测指导慢性肾脏病(CKD)管理的能力尚不清楚。我们进行了一项回顾性队列研究,研究对象为28779名非透析依赖的CKD成人患者,他们在1996年至2009年期间在两个大型安全网医疗系统接受医疗服务,并随访至2011年9月以观察终末期肾病(ESRD)情况。我们使用最近提出的旨在为疾病管理的人群健康方法提供信息的标准,开发并评估了ESRD风险预测模型的性能:随访病例比例和需要随访的比例。总体而言,1730人在随访期间进展为ESRD(中位随访时间 = 6.6年)。长达5年时间框架内的ESRD风险高度集中在相对较少的个体中。一个使用五个常见变量(年龄、性别、种族、估算肾小球滤过率[eGFR]和试纸法蛋白尿)的预测模型与纳入广泛社会人口统计学和临床数据的更复杂模型表现相似。使用该模型,最终发展为ESRD的个体中,80%在1年时处于ESRD估计风险最高的队列成员的5%之中。同样,一个对ESRD风险最高的8%和13%的个体进行随访的项目,将分别在3年和5年时纳入最终进展为ESRD的个体的80%。在这个医疗服务不足的环境中,一个简单的五变量模型能够准确预测5年内发生的大多数ESRD病例。采用人群健康方法应用风险预测,可能通过将资源导向进展为ESRD风险最高的一小部分亚人群,改善CKD监测和弱势群体的管理。