Internal Medicine, University of New Mexico, Albuquerque, NM, 87131, Mexico.
David Geffen School of Medicine, UCLA, Los Angeles, CA, 90024, USA.
Sci Rep. 2018 Oct 26;8(1):15900. doi: 10.1038/s41598-018-34233-w.
Chronic Kidney Disease (CKD), is highly prevalent in the United States. Epidemiological systems for surveillance of CKD rely on data that are based solely on the NHANES survey, which does not include many patients with the most severe and less frequent forms of CKD. We investigated the feasibility of estimating CKD prevalence from the large-scale community disease detection Kidney Early Evaluation and Program (KEEP, n = 127,149). We adopted methodologies from the field of web surveys to address the self-selection bias inherent in KEEP. Primary outcomes studied were CKD Stage 3-5 (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m, and CKD Stage 4-5 (eGFR <30 mL/min/1.73 m). The unweighted prevalence of Stage 4-5 CKD was higher in KEEP (1.00%, 95%CI: 0.94-1.05%) than in NHANES (0.51%, 95% CI: 0.43-0.59%). Application of a selection model that used variables related to demographics, recruitment and socio-economic factors resulted in estimates similar to NHANES (0.55%, 95% CI: 0.50-0.60%). Weighted prevalence of Stages 3-5 CKD in KEEP was 6.45% (95% CI: 5.70-7.28%) compared to 6.73% (95% CI: 6.30-7.19%) for NHANES. Application of methodologies that address the self-selection bias in the KEEP program may allow the use of this large, geographically diverse dataset for CKD surveillance.
慢性肾脏病(CKD)在美国的发病率很高。CKD 的流行病学监测系统依赖于仅基于 NHANES 调查的数据,而该调查并未包括许多患有最严重和较少见的 CKD 形式的患者。我们研究了从大规模社区疾病检测 Kidney Early Evaluation and Program (KEEP,n=127149) 中估算 CKD 患病率的可行性。我们采用了网络调查领域的方法,以解决 KEEP 中固有的自我选择偏差。主要研究结果是 CKD 3-5 期(估计肾小球滤过率[eGFR]<60mL/min/1.73m,和 CKD 4-5 期(eGFR<30mL/min/1.73m)。KEEP 中未加权的 4-5 期 CKD 患病率高于 NHANES(1.00%,95%CI:0.94-1.05%)(0.51%,95%CI:0.43-0.59%)。应用一种选择模型,该模型使用与人口统计学、招募和社会经济因素相关的变量,得出的估计值与 NHANES 相似(0.55%,95%CI:0.50-0.60%)。KEEP 中 3-5 期 CKD 的加权患病率为 6.45%(95%CI:5.70-7.28%),而 NHANES 为 6.73%(95%CI:6.30-7.19%)。应用解决 KEEP 计划中自我选择偏差的方法可能允许使用这个大型、地理上多样化的数据集进行 CKD 监测。