Wang Xuelei, Lewis Julia, Appel Lawrence, Cheek DeAnna, Contreras Gabriel, Faulkner Marquetta, Feldman Harold, Gassman Jennifer, Lea Janice, Kopple Joel, Sika Mohammed, Toto Robert, Greene Tom
Cleveland Clinic Foundation, Department of Quantitative Health Sciences, Wb-4, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
J Am Soc Nephrol. 2006 Oct;17(10):2900-9. doi: 10.1681/ASN.2005101106. Epub 2006 Sep 20.
Whereas much research has investigated equations for obtaining estimated GFR (eGFR) from serum creatinine in cross-sectional settings, little attention has been given to validating these equations as outcomes in longitudinal studies of chronic kidney disease. A common objective of chronic kidney disease studies is to identify risk factors for progression, characterized by slope (rate of change over time) or time to event (time until a designated decline in kidney function or ESRD). The relationships of 35 baseline factors with eGFR-based outcomes were compared with the relationships of the same factors with iothalamate GFR (iGFR)-based outcomes in the African American Study of Kidney Disease and Hypertension (AASK; n = 1094). With the use of the AASK equation to calculate eGFR, results were compared between time to halving of eGFR or ESRD and time to halving of iGFR or ESRD (with effect sizes expressed per 1 SD) and between eGFR and iGFR slopes starting 3 mo after randomization. The effects of the baseline factors were similar between the eGFR- and iGFR-based time-to-event outcomes (Pearson R = 0.99, concordance R = 0.98). Small but statistically significant differences (P < 0.05, without adjustment for multiple analyses) were observed for seven of the 35 factors. Agreement between eGFR and iGFR was somewhat weaker, although still relatively high for slope-based outcomes (Pearson R = 0.93, concordance R = 0.92). Effects of covariate adjustment for age, gender, baseline GFR, and urine proteinuria also were similar between the eGFR and iGFR outcomes. Sensitivity analyses including death in the composite time-to-event outcomes or using the Modification of Diet in Renal Disease equation instead of the AASK equation provided similar results. In conclusion, the data from the AASK provide tentative support for use of outcomes that are based on an established eGFR formula using serum creatinine as a surrogate for measured iGFR-based outcomes in analyses of risk factors for the progression of kidney disease.
尽管许多研究在横断面研究中探讨了从血清肌酐获取估计肾小球滤过率（eGFR）的方程，但在慢性肾脏病纵向研究中，将这些方程作为研究结果进行验证的关注较少。慢性肾脏病研究的一个共同目标是确定疾病进展的危险因素，其特征为斜率（随时间的变化率）或事件发生时间（直至肾功能指定下降或终末期肾病的时间）。在非裔美国人肾脏病与高血压研究（AASK；n = 1094）中，比较了35个基线因素与基于eGFR的研究结果之间的关系，以及相同因素与基于碘海醇肾小球滤过率（iGFR）的研究结果之间的关系。使用AASK方程计算eGFR，比较了eGFR或ESRD减半时间与iGFR或ESRD减半时间（效应大小以每1个标准差表示），以及随机分组后3个月开始的eGFR和iGFR斜率。基于eGFR和基于iGFR的事件发生时间结果之间，基线因素的影响相似（Pearson相关系数R = 0.99，一致性相关系数R = 0.98）。在35个因素中的7个因素上观察到了微小但具有统计学意义的差异（P < 0.05，未进行多重分析校正）。eGFR和iGFR之间的一致性稍弱，尽管基于斜率的结果仍然相对较高（Pearson相关系数R = 0.93，一致性相关系数R = 0.92）。eGFR和iGFR结果中，对年龄、性别、基线GFR和尿蛋白进行协变量调整的效果也相似。敏感性分析包括在复合事件发生时间结果中纳入死亡情况，或使用肾脏病膳食改良方程而非AASK方程，结果相似。总之，AASK的数据为在肾脏病进展危险因素分析中，使用基于既定eGFR公式（以血清肌酐作为测量iGFR结果的替代指标）的研究结果提供了初步支持。
