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Methods for Characterizing Differences in Longitudinal Glomerular Filtration Rate Changes Between Children With Glomerular Chronic Kidney Disease and Those With Nonglomerular Chronic Kidney Disease

机译:表征肾小球慢性肾脏病患儿和非肾小球慢性肾脏病患儿纵向肾小球滤过率变化差异的方法

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摘要

The rate of decline of glomerular filtration rate (GFR) in children with chronic kidney disease (CKD) can vary, even among those with similar diagnoses. Classic regression methods applied to the log-transformed GFR (i.e., lognormal) quantify only rigid shifts in a given outcome. The generalized gamma distribution offers an alternative approach for characterizing the heterogeneity of effect of an exposure on a positive, continuous outcome. Using directly measured GFR longitudinally assessed between 2005 and 2010 in 529 children enrolled in the Chronic Kidney Disease in Children Study, the authors characterized the effect of glomerular CKD versus nonglomerular CKD diagnoses on the outcome, measured as the annualized GFR ratio. Relative percentiles were used to characterize the heterogeneity of effect of CKD diagnosis across the distribution of the outcome. The rigid shift assumed by the classic mixed models failed to capture the fact that the greatest difference between the glomerular and nonglomerular diagnosis’ annualized GFR ratios was in children who exhibited the fastest GFR declines. Although this difference was enhanced in children with an initial GFR level of 45 mL/minute/1.73 m2 or less, the effect of diagnosis on outcome was not significantly modified by level. Generalized gamma models captured heterogeneity of effect more richly and provided a better fit to the data than did conventional lognormal models.
机译:慢性肾脏病(CKD)儿童的肾小球滤过率(GFR)下降率可能有所不同,即使在诊断相似的儿童中也是如此。应用于对数转换后的GFR(即对数正态)的经典回归方法仅量化了给定结果中的刚性变化。广义伽玛分布提供了另一种方法来表征暴露对阳性连续结果的影响的异质性。作者使用2005年至2010年之间纵向评估的529例儿童慢性肾脏病儿童研究中的GFR进行了纵向评估,作者确定了肾小球CKD与非肾小球CKD诊断对结局的影响,以年化GFR比衡量。相对百分位用于表征结果分布中CKD诊断效果的异质性。经典混合模型所假定的刚性变化未能反映出肾小球和非肾小球诊断的年化GFR比之间最大的差异是GFR下降最快的儿童。虽然最初的GFR水平为45 mL / min / 1.73 m 2 或更低的儿童,这种差异有所增强,但诊断对结局的影响并未明显改变。与常规对数正态模型相比,广义伽玛模型更丰富地捕获了效果的异质性,并提供了更好的数据拟合性。

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