Assessing bias in GFR estimating equations: improper GFR stratification can yield misleading results.

Background: Assessing bias (estimated – measured) is key to evaluating glomerular filtration rate (GFR). Stratification by subgroups can indicate where equations perform differently. However, there is a fallacy in the assessment of two instruments (e.g., eGFR and mGFR) when stratifying on the level...

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Published in:Pediatric Nephrology Vol. 39; no. 7; pp. 2139 - 2146
Main Authors: Ng, Derek K., Muñoz, Alvaro
Format: equations & formulas research tables/charts Journal Article
Published: Springer Nature Jul2024
Online Access:View this record in EBSCOhost
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      dt: Jul2024
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00467-024-06318-4
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        atl: Assessing bias in GFR estimating equations: improper GFR stratification can yield misleading results.
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          Ng, Derek K.
          Muñoz, Alvaro
        affil: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Room E7642, 21205, Baltimore, MD, USA
      sug:
        subj:
          Glomerular Filtration Rate Evaluation
          Renal Insufficiency, Chronic Diagnosis
          Bias (Research)
          Pediatrics
          Human
          Female
          Child
          Adolescence
          Models, Statistical Methods
          Kidney Physiology
          Creatinine Blood
          Kidney Function Tests
          Descriptive Statistics
          Comparative Studies
          Confidence Intervals
          Funding Source
          Child: 6-12 years
          Adolescent: 13-18 years
          Female
      ab: Background: Assessing bias (estimated – measured) is key to evaluating glomerular filtration rate (GFR). Stratification by subgroups can indicate where equations perform differently. However, there is a fallacy in the assessment of two instruments (e.g., eGFR and mGFR) when stratifying on the level of only one of those instruments. Here, we present statistical aspects of the problem and a solution for GFR stratification along with an empirical investigation using data from the CKiD study. Methods: Compared and contrasted biases (eGFR relative to mGFR) with 95% confidence intervals within strata of mGFR only, eGFR only, and the average of mGFR and eGFR using data from the Chronic Kidney Disease in Children (CKiD) study. Results: A total of 304 participants contributed 843 GFR studies with a mean mGFR of 48.46 (SD = 22.72) and mean eGFR of 48.67 (SD = 22.32) and correlation of 0.904. Despite strong agreement, eGFR significantly overestimated mGFR when mGFR < 30 (+ 6.2%; 95%CI + 2.9%, + 9.7%) and significantly underestimated when mGFR > 90 (–12.2%; 95%CI − 17.3%, − 7.0%). Significant biases in opposite direction were present when stratifying by eGFR only. In contrast, when stratifying by the average of eGFR and mGFR, biases were not significant (+ 1.3% and − 1.0%, respectively) congruent with strong agreement. Conclusions: Stratifying by either mGFR or eGFR only to assess eGFR biases is ubiquitous but can lead to inappropriate inference due to intrinsic statistical issues that we characterize and empirically illustrate using data from the CKiD study. Using the average of eGFR and mGFR is recommended for valid inferences in evaluations of eGFR biases.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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