Enhancing eGFRcr-cys Accuracy in Extreme Body Mass Index Groups

We read with great interest the recent JASN article by Russel et al.1 titled “Obesity, Underweight, and Accuracy of eGFR Using Cystatin C and Creatinine in a Northern European Population.” The authors found that indexed creatinine–cystatin C eGFR (eGFRcr-cys) outperforms creatinine or cystatin C–based equations in individuals with low or high body mass index (BMI). This finding has significant implications for clinical decision-making, particularly in drug dosing and treatment eligibility. We commend the authors for their rigorous methodology and nuanced exploration of the role of indexing in eGFR accuracy, but we thought there was something to discuss. First, the study appropriately acknowledges that muscle mass and adiposity influence eGFR accuracy. Yet, despite this, no direct measurements of lean body mass or fat mass were incorporated. BMI is a crude surrogate for body composition; individuals with identical BMIs may exhibit vastly different muscle-to-fat ratios. For instance, sarcopenic obesity or high muscle mass in underweight individuals could confound the relationship between BMI and eGFR bias.2 Second, the study treats all eGFRcr-cys equations uniformly, but methodologies varied: CKD Epidemiology Collaboration uses a validated equation, whereas The European Kidney Function Consortium and the revised Lund-Malmö and Caucasian and Asian pediatric and adult participants use a simple average of creatinine-based eGFR and cystatin C–based eGFR. This inconsistency in combining biomarkers may introduce unmeasured bias.3 A sensitivity analysis comparing validated with averaged equations would clarify if methodological differences affect accuracy across BMI strata. Third, when assessing eGFR performance across BMI categories, covariates (e.g., diabetes, cardiovascular disease) were excluded to avoid overadjustment. However, comorbidities like diabetes disproportionately affect obese individuals and may independently alter creatinine or cystatin C metabolism.4 Adjusting for key confounders within BMI subgroups could isolate BMI-specific effects more precisely. In conclusion, Russel et al.1 provide valuable insights into GFR estimation across BMI extremes, while future studies incorporating direct body composition measurements, standardized eGFRcr-cys methodologies, and comorbidity-adjusted analyses within BMI subgroups would significantly strengthen the clinical applicability of these findings across diverse populations and care settings.