Impact of Equation Choice on Models Assessing the Association Between Lipoprotein(a) and Estimated Glomerular Filtration Rate in Adult Patients Without Chronic Kidney Disease.

Background

In our recent research, we established a strong and statistically significant association between the highest quartile of lipoprotein(a) [Lp(a)] and mildly reduced estimated glomerular filtration rate (eGFR). Comparisons with similar studies were hindered by varying Lp(a) analytical methods and different eGFR equations. We analyzed how replacing the diagnostic standard CKD-EPI 2021 equation with alternatives (CKD-EPI 2009, CKD-MDRD, CKD-EKFC) affects predictive models under comprehensive demographic and clinical confounder adjustments.

Methods

We calculated eGFR for 310 adults using the four equations. Creatinine and Lp(a) were measured via IFCC-recommended methods. The cohort was divided into a main (eGFR 60-80 mL/min/1.73 m2) and a control group (eGFR > 80 mL/min/1.73 m2). Multivariable logistic regression and Area Under the Curve (AUC) metrics evaluated model performance.

Results

Alternative equations systematically underestimated eGFR, artificially increasing the reduced filtration group. After full multivariable adjustment, only CKD-EPI 2021 preserved the independent association between the highest Lp(a) quartile and mildly decreased eGFR (OR = 2.65, p = 0.008), achieving an AUC of 0.732. Conversely, CKD-EPI 2009 lost significance; CKD-MDRD exhibited mathematical instability from control group depletion, and EKFC showed severe over-adjustment when demographic covariates were included.

Conclusions

Older equations and the age-embedded EKFC equation may influence regression models, potentially obscuring the true biomarker associations. CKD-EPI 2021 demonstrated the highest precision, successfully isolating physiological aging and suggesting an independent association between high Lp(a) and mildly reduced eGFR, irrespective of metabolic and vascular confounders.