Grassi, M

In the original publication [...]

Abstract Background An accurate and reliable measurement of glomerular filtration rate (GFR) is essential to monitor for rejection and disease progression post-kidney transplantation. Measured GFR (mGFR) is the current gold standard. However, it has scarce availability at many centers and is labor intensive. Newer estimated GFR (eGFR) methods containing cystatin-C and/or other biomarkers have not been clinically validated in a post-transplant cohort. In this study, we evaluated a new NMR-based GFR (GFRNMR) equation that contains serum creatinine, cystatin C, myoinositol, and valine in post-kidney transplant recipients in a clinical routine setting. Methods Venipuncture for serum collection was performed immediately prior to mGFR measurement with urinary iothalamate clearance in 67 post-kidney transplant recipients. Serum was stored at 4°C and measured by NMR no later than four days after collection. eGFR was assessed using the following equations: i) GFRNMR, ii) CKD-EPI2021Cr (creatinine) and iii) CKD-EPI2021Cr,Cys (creatinine and cystatin-C). Bias was calculated as “eGFR—mGFR” for all equations. The Bootstrap method was employed to assess pairwise significance levels between bias distributions interquartile ranges (IQR), and P-value correction was determined with the Benjamini & Hochberg method. Precision, which was defined as percentage of samples within ±30% and ±15% from the mGFR value (P30 and P15, respectively), was calculated for each equation. Pairwise comparisons were made using McNemar’s Chi-squared and Benjamini & Hochberg correction. Precision was defined as the proportion of eGFR values concordant with mGFR values by CKD clinical stage. Results P30 for GFRNMR was significantly higher than CKD-EPI2021 Cr,Cys (97% vs 84%, P < 0.01) and higher than CKD-EPI2021 Cr (88%, P = 0.08). Similarly, P15 for GFRNMR was 63%; higher than for CKD-EPI2021 Cr (54%, P = 0.35) and CKD-EPI2021 Cr,Cys (51%, P = 0.19). Bias IQR for GFRNMR was 9.5 mL/min/1.73 m2 (median bias 2.0 mL/min/1.73 m2); significantly smaller than for CKD-EPI2021 Cr (Bias IQR 15.55 mL/min/1.73 m2, P < 0.05; median bias 1.47 mL/min/1.73 m2), and smaller than CKD-EPI2021 Cr,Cys (Bias IQR 14.4 mL/min/1.73 m2, P = 0.09; median bias 2.3 mL/min/1.73 m2). A broad range of medications such as immune modulators, and comorbidities such as hypertension, thyroid dysfunction, and coronary artery disease, did not interfere with GFRNMR performance. Conclusion NMR-based eGFR was less biased, more precise, and more accurate compared to creatinine and cystatin-C CKD-EPI eGFR equations in a post-kidney transplant setting. These findings suggest GFRNMR may more closely resemble mGFR in post-transplant patients and warrants further study on its potential use to improve clinical management in this patient group.

An accurate estimate of glomerular filtration rate (eGFR) is essential for proper clinical management, especially in patients with kidney dysfunction. This prospective observational study evaluated the real-world performance of the nuclear magnetic resonance (NMR)-based GFRNMR equation, which combines creatinine, cystatin C, valine, and myo-inositol with age and sex. We compared GFRNMR performance to that of the 2021 CKD-EPI creatinine and creatinine-cystatin C equations (CKD-EPI2021Cr and CKD-EPI2021CrCys), using 115 fresh routine samples of patients scheduled for urinary iothalamate clearance measurement (mGFR). Median bias to mGFR of the three eGFR equations was comparably low, ranging from 0.4 to 2.0 mL/min/1.73 m2. GFRNMR outperformed the 2021 CKD-EPI equations in terms of precision (interquartile range to mGFR of 10.5 vs. 17.9 mL/min/1.73 m2 for GFRNMR vs. CKD-EPI2021CrCys; p = 0.01) and accuracy (P15, P20, and P30 of 66.1% vs. 48.7% [p = 0.007], 80.0% vs. 60.0% [p < 0.001] and 95.7% vs. 86.1% [p = 0.006], respectively, for GFRNMR vs. CKD-EPI2021CrCys). Clinical parameters such as etiology, comorbidities, or medications did not significantly alter the performance of the three eGFR equations. Altogether, this study confirmed the utility of GFRNMR for accurate GFR estimation, and its potential value in routine clinical practice for improved medical care.

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived ‘metabolite constellation’ (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (−1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. −6.0 (−7.0; −5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.