Estimation of GFR in children using rescaled beta-trace protein

β-Trace Protein and β2-Microglobulin do not Improve Estimation of Glomerular Filtration Rate in Kidney Transplant Recipients Compared With Creatinine and Cystatin C

BACKGROUND

Reliable estimates of glomerular filtration rate (eGFR) are important for detecting changes in graft function in kidney transplant recipients. Current eGFR equations are based on plasma creatinine and/or cystatin C; however, these are associated with significant bias. This study investigated if equations based on β-trace protein (BTP) and β2-microglobulin (B2M) performed better than the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on creatinine and cystatin C among kidney transplant recipients.

METHODS

We included samples and data from the clinical trial CONTEXT. Glomerular filtration rate (GFR) was measured by plasma clearance of an exogenous marker. The eGFR was calculated using the CKD-EPI equations for estimating GFR from BTP and/or B2M and the 2021 CKD-EPI creatinine and creatinine-cystatin C equations. The GFR estimates were evaluated 3 (n = 82) and 12 (n = 64) months after transplant using mean bias, precision, and accuracy. Furthermore, we analyzed the ability of the equations to correctly classify the direction of changes in measured GFR from 3 to 12 months.

RESULTS

Among the BTP- and B2M-based equations, the combined eGFR-BTP-B2M performed best with respect to precision (SD = 7.64 mL/min/1.73 m2) and accuracy (±10% from measured GFR = 36%). The eGFR-BTP-B2M and the eGFR-creatinine-cystatin C (2021) performed similarly when comparing precision, accuracy, and residuals (P = .481). The BTP- and/or B2M-based equations did not perform better than the eGFR-creatinine-cystatin C (2021) in correctly classifying the direction of changes in measured GFR from 3 to 12 months.

CONCLUSIONS

β-trace protein and/or B2M do not improve the estimation of GFR when compared with creatinine- and cystatin C-based 2021 CKD-EPI equations.

Construct a classification decision tree model to select the optimal equation for estimating glomerular filtration rate and estimate it more accurately

Chronic kidney disease (CKD) has become a worldwide public health problem and accurate assessment of renal function in CKD patients is important for the treatment. Although the glomerular filtration rate (GFR) can accurately evaluate the renal function, the procedure of measurement is complicated. Therefore, endogenous markers are often chosen to estimate GFR indirectly. However, the accuracy of the equations for estimating GFR is not optimistic. To estimate GFR more precisely, we constructed a classification decision tree model to select the most befitting GFR estimation equation for CKD patients. By searching the HIS system of the First Affiliated Hospital of Zhejiang Chinese Medicine University for all CKD patients who visited the hospital from December 1, 2018 to December 1, 2021 and underwent Gate's method of ^99mTc-DTPA renal dynamic imaging to detect GFR, we eventually collected 518 eligible subjects, who were randomly divided into a training set (70%, 362) and a test set (30%, 156). Then, we used the training set data to build a classification decision tree model that would choose the most accurate equation from the four equations of BIS-2, CKD-EPI(CysC), CKD-EPI(Cr-CysC) and Ruijin, and the equation was selected by the model to estimate GFR. Next, we utilized the test set data to verify our tree model, and compared the GFR estimated by the tree model with other 13 equations. Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Bland-Altman plot were used to evaluate the accuracy of the estimates by different methods. A classification decision tree model, including BSA, BMI, 24-hour Urine protein quantity, diabetic nephropathy, age and RASi, was eventually retrieved. In the test set, the RMSE and MAE of GFR estimated by the classification decision tree model were 12.2 and 8.5 respectively, which were lower than other GFR estimation equations. According to Bland-Altman plot of patients in the test set, the eGFR was calculated based on this model and had the smallest degree of variation. We applied the classification decision tree model to select an appropriate GFR estimation equation for CKD patients, and the final GFR estimation was based on the model selection results, which provided us with greater accuracy in GFR estimation.

A Review of Specific Biomarkers of Chronic Renal Injury and Their Potential Application in Nonclinical Safety Assessment Studies

A host of novel renal biomarkers have been developed over the past few decades which have enhanced monitoring of renal disease and drug-induced kidney injury in both preclinical studies and in humans. Since chronic kidney disease (CKD) and acute kidney injury (AKI) share similar underlying mechanisms and the tubulointerstitial compartment has a functional role in the progression of CKD, urinary biomarkers of AKI may provide predictive information in chronic renal disease. Numerous studies have explored whether the recent AKI biomarkers could improve upon the standard clinical biomarkers, estimated glomerular filtration rate (eGFR), and urinary albumin to creatinine ratio, for predicting outcomes in CKD patients. This review is an introduction to alternative assays that can be utilized in chronic (>3 months duration) nonclinical safety studies to provide information on renal dysfunction and to demonstrate specific situations where these assays could be utilized in nonclinical drug development. Novel biomarkers such as symmetrical dimethyl arginine, dickkopf homolog 3, and cystatin C predict chronic renal injury in animals, act as surrogates for GFR, and may predict changes in GFR in patients over time, ultimately providing a bridge from preclinical to clinical renal monitoring.

GFR Estimation Using a Panel of Filtration Markers in Shanghai and Beijing

RATIONALE & OBJECTIVES

Estimated glomerular filtration rate (eGFR) using creatinine and cystatin C (eGFRcr-cys) may be less accurate compared to measured GFR (mGFR) in China than in North America, Europe, and Australia due to variation across regions in their non-GFR determinants. The non-GFR determinants of β2-microglobulin (B2M) and β-trace protein (BTP) differ from those of creatinine and cystatin C. Thus, the average eGFR using all 4 markers (eGFRavg) could be more accurate than eGFRcr-cys in China.

STUDY DESIGN

Diagnostic test study.

SETTING & PARTICIPANTS

1,066 participants in Shanghai and Beijing with creatinine and cystatin C and 666 participants with all 4 filtration markers.

TESTS COMPARED

Index tests were previously developed equations for eGFR using creatinine, cystatin C, B2M, and BTP and combinations. The reference test was mGFR using plasma clearance of iohexol. We compared the performance of eGFRavg to eGFRcr-cys using the proportion of participants with errors in eGFR >30% of mGFR (1 - P30) and root mean square error (RMSE) of the regression of eGFR on mGFR on the logarithmic scale. We also compared classification and reclassification of mGFR categories using eGFRavg compared to eGFRcr-cys.

OUTCOMES

Accuracy was significantly better for eGFRavg (1 - P30 of 10.4% and RMSE of 0.214) compared to eGFRcr-cys (1 - P30 of 13.8% and RMSE of 0.232; P = 0.004 and P = 0.006, respectively). However, improvements in accuracy did not generally translate into significant improvement in classification or reclassification of mGFR categories.

LIMITATIONS

Study population may not be generalizable to clinical settings other than large urban medical centers in China.

CONCLUSIONS

A panel of endogenous filtration markers including B2M and BTP in addition to creatinine and cystatin C may improve GFR estimation in China. Further study is necessary to determine whether GFR estimation using B2M and BTP can be improved and whether these improvements lead to useful clinical applications.

Comparison of the new and traditional CKD-EPI GFR estimation equations with urinary inulin clearance: A study of equation performance

BACKGROUND

Diagnosis, prognostication and treatment in chronic kidney disease is often informed by an estimate of the glomerular filtration rate (GFR). Commonly used GFR estimation (eGFR) equations are based on serum creatinine (Cr) concentrations and display suboptimal precision and accuracy. Newer equations incorporating additional endogenous markers such as β-Trace Protein (BTP), β₂-Microglobulin (B2M) and cystatin C (cysC) have been developed but require validation.

METHODS

This prospective cohort study evaluated the performance of 6 eGFR equations developed by the chronic kidney disease - epidemiology collaboration group (CKD-EPI) against urinary inulin clearance GFR in patients recruited from outpatient nephrology clinics.

RESULTS

Mean biases were negligible and similar between equations. The eGFR-EPI Cr/cysC had the best precision and accuracy of all the equations and the best agreement with inulin mGFR when classifying participants into GFR categories. The BTP and B2M equations displayed the worst precisions and accuracies and showed the least consistent performance across levels of GFR. Thus, the eGFR-EPI Cr/cysC is the least biased, most precise and has the highest accuracy as compared to other eGFR-EPI equations.

CONCLUSIONS

The BTP and B2M equations are the worst performing of the eGFR-EPI equations, and no benefit is observed with the addition of BTP or B2M to Cr/cysC.