GFR prediction from cystatin C and creatinine in children: effect of including body cell mass
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Published on: October 21, 2018
Trine Borup Andersen1, Lars Jødal, Martin Boegsted
1Department of Nuclear Medicine, Aalborg Hospital, Aarhus University Hospital, Aalborg, Denmark. tba@rn.dk
Insights
A new model estimating glomerular filtration rate (GFR) using body cell mass (BCM) in children shows improved accuracy. Another model using weight also provides accurate GFR estimates without needing BCM measurements.
Area of Science:
- Pediatric Nephrology
- Biomarkers
- Renal Function Estimation
Background:
- Accurate estimation of glomerular filtration rate (GFR) is crucial for pediatric kidney disease management.
- Existing cystatin C-based models for GFR estimation in children require improvement for enhanced accuracy.
- Hypothesized that incorporating body cell mass (BCM) into GFR estimation models would improve accuracy.
Purpose of the Study:
- To develop and validate novel GFR estimation models for children.
- To compare the accuracy of new models, including one using BCM, against established GFR reference methods and existing prediction models.
- To assess the utility of a weight-based GFR estimation model as an alternative to BCM.
Main Methods:
- Diagnostic test accuracy study involving 119 children.
- Developed two new GFR prediction models: one incorporating BCM (SCysC, height, BSA, SCr) and another using weight (SCysC, height, BSA, SCr).
- Validated models using random subsampling cross-validation, comparing accuracy and precision (RMSE, R(2), % within ±10% and ±30%) against chromium 51 ethylenediaminetetraacetic acid ((51)Cr-EDTA) clearance.
Main Results:
- The BCM-based model demonstrated superior performance, predicting GFR within ±30% for 98% and ±10% for 66% of participants.
- The weight-based model showed comparable accuracy, predicting GFR within ±30% for 97.5% and ±10% for 62% of participants.
- The BCM model achieved the highest R(2) and lowest root mean square error (RMSE) among all evaluated models.
Conclusions:
- A novel GFR estimation model incorporating BCM offers higher accuracy in children compared to previous models.
- A weight-based GFR estimation model provides a nearly equally accurate alternative when BCM data is unavailable.
- While improved, endogenous GFR estimation methods still lack the accuracy of exogenous markers for precise clinical determination.
Background:
Aiming to develop a more accurate cystatin C-based model for estimation of glomerular filtration rate (GFR) in children, we hypothesized that inclusion of body cell mass (BCM) would increase the accuracy of the GFR estimate in comparison to a well-established GFR reference method.
Study Design:
Diagnostic test accuracy study.
Settings & Participants:
119 children (mean age, 8.8; range, 2.3-14.9 years) referred for GFR measurement by chromium 51 ethylenediaminetetraacetic acid ((51)Cr-EDTA) clearance (mean GFR, 98; range, 13.7-147.4 mL/min/1.73 m(2)).
Index Test:
GFR estimations by the 2 prediction models resulting from theoretical considerations corroborated by forward stepwise variable selection: GFR (mL/min) = 0.542 × (BCM/SCysC)(0.40) × (height × BSA/SCr)(0.65) and GFR (mL/min) = 0.426 × (weight/SCysC)(0.39) × (height × BSA/SCr)(0.64), where SCysC is serum cystatin C level, BSA is body surface area, and SCr is serum creatinine level. The accuracy and precision of these models were compared with 7 previously published prediction models using random subsampling cross-validation. Local constants and coefficients were calculated for all models. Root mean square error, R(2), and percentage of predictions within ±10% and ±30% of the reference GFR were calculated for all models. Based on 1,000 runs of the cross-validation procedure, median values and 2.5th and 97.5th quantiles of the validation parameters were calculated.
Reference Test:
GFR measurement by (51)Cr-EDTA clearance.
Results:
The BCM model predicted 98% within ±30% of reference GFR and 66% within ±10%, which was higher than for any other model. The weight model predicted 97.5% within ±30% of reference GFR and 62% within ±10%. The BCM model had the highest R(2) and the smallest root mean square error.
Limitations:
Included only 9 children with GFR <60 mL/min/1.73 m(2). Lack of independent validation cohort.
Conclusions:
The novel BCM model predicts GFR with higher accuracy than previously published models. The weight model is almost as accurate as the BCM model and allows for GFR estimation without knowledge of BCM. However, endogenous methods are still not sufficiently accurate to replace exogenous markers when GFR must be determined with high accuracy.
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