Key Points

Plasma biomarkers (kidney injury molecule-1, KIM-1), urine biomarkers (EGF/creatinine and urine albumin-creatinine ratio), and eGFR identified four prognostic groups in children with CKD progression.A panel of biomarkers may better capture the complexity of kidney disease in children and may allow for a broader assessment of kidney health.

Background

We have previously studied biomarkers of tubular health (EGF), injury (kidney injury molecule-1 [KIM-1]), dysfunction (α-1 microglobulin), and inflammation (TNF receptor-1, TNF receptor-2, monocyte chemoattractant protein-1, YKL-40, and soluble urokinase plasminogen activator receptor) and demonstrated that plasma KIM-1, TNF receptor-1, TNF receptor-2, urine KIM-1, EGF, monocyte chemoattractant protein-1, and urine α-1 microglobulin are each independently associated with CKD progression in children. In this study, we used bootstrapped survival trees to identify a combination of biomarkers to predict CKD progression in children.

Methods

The Chronic Kidney Disease in Children (CKiD) Cohort Study prospectively enrolled children aged 6 months to 16 years with an eGFR of 30–90 ml/min per 1.73 m2. We measured biomarkers in stored plasma and urine collected 5 months after study enrollment. The primary outcome of CKD progression was a composite of 50% eGFR decline or kidney failure. We constructed a regression tree–based model for predicting the time to the composite event, using a panel of clinically relevant biomarkers with empirically derived thresholds, in addition to conventional risk factors.

Results

Of the 599 children included, the median age was 12 years (interquartile range [IQR], 8–15), 371 (62%) were male, baseline urine protein-creatinine ratio was 0.33 (IQR, 0.12–0.95) mg/mg, and baseline eGFR was 53 (IQR, 40–66) ml/min per 1.73 m2. Overall, 205 children (34%) reached the primary outcome of CKD progression. A single regression tree–based model using the most informative predictors with data-driven biomarker thresholds suggested a final set of four prognosis groups. In the final model, urine albumin/creatinine was the variable with the highest importance and along with urine EGF/creatinine identified the highest risk group of 24 children, 100% of whom developed CKD progression at a median time of 1.3 years (95% confidence interval [CI], 1.0 to 1.7). When the regression tree–derived risk group classifications were added to prediction models including the clinical risk factors, the C-statistic increased from 0.76 (95% CI, 0.71 to 0.80) to 0.85 (95% CI, 0.81 to 0.88).

Conclusions

Using regression tree–based methods, we identified a biomarker panel of urine albumin/creatinine, urine EGF/creatinine, plasma KIM-1, and eGFR, which significantly improved discrimination for CKD progression.