Combined Urinary Biomarkers Improve CKD Detection Accuracy in Sickle Cell Patients


Identifying early stages of chronic kidney disease in patients with sickle cell anemia has the potential of allowing for personalized treatment and better prognosis.

Yagahira Castro-Sesquen, PhD

Yagahira Castro-Sesquen, PhD

Using a combination of urinary biomarkers can improve accuracy in early chronic kidney disease (CKD) detection among patients with sickle cell anemia, according to a new study.

Since more than 60% of sickle cell anemia adults develop CKD, early identification can allow for personalized treatment and better prognosis in these patients.

A team led by Yagahira Castro-Sesquen, PhD, Department of Microbiology, Howard University, evaluated spot urine samples of patients with sickle cell disease (n = 54) at the University of Illinois at Chicago. All patients were considered in a steady state.

Castro-Sesquen and colleagues then classified them by the stage of CKD based on the National Kidney Foundation, Kidney Disease Outcomes Quality guidelines.

As such, patients were grouped into 3 cohorts: Stage 0 (no CKD, n = 23), Stage 1 (early stage CKD, n = 19), and Stages 2-5 (moderate to severe CKD, n = 12).

The investigators measured urine levels of ceruloplasmin, transferrin, hemoglobin, ferritin, orosomucoid, and hepatocyte growth factor like—all of which reflect the pathophysiology of sickle cell anemia, such as iron homeostasis, inflammation, and glomerular hyperfiltration.

The biomarkers were measured by ELISA and normalized to urinary creatinine concentrations. Further, they used the McNemar’s Test against the simple model (urine hemoglobin only) and complete model (all biomarkers together) to compare differences in sensitivity and specificity of biomarker combinations.

Thus, they proceeded to test each biomarker’s ability to distinguish sickle cell anemia patients without CKD and CKD Stage 1. To do this, they constructed receiver operating characteristic (ROC) curves to determine the appropriate cutoffs for each biomarker—they used only the cutoffs that provided the highest Youden Indexes.

The investigators found that hemoglobin, ceruloplasmin, and orosomucoid had a sensitivity of 100%. However, they noted that specificity was lower than 80% (range, 65.2%-72.7%).

“Other biomarkers [ferritin, transferrin, hepatocyte growth factor like] had sensitivities lower than 80%, suggesting that individually these biomarkers are not accurate for early detection of CKD,” they wrote.

Different combinations of biomarkers were then compared to the single biomarker model (hemoglobin) as well as a complete combination of 6 biomarkers.

They reported that this complete combination significantly improved specificity (from 69.6% to 82.6%). All combinations significantly increased specificity (from 69.6% to 78.3%-82.7%) when compared with the single biomarker model.

The investigators also noted that even combinations of 4 to 5 biomarkers also improved specificity compared to the single biomarker model.

And finally, they found that a combination of hemoglobin, ceruloplasmin, orosomucoid, ferritin produced specificity values similar to the complete model.

“These results demonstrate that the use of multiple biomarkers can improve the accuracy in the detection of kidney pathology in SCD patients, which has essential value for clinicians and researchers of clinical trials to target high-risk individuals for early treatment and preventive care,” Castro-Sesquen and team wrote.

The study, “Use of Multiple Urinary Biomarkers for Early Detection of Chronic Kidney Disease in Sickle Cell Anemia Patients,” was published online in Blood.

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