Arch. Endocrinol. Metab. 2016;60(2):92-94
Biomarkers in diabetic kidney disease: good use and pitfalls
DOI: 10.1590/2359-3997000000167
In this issue of Archives of Endocrinology and Metabolism (AE&M), two manuscripts address the important issue of the search for new and reliable biomarkers of kidney function and chronic kidney disease (CKD) risk in diabetes. Domingueti and cols. () evaluate the performance of several formulas of GFR estimation in regard to albuminuria classification (normo-, micro- and macroalbuminuria). In their analyses, cystatin C-based formulas showed the best performance, followed closely by the new CKD-EPI creatinine-based equation. Their findings highlight the crave for more precise measures of GFR estimation and waiving of less efficient methods such as Cockcroft-Gault formula. When compared to MDRD equation the new CKD-EPI equation is more accurate and reduces the known effect of MDRD on sub-estimating GFR in normal and near-normal values (). However, the CKD-EPI equation based on creatinine also requires a race definition, which is always problematic, particularly in highly admixture populations. This formula has not been largely validated outside US, Europe and Australia and this should be done in populations ethnically different from the population in whom the equation was derived and revalidated, such as Brazil. Small Brazilian studies yielded results suggesting that this equation may be applied in our population (-), but larger studies are still necessary. On the other hand, cystatin C seems to improve accuracy in comparison to creatinine, but is still not largely available and its cost is still high. These problems could be minimized with a broader use of this marker, but to the present cystatin C use is still very much restricted to the research field.
In the other manuscript, Polat and cols. () have analyzed several endothelial dysfunction biomarkers in 73 patients with diabetes and either normoalbuminuria and microalbuminuria in comparison to healthy controls. The authors showed that although differences can be detected among the diabetic and non-diabetic groups, most biomarkers cannot discriminate those with and without albuminuria. Only sVCAM-1 showed a better performance in identifying those with microalbuminuria.
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