Chronic kidney disease is often diagnosed quite late, because in early disease it causes no pains or other specific symptoms. Sometimes the patients have not even been aware of their impaired renal function, until they are in need of a renal replacement therapy (dialysis or transplantation). Then the diagnosis comes as a shock - and is especially bitter, because the patients usually learn that various interventions (e.g. a special diet, but also medication with ACE inhibitors) might have delayed, perhaps even prevented, end-stage renal disease.
CKD progression is currently assessed by a decline in estimated glomerular filtration rate (eGFR) and an increase in urinary albumin excretion (UAE). One major problem is that these "kidney parameters" are often not routinely measured by the GP. Besides, these markers are considered either to be late-stage markers or to have low sensitivity or specificity. It is nearly impossible to predict in patients with early stage CKD, if their disease will progress quickly or not. In some patients with an eGFR >60 ml/min/1.73 m2 and an UAE between 30 and 300 mg/g a rapid eGFR decline of more than 15 ml/min/1.73 m2 takes place, while in others the eGFR stays stable and the disease does not progress. "In order to stratify patients who are at high risk of rapid disease progression, we have to wait for one year, at least. Then we can evaluate, if the eGFR have declined by more than 15% during the last 12 month, and can start to treat", explains Prof. Carmine Zoccali, NDT Editor-in-Chief. "We are in need of new markers for CKD that give a better and faster result. Therefore the freshly published paper of Pontillo et al is of great importance."
The study group tested the performance of the urinary proteome-based classifier CKD273. The study results suggest that the marker allows the detection of progressive CKD at early disease stages. "This holds an enormous potential, especially, because early diagnosis and treatment of CKD can stop the disease from advancing, or slow its progress at least", concludes Prof. Zoccali.
Article: A urinary proteome-based classifier for the early detection of decline in glomerular filtration, Pontillo C, Jacobs L, Staessen JA et al., NDT, doi: 10.1093/ndt/gfw239, published online 6 July 2016.