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Open Access Highly Accessed Research article

Predicting erythropoietin resistance in hemodialysis patients with type 2 diabetes

Andreas Schneider12*, Markus P Schneider23, Hubert Scharnagl4, Alan G Jardine2, Christoph Wanner1 and Christiane Drechsler1

Author Affiliations

1 Department of Medicine, Division of Nephrology, University Hospital Wuerzburg, Wuerzburg, Germany

2 Renal Research Group, British Heart Foundation (BHF) Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK

3 Department of Nephrology and Hypertension, University Hospital Erlangen, Erlangen, Germany

4 Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University Graz, Graz, Austria

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BMC Nephrology 2013, 14:67  doi:10.1186/1471-2369-14-67

Published: 22 March 2013

Abstract

Background

Resistance to ESAs (erythropoietin stimulating agents) is highly prevalent in hemodialysis patients with diabetes and associated with an increased mortality. The aim of this study was to identify predictors for ESA resistance and to develop a prediction model for the risk stratification in these patients.

Methods

A post-hoc analysis was conducted of the 4D study, including 1015 patients with type 2 diabetes undergoing hemodialysis. Determinants of ESA resistance were identified by univariate logistic regression analyses. Subsequently, multivariate models were performed with stepwise inclusion of significant predictors from clinical parameters, routine laboratory and specific biomarkers.

Results

In the model restricted to clinical parameters, male sex, shorter dialysis vintage, lower BMI, history of CHF, use of ACE-inhibitors and a higher heart rate were identified as independent predictors of ESA resistance. In regard to routine laboratory markers, lower albumin, lower iron saturation, higher creatinine and higher potassium levels were independently associated with ESA resistance. With respect to specific biomarkers, higher ADMA and CRP levels as well as lower Osteocalcin levels were predictors of ESA resistance.

Conclusions

Easily obtainable clinical parameters and routine laboratory parameters can predict ESA resistance in diabetic hemodialysis patients with good discrimination. Specific biomarkers did not meaningfully further improve the risk prediction of ESA resistance. Routinely assessed data can be used in clinical practice to stratify patients according to the risk of ESA resistance, which may help to assign appropriate treatment strategies.

Clinical trial registration

The study was registered at the German medical authority (BfArM; registration number 401 3206). The sponsor protocol ID and clinical trial unique identified number was CT-981-423-239. The results of the study are published and available at http://www.ncbi.nlm.nih.gov/pubmed/16034009 webcite.