In patients with type 2 diabetes mellitus, anemia is common and appears in earlier stages of chronic kidney disease (CKD) than in nondiabetic patients (1,2). Anemia further increases the risk for cardiovascular disease (CVD) and death (3–5). Renal production of erythropoietin (EPO), the most important hormone of hemoglobin regulation, might be impaired in CKD, resulting in absolute EPO deficiency, i.e. low EPO levels as the cause of decreasing hemoglobin levels (6). However, because anemia can frequently be observed even in the early stages of CKD, it is unlikely that mild-to-moderate impairment of kidney function is the sole underlying mechanism (2,7,8).
Normochromic normocytic anemia can occur in various chronic diseases, and it appears that dysregulation of iron homeostasis and inflammatory processes act as the main mediators (9–11). Similarly, anemia in diabetic CKD is likely multifactorial, involving EPO deficiency as well as iron dysregulation and inflammation (12–14). Absolute EPO deficiency can be caused by diminished EPO production as well as by EPO-sensing errors (15, 16); however, recent data also describe functional EPO deficiency or EPO resistance, which is characterized by a low hemoglobin despite EPO levels that are within the “normal” range (17).
Understanding the pathophysiology of anemia of CKD is crucial, because there is growing evidence that treatment of anemia with EPO-stimulating agents (ESA) might be associated with increased risk for serious adverse events when targeting higher (i.e. normal for the healthy population) hemoglobin levels (18). This was observed in diabetic and nondiabetic patients, as well as in CKD patients and those receiving dialysis or after kidney transplantation. Currently, it is unknown which particular group of patients might benefit from a higher hemoglobin target versus those who are at high risk for adverse events. In addition, it is also not clear to date whether the attributable risk is caused by ESA themselves or by the underlying processes that lead to the requirement for higher ESA doses (19).
The purpose of this study was to characterize levels of endogenous EPO in diabetic patients with CKD without severe iron deficiency or on treatment for anemia. We aimed to identify factors associated with EPO levels, with a particular focus on CKD and inflammatory markers, as well as to investigate the relationship between EPO levels and all-cause mortality risk.
Study Population and Methods
A cohort of 255 patients with type 2 diabetes mellitus was enrolled between 2003 and 2005 from four nephrology outpatient clinics in the Würzburg area of Germany. Adult patients with type 2 diabetes mellitus and CKD of any stage, but not on dialysis or after kidney transplantation, were included. The patients were not eligible if they were on iron, vitamin B12, folate, or ESA therapy or received red blood cell transfusions within 3 weeks before enrollment. For this study, we excluded patients with obvious iron deficiency (i.e. ferritin <30 μg/L) (20) and patients on antibiotic treatment, to minimize infectious reasons for inflammation. We analyzed 215 patients in whom EPO levels were available.
The primary purpose of the study was to investigate the cross-sectional association between untreated anemia and clinical parameters, markers of kidney function, and inflammation in patients with diabetes and CKD. As a post hoc defined aim, we collected longitudinal data of the patients' survival status. This was done between 2008 and 2009 by telephone interviews with the patients' nephrologist and/or primary-care physician. The study was conducted according to the Declaration of Helsinki and received approval from the local ethics committee of the University of Würzburg. All of the patients gave written informed consent.
The study visit was performed by a trained nurse and/or physician and comprised physical examination and detailed evaluation of medical history and medications. All of the laboratory tests except EPO level were measured as part of the usual standard of care. Serum EPO was quantified by ELISA (EPO-ELISA®; Roche; limit of quantification, 2.8 to 200 units/L; intra-assay variance, 2.7 to 7.1%; interassay variance, 1.9 to 8.3%; limit of detection, 0.24 units/L), and the results were not reported to the treating physician. History of angina pectoris, myocardial infarction, stroke, or transient ischemic attack was considered as history of CVD. GFR was calculated by taking the average of measured creatinine and urea clearance in a 24 hour urine collection, adjusted for body-surface area (21). If the 24 hour urine was missing (4.9% of the total cohort), GFR was estimated according to the simplified Modification of Diet in Renal Disease (MDRD) formula (22). Stages of CKD were determined according to Kidney Disease Outcomes Quality Initiative guidelines (22). Anemia was defined as hemoglobin <120 g/L in women and <135 g/L in men (6).
Analyses were performed using SAS 9.1 (SAS Institute, Cary, NC). Characteristics of study participants were compared across EPO tertiles (≤10.6 units/L, 10.7 to 15.9 units/L, and ≥16.0 units/L) using ANOVA, Kruskal-Wallis test, chi-squared test, and Fisher's exact test, as appropriate. Factors associated with EPO levels at baseline were examined using linear regression analysis, including variables that differed (P < 0.2) across EPO tertiles. The logarithmic form was used for EPO, C-reactive protein (CRP), ferritin, and proteinuria; the quadratic term was calculated for age and albumin; and cholesterol was included as its inverse. In multivariate stepwise selection analyses, all of the variables associated (P < 0.1) with EPO were included in addition to hemoglobin, because EPO itself stimulates hematopoiesis (11). We also tested the interaction of GFR on the relationship between CRP and EPO.
We conducted several sensitivity analyses to assess the robustness of the results by (1) excluding patients in whom GFR was estimated rather than calculated on the basis of measured creatinine and urea clearances; (2) forcing gender and proteinuria in the models; and (3) including angiotensin-converting enzyme (ACE) inhibitor/angiotensin-receptor blocker (ARB) treatment and statin treatment in the analyses. Statins might affect inflammatory processes through pleiotropic effects independently from its lipid-lowering potency (23), and ACE inhibitors and ARB are known to influence hematopoiesis and inflammation (24).
The association of EPO levels at baseline with mortality was investigated by Kaplan–Meier analyses across tertiles. We used Cox proportional hazards analyses to analyze the same variables from our linear regression models on their relation to time to death. All of the variables with P ≤ 0.05 in univariate analyses were included in multivariate models. The proportional hazards assumption and the functional form of the variables were investigated with log-log-survival plots, Martingale residuals, and Schoenfeld residuals, respectively. Model performance was assessed by a time-dependent C-statistic; similar to the area under the receiver operator curve, it describes the probability that the model will assign the higher mortality risk to the patient who actually died as compared with the patient who remained alive.
Characteristics of study participants are displayed in Table 1. The median GFR of the entire cohort was 49 ml/min per 1.73 m2, reflecting a mostly mild-to-moderate impairment of kidney function: CKD stage 1, 5.6%; stage 2, 32.9%; stage 3, 38.4%; stage 4, 18.5%; and stage 5, 4.6%. The prevalence of anemia was 41% in the total cohort and increased from 15% to 18% in CKD stages 1 and 2, to 46% in CKD stage 3, and up to 81% to 89% in CKD stages 4 and 5 (P < 0.001 for trend). Median EPO level did not vary significantly across CKD stages and ranged from 13.0 to 14.9 units/L. Patients in the highest EPO tertile were older with a lower GFR and a high prevalence of history of CVD. Elevated-CRP and low albumin levels were also particularly common in this group of patients. Hemoglobin levels did not vary significantly across EPO tertiles, whereas ferritin was lowest in the highest EPO tertile.
Factors Associated with EPO Levels
In univariate analysis, a number of variables were associated with higher EPO levels (Table 2). These included older age, elevated CRP, decreased albumin, ferritin, and cholesterol, as well as a history of CVD (all P < 0.05) and of hypertension (P = 0.1). Advanced stages of CKD, i.e. low levels of GFR, were associated with higher EPO levels (P = 0.01). After adjusting for these variables as well as for hemoglobin, only CRP, ferritin, and hypertension were independently associated with EPO levels, whereas albumin (P = 0.07) and a history of CVD (P = 0.07) approached significance. GFR lost its significant inverse association (P = 0.37) with EPO after adjustment for the described variables. Notably, hemoglobin was not associated with EPO levels (univariate P = 0.13, multivariate P = 0.31), and even forcing hemoglobin into the multivariate analyses did not change the associations of the predictive variables. The interaction term of CRP and GFR (P = 0.07 in the multivariate model) suggested an even stronger relationship between CRP and EPO levels in patients with reduced kidney function. We tested the robustness of our results in a first step by excluding patients in whom GFR was estimated according to the MDRD formula (n = 11) because of missing 24-hour urine collection. The variables of the model remained significant with similar β-coefficients. Similarly, forcing gender and proteinuria into the models had no effect on the findings. Finally, we included statin treatment and ACE inhibitor/ARB treatment in the regression model. No relationship between these variables and EPO levels could be identified.
Patients were followed for up to 7.0 years (median duration, 4.1 years) and 41 patients died (19.2%). None of the patients were lost to follow-up. A cardiac event (myocardial infarction, sudden death, or heart failure) was the primary cause of death (n = 14; 35.2%), followed by infections (n = 10; 24.4%). Two patients died from stroke, three died from malignancy, five died from other causes, and no cause of death could be determined in seven patients. We could not find a clear relation of EPO levels with a specific cause of death, in particular with cardiac reasons (low, n = 5; intermediate, n = 2; high EPO tertile, n = 8, respectively), because of the limited number of outcomes.
Predictors of Mortality
Elevated EPO levels were associated (P = 0.056) with mortality across tertiles (Figure 1). In univariate Cox regression, an elevated EPO level was a predictor of mortality along with older age, a history of CVD, impaired kidney function, elevated CRP, and lower levels of albumin and hemoglobin (Table 3). In multivariate modeling, only age, history of CVD, albumin, and EPO level remained independently associated with mortality. Advanced stages of CKD (P = 0.2) and higher CRP levels (P = 0.3) were still related to worse outcome but lost significance. In contrast, the point estimate for hemoglobin in the multivariate analysis showed no association any more with all-cause mortality. Ferritin and hypertension were not related to mortality in univariate modeling and thus were not considered in the multivariate model. However, if we forced these variables in the multivariate model, the results did not change, i.e. the coefficients of the variables associated with mortality remained unchanged. A model that included age, albumin, and history of CVD provided a C-statistic of 0.79 (95% confidence interval, 0.72 to 0.86). There was a small incremental improvement in the C-statistic, 0.80 (95% confidence interval, 0.74 to 0.87) when the EPO level was added to this model.
In diabetic patients with CKD, we found EPO levels that were closely related to markers of inflammation and iron status and that were widely unrelated to impaired kidney function. We did not find support for absolute EPO deficiency, because EPO levels stayed within a considerably “normal” range. A possible explanation of our results may be a combination of endogenous EPO resistance caused by inflammation along with diminished iron availability. Furthermore, elevated EPO levels represent a risk factor for mortality that was independent of the level of kidney function and inflammation.
In our population of diabetic patients, EPO levels were predominantly in a range that would be considered normal in the healthy population; however, the normal range for EPO levels in elderly diabetic patients with CKD is unknown (17). EPO levels are conventionally thought to be diminished in CKD, as a consequence of impaired renal EPO production (22). We found high EPO levels to be associated with lower GFR; thus we did not find evidence to support an absolute EPO deficiency. The scenario of EPO levels that are inappropriately low for the degree of anemia (although in absolute values may be even higher than in the healthy population) (25) has been described in a variety of chronic diseases including congestive heart failure and CKD (17,26). Several inflammatory mechanisms may contribute to this phenomenon of EPO resistance, such as inhibition of the growth of erythroid progenitor cells, down-regulation of EPO-receptor expression, mediation of antagonistic binding to the EPO receptor, and inhibition of downstream signaling cascades (26). Our results that elevated EPO levels were in large part related to the level of inflammation are in line with the described mechanisms. Interestingly, recent reports demonstrated diminished EPO resistance after statin treatment potentially through pleiotropic “inflammation-lowering” effects (27,28). However, in our study we could not detect any effect of statin treatment on the described associations. In all our analyses, higher EPO levels were independently related to markers of inflammation, namely higher CRP levels and lower albumin levels, as well as with hypertension and a history of CVD. The latter variables are known to be associated with inflammatory processes (12,13) and can be considered as a proxy for sicker patients who developed cardiovascular complications for various reasons. Interestingly, although the association of EPO levels and GFR disappeared in multivariate analyses, we found a more pronounced relationship between CRP and EPO in patients with impaired kidney function.
Inflammatory mechanisms are proposed to be responsible for multiple processes in anemia of chronic diseases, such as for dysregulation of iron homeostasis, where iron uptake is increased but gets “trapped in its stores,” i.e. the cells of the reticuloendothelial system (10,11). As a result, the levels of circulating iron are decreased and are therefore not available for hemoglobin synthesis or other biologic purposes. The acute phase protein hepcidin appears to have an important role, itself being regulated by iron and cytokines (29). Although we excluded patients with obvious absolute iron deficiency (ferritin, <30 μg/L), we found evidence for diminished iron availability as expressed by an inverse relationship between EPO and ferritin (a marker of iron storage as well as an acute phase reactant) (30), even after adjustment for variables that reflect inflammatory processes. Furthermore, whereas EPO stimulates erythrocyte and hemoglobin synthesis (11), we did not detect an association of hemoglobin with EPO. These results support the described “blunted EPO response” to low hemoglobin in diabetic patients in contrast to nondiabetic patients, in whom an inverse correlation between EPO and hemoglobin levels was observed (31).
Both diabetes and CKD represent a “high risk” population for worse outcome (13,14,32). In addition to established predictors for mortality, such as age, history of CVD, and albumin (33), we identified elevated EPO levels as an independent risk factor. Similar results were observed in elderly patients (34), kidney transplant recipients (35), and patients with congestive heart failure (36,37). We observed that the association of EPO with the risk for death was even stronger than that of CRP or GFR, whereas low hemoglobin levels were not associated with the outcome after controlling for the described variables.
It is of crucial clinical importance to understand the pathophysiologic processes related to anemia, especially if ESA treatment needs to be started. It is well known that patients with elevated levels of inflammatory markers need higher doses of ESA to reach certain hemoglobin targets and that these patients are at particularly high risk for mortality (38–40). In a subgroup analysis or the Trial to Reduce Cardiovascular Events With Aranesp Therapy trial, this group of patients was described as “nonresponders,” because hemoglobin did not increase adequately to initial ESA treatment (41). Thus therapy was not only ineffective in this group but was also associated with increased risk for mortality. To date, it is not sufficiently understood whether it is the use of a higher ESA dose itself or the underlying reasons that necessitate the use of higher ESA doses to achieve target hemoglobin levels which are responsible for this phenomenon (19). The TREAT investigators commented that it was not possible to develop a model to predict response to ESA treatment despite the large number of variables available; thus the group of patients that was at high risk for mortality could not be characterized sufficiently (41). The incremental discriminatory value of EPO level to our Cox model was modest but may improve the prediction of response to ESA treatment (42). It is conceivable that elevated endogenous EPO levels despite low levels of hemoglobin, so-called EPO resistance, are an important prognostic factor for worse patient outcome.
We are aware of several limitations of our findings. As in any observational study, no relationship can be determined sufficiently, i.e. the direction of an association in cross-sectional analyses cannot be explored, as well as whether a variable that is predictive for the outcome in longitudinal analyses is in fact causal. It is of note that anemia was more common (41%) in our cohort as compared with published prevalence rates of 15% to 25% (16,17). Our study design restricted patients to those not on any form of anemia therapy. This likely reflects the natural (untreated) prevalence of anemia in CKD; thus we cannot claim generalizability to anemia-treated patients. We could not separate iron deficiency from iron dysregulation under the influence of inflammation, because we did not have measurements of soluble transferrin receptor (11) or hepcidin (10). Additionally, although only 41 outcomes were observed, we included seven variables in the multivariate analyses; therefore overfitting of the model is possible. Because the study was not designed to investigate mortality, the purpose of the longitudinal analysis was mainly considered as hypothesis generating, in particular because no data on either iron or ESA therapy that was started after baseline was collected. Finally, we cannot apply our findings to the nondiabetic CKD population.
In our cohort of patients with diabetic CKD, EPO levels were closely associated with inflammation and largely independent of kidney function and hemoglobin. Elevated EPO levels were also independently predictive for all-cause mortality. Aside from iron dysregulation, inflammation may contribute to endogenous EPO resistance and impair hemoglobin regulation. This phenomenon may play an important role in understanding the efficacy and safety of ESA treatment in patients with CKD.
Dr. Wagner received travel grants from Roche, Germany. The other authors have nothing to declare. Roche, Germany, sponsored data collection as well as measurement of EPO. Otherwise, Roche, Germany had no influence on the conduct of the study, data analysis, and interpretation. The data are owned by the authors.
We thank Christine Penka and Marcus Werner for data collection, and we gratefully acknowledge the effort of the collaborators in the outpatient clinics of the University Hospital Würzburg and the Dialysis Centers in Schweinfurt (Drs. Harlos, Berweck, and Schwedler), Marktheidenfeld (Drs. Kulzer, Warsitz, and Naujoks), and Würzburg (Drs. Netzer and Heyd-Schramm). We also thank Hocine Tighiouart at Tufts Medical Center for providing the SAS macro for calculating a time-dependent C-statistic.
Dr. Wagner received funding from the fellowship training program of the National Kidney Foundation Center for Clinical Practice Guideline Development and Implementation at Tufts Medical Center. Dr. Alam was supported by a fellowship training grant from the Kidney Foundation of Canada. Parts of the results have been presented in abstract form at the XLV ERA-EDTA congress in May 2008 in Stockholm, Sweden and the 43rd Congress of the American Society of Nephrology in November 2010 in Denver, Colorado.
Published online ahead of print. Publication date available at www.cjasn.org.
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