Diabetes continues to be the leading cause of end-stage renal disease (ESRD) requiring renal replacement therapy (RRT) in the United States. Approximately 187,000 cases, or 44% of all cases of ESRD, can be attributed to type 1 (6%) and type 2 (38%) diabetes1. Over the next 10 years, the number of patients with diabetes and ESRD is expected to double, causing a significant increase in the burden of care for this population of patients2. Therefore, the identification of modifiable factors that might prevent or slow the progression of end-stage diabetic nephropathy has become increasingly important.
In patients with type 1 diabetes, renal impairment is rarely present at the time of diagnosis, but the prevalence rises to approximately 20% after 20 to 25 years of diabetes3. The prevalence of nephropathy at diagnosis of type 2 diabetes is 5% to 10% and the cmulative incidence of nephropathy has been reported to be 25% to 60% after 20 years of diabetes4. Despite the differences in the prevalence of renal disease at the time of diagnosis of type 1 and type 2 diabetes, the cmulative incidence5 and clinical course of renal dysfunction is similar4. With continued renal impairment, the glomerular filtration rate (GRF) declines and macroalbuminuria ensues, marking the early stages of the progression to end-stage renal failure6. Recently, the World Health Organization (WHO) Multinational Study of Vascular Disease in Diabetes confirmed the importance of proteinuria and retinopathy as markers of renal failure in patients with type 1 and type 2 diabetes7.
Persons with diabetes may have nondiabetic glomerulopathies that mimic the clinical picture of diabetic nephropathy8. The presence of retinopathy in patients with diabetes, however, strongly suggests that diabetes is the underlying cause of the nephropathy9. In persons without retinopathy, the likelihood of finding a nondiabetic cause of renal disease may be as high as 50%10. The Early Treatment Diabetic Retinopathy Study (ETDRS) enrolled persons with diabetes and retinopathy to study the therapeutic effects of aspirin and laser photocoagulation on diabetic retinopathy11. Because all ETDRS participants had some degree of retinopathy, the etiology of renal disease in this population was most likely due to diabetes. Thus, the ETDRS provides an ideal cohort to assess the risk factors for diabetic renal disease. In this study, we use the ETDRS cohort to identify risk factors for the future development of ESRD requiring RTT.
METHODS
Study subjects
Subjects were participants in the ETDRS, a randomized clinical trial designed to assess photocoagulation and aspirin treatment for patients with diabetic retinopathy. From April 1980 through July 1985, the ETDRS enrolled 3711 persons aged 18 to 69 years with retinopathy in each eye that was defined as having either mild, moderate, or severe nonproliferative diabetic retinopathy (NPDR) or mild to moderate proliferative diabetic retinopathy (PDR), with or without macular edema. The exclusion criteria for entry into the ETDRS were systolic blood pressure >210 mm Hg and/or diastolic blood pressure >110 mm Hg, and severe renal disease defined as a history of renal transplant or renal dialysis. Due to the need for long-term follow-up in this clinical trial, patients with severe renal disease, or an unfavorable prognosis for 5 years, were excluded from participating in the ETDRS. Eligible patients were randomly assigned to receive either 650 mg aspirin or placebo daily. Patients were followed for a minimum of 5 years and for as long as 9 years.
At baseline and during follow-up exams of 4-month intervals, ocular examinations and medical examinations were performed. The ocular risk factors evaluated include visual acuity, macular edema status, severity of diabetic retinopathy, and the development of proliferative retinopathy during the study. The patient characteristics included age, gender, race, body mass index (BMI), blood pressure, duration of diabetes, use of insulin, use of oral hypoglycemic medications, use of antihypertensive medications, cigarette smoking, alcohol consumption, and presence of diabetic neuropathy. Blood pressure was measured in the right arm, or the left arm if the right arm could not be used, of the seated patient, and was performed by the certified ETDRS medical examiner in the clinic. Neuropathy, evaluated by a physician at each clinical center, was assessed by testing vibratory sensation and assessing the patient for ulcers and previous amputations secondary to diabetes. Patients were classified as having type 1 diabetes if their age at diabetes diagnosis was 30 years or less and they started on continuous insulin use within 1 year of diagnosis, or their age at diabetes diagnosis was 40 years or less, they started on continuous insulin within 1 year of diagnosis, and their percent desirable weight was less than 120%. All others were classified as having type 2 diabetes. Baseline laboratory measurements assessed include fasting serum levels of hemoglobin A1c (HbA1c), total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, fibrinogen, creatinine, hematocrit, plasma proteins (fibrinogen and albumin), and urine protein. Urine specimens were tested once at baseline for urine protein by the dipstick method. After the first 2709 patients were enrolled the ETDRS protocol was modified, discontinuing some baseline laboratory measures.
Outcome measurement
The primary renal variable evaluated is the time to RRT and this was evaluated at every follow-up visit, scheduled at 4-month intervals during the course of the study. RRT was considered to be present when the patient had or became a candidate for renal dialysis or renal transplantation.
Statistical analysis
Kaplan-Meier analyses were used to evaluate the rate of RRT separately in type 1 and type 2 diabetes in the entire ETDRS population. Categorical and continuous variables were compared using the chi-square and Student t test, respectively, for the baseline demographic, clinical, and laboratory characteristics among the patients with type 1 or type 2 diabetes, with or without the requirement of RRT.
Cox proportional hazards regression was used to estimate the associations between demographic, clinical, and laboratory variables and the time to RRT, within each of the groups. The fully adjusted, multivariate Cox regression model was built using a backward stepwise elimination procedure, with age, gender, and race remaining in the model. All demographic, clinical, and laboratory variables were entered initially as continuous variables if possible. The only exceptions to fitting all variables in the model was for LDL cholesterol. LDL cholesterol was highly correlated with total cholesterol in type 1 (r = 0.90) and type 2 (r = 0.81) diabetes. Because significant results were identical using either total cholesterol or LDL cholesterol, we used total cholesterol and not LDL cholesterol in all analyses. The development of PDR was analyzed as a time-dependent covariate. The variables were eliminated from the model in the order of least significance until all remaining variables were significant at P
0.10. Continuous variables that were significant at the P 0.01 level were also redefined into clinically relevant categories, based on recommendations for clinical treatment recommendations where available12,13. Furthermore, categories may reveal useful information in cases of factors that provide nonlinear contributions to risk estimates. Serum creatinine is reported in the log form in order to control for the skewed distribution at baseline. Two-way interactions between relevant variables were then tested, and no significant terms were found to remain in the model.
Hazards ratios (HR) and 99% confidence intervals (CI) for the independent variables were calculated from the parameter estimates and standard errors in the final model. The reason for using a statistically significant P value of 0.01 and 99% CI is that these are secondary analyses, and more stringent criteria are preferred. Statistical analyses were performed using SAS 8.2 for Windows (SAS Institute Inc., Cary, NC, USA).
RESULTS
Study groups
Of the total ETDRS population (N = 3711), the 5-year Kaplan-Meier probability estimates of RRT during the course of the study were 10.2% and 9.8% for patients with type 1 and type 2 diabetes, respectively Figure 1. These rates resulted in approximately 13.2% of patients with type 1 diabetes and 11.3% of patients with type 2 diabetes requiring RRT during the entire course of the study. Baseline characteristics of patients with complete laboratory data, based on type of diabetes and the development of the requirement or the lack of requirement for RRT, are shown in Table 1. Those subjects with complete baseline data, shown in Table 1, did not significantly differ from those without complete data with respect to demographic data (data not shown).
Figure 1.
The Kaplan-Meier probability estimates of renal replacement therapy in the entire Early Treatment Diabetic Retinopathy Study (ETDRS) population by type 1 and type 2 diabetes.
Full figure and legend (11K)Table 1 - Baseline characteristics by diabetes type and development of renal replacement therapy (RRT).
Full table Of the ETDRS participants with complete baseline data, approximately 14% of patients with type 1 diabetes (N = 934) developed the requirement for RRT, with a mean follow-up time of 6.5 (
1.3) years. Those that required RRT were more likely to use antihypertensive medications, have proteinuria, have developed proliferative retinopathy during the study, have higher levels of HbA1c, systolic blood pressure, total cholesterol, LDL, triglycerides, and fibrinogen; and have lower levels of serum albumin and hematocrit.
Of those with type 2 diabetes (N = 1232) and complete baseline data, approximately 12% developed the requirement for RRT, with a mean follow-up time of 5.9 (1.8) years. In general, those that required RRT were more likely to be younger, use insulin daily, not use glucose lowering medications, have proteinuria, have developed proliferative retinopathy during the study, have higher levels of BMI, HbA1c, total cholesterol, triglycerides, fibrinogen, and serum creatinine, and have lower levels of HDL, serum albumin, and hematocrit.
Risk factors for RRT
Statistically significant predictors (P < 0.01) of RRT using multivariable Cox regression are shown in Table 2 by type of diabetes. Risk factors are shown as both categorical and continuous variables for comparison. Statistically significant predictors of the development of severe renal disease found in subjects with type 1 diabetes include duration of diabetes (HR = 0.94, 99% CI 0.90 to 0.99 per 1-year increment), BMI (HR = 1.14, 99% CI 1.05 to 1.23 per 1 unit decrement), HbA1c (HR = 1.21, 99% CI 1.07 to 1.38 per 1% increase), systolic blood pressure (HR = 1.20, 99% CI 1.04 to 1.39 per 10 mm Hg increase), total cholesterol (HR = 1.08, 99% CI 1.03 to 1.12 per 0.259 mmol/L increment), serum creatinine (HR = 8.74, 99% CI 3.17 to 24.06 per unit increment of log 1 
mol/L), serum albumin (HR = 2.54, 99% CI 1.51 to 4.27 per 10 g/L increment), and anemia (HR = 4.62, 99% CI 1.63 to 13.09). The development of PDR was also a predictor of RRT (HR = 2.65, 99% CI 1.40 to 5.02). The hazards model for patients with type 1 diabetes was also adjusted for age, race, gender, proteinuria, and alcohol consumption.
Table 2 - Risk factors for renal replacement therapy (RRT): Results of the final hazards ratio (HR) models.
Full table Statistically significant risk factors for RRT in type 2 diabetes include age (HR = 1.04, 99% CI 1.01 to 1.07 per 1-year decrement), total cholesterol (HR = 1.04, 99% CI 1.00 to 1.08 per 0.259 mmol/L increment), triglycerides (HR = 1.01, 99% CI 1.00 to 1.03 per 0.113 mmol/L increment), serum creatinine (HR = 17.49, 99% CI 8.10 to 37.77 per unit increment of log 1 mol/L), serum albumin (HR = 2.85, 99% CI 1.77 to 4.57 per 10 g/L increment), proteinuria (HR = 2.43, 99% CI 1.52 to 3.89), and anemia (HR = 4.12, 99% CI 1.62 to 10.39). The hazards model for patients with type 2 diabetes was also adjusted for race, gender, HbA1c, diabetic retinopathy, and neuropathy. Aspirin use, as assigned by the ETDRS trial, had neither a beneficial nor harmful effect on the development of the requirement for RRT in either type 1 or type 2 diabetes.
DISCUSSION
The ETDRS enrolled patients with some degree of retinopathy at baseline, making it likely that the etiology of renal disease in this population was related to diabetes, rather than some other cause of nephropathy9. The present study showed the baseline risk factors for RRT common to type 1 and type 2 diabetes include elevated total cholesterol, elevated serum creatinine, low serum albumin, and anemia. Other significant risk factors associated with type 1 diabetes, but not type 2 diabetes, included BMI, shorter duration of diabetes, elevated HbA1c, elevated systolic blood pressure, and the development of PDR. Risk factors associated with type 2 diabetes, but not type 1 diabetes, included younger age, proteinuria, and elevated triglycerides.
The WHO Multinational Study of Vascular Disease in Diabetes (WHO MSVDD) assessed predictors of renal failure, defined as RRT or nephrogenic causes of death, in patients with type 1 and type 2 diabetes7. Similar to our results in patients with type 1 diabetes, the WHO MSVDD showed that systolic blood pressure was associated with renal failure in type 1 but not type 2 diabetes. Also consistent with our findings was the finding in the WHO MSVDD that triglycerides were associated with renal failure in type 2 but not type 1 diabetes. Proteinuria was also an important risk factor for renal failure in both type 1 and type 2 diabetes in the WHO MSVDD. Unlike our findings, however, the WHO MSVDD did not find total cholesterol associated with the development of renal failure.
Proteinuria is a well-known complication and predictor of renal disease. Our findings are consistent with other studies demonstrating a relationship of proteinuria and the development of nephropathy in patients with type 114,15,16,17 and type 218,19 diabetes. Other complications of diabetes, such as retinopathy and neuropathy, although not statistically significant as independent predictors at the P 0.01 level in the multivariable hazards model for type 2 diabetes, were associated with RRT in our study. The development of PDR was associated with the development of RRT in patients with type 1 diabetes, suggesting a parallel course of these two serious complications, as seen in another study of diabetic retinopathy20.
The present study revealed that increasing levels of serum creatinine were independently associated with the requirement for RRT in both type 1 and type 2 diabetes. An increasing level of serum creatinine is reflective of a decreasing GFR. In the natural course of diabetic renal disease, the progressive decline of GFR is generally thought to be initiated after the development of overt nephropathy, or macroalbuminuria4. Therefore, increasing levels of serum creatinine likely reflect a more severe stage of renal disease in patients with diabetes. Hypoalbuminemia was also predictive for RRT in both type 1 and type 2 diabetes, consistent with other reports21. The excess loss of albumin through the kidney is likely the result of diabetic renal disease. Low levels of serum albumin, along with decreased BMI, may also reflect other systemic maladies such as malnutrition in patients with renal disease.
The interplay between lipids and nephropathy is becoming increasingly recognized, and lipids may independently contribute to renal injury in patients with diabetes22. The findings in our study are consistent with the findings of a recent study where correlations were shown between lipid abnormalities and degrees of renal damage in patients with chronic renal failure23. We present HRs for cholesterol and triglycerides treated as continuous and categorical data for comparison. These categories are based on clinical treatment recommendations of expert panels12. Although the high-risk categories of total cholesterol were not always statistically significant predictors of RRT as compared with the lowest risk category, total cholesterol was a statistically significant predictor when treated as a continuous variable. This discrepancy was likely due to the use of categories that did not adequately separate subjects into a high-risk group. It is also important to note that the creation of categories reduces the power of statistical analyses to detect differences among groups.
Anemia is a complication described in patients with severe diabetic complications24,25 and also found to be associated with an increased risk of developing PDR26. Anemia may be secondary to decreased levels of erythropoietin, a protein produced by the peritubular fibroblasts of the renal cortex that mainly functions to stimulate the production of red blood cells. The decrease in erythropoietin is likely caused by damage to the erythropoietin-producing fibroblasts, indicating serious renal pathology. However, anemia has been shown to be present in the earlier stages of nephropathy27. In the present study, decreased hematocrit was predictive of RRT in both type 1 and type 2 diabetes. Our findings confirm previous report of low hematocrit as a predictor of the progression of renal insufficiency28.
One of the more novel findings of this study is the observation that elevated serum fibrinogen, although not independently statistically significant at the P 0.01 level in the multivariable hazards model for type 2 diabetes, may be predictive of RRT. After adjusting for age and gender in the current study, hazards models showed that fibrinogen was a statistically significant predictor of RRT in type 1 (HR = 1.21, 99% CI 1.15 to 1.28 per 0.20 g/L increment) and type 2 diabetes (HR = 1.12, 99% CI 1.08 to 1.17 per 0.20 g/L increment). High fibrinogen concentrations have been shown to be associated with macrovascular disease for several decades29,30. A relationship between diabetic nephropathy and fibrinogen has been demonstrated with associations between markers of inflammatory activity, such as C-reactive protein and fibrinogen, with increases in proteinuria in patients with type 2 diabetes31. Although we found fibrinogen to be a possible risk factor, we cannot distinguish between the possibility that increased fibrinogen leads to thrombotic events that contribute to diabetic nephropathy or the possibility that the increased fibrinogen is an acute phase reactant or "inflammatory marker" related to diffuse microvascular damage, and is therefore an effect of the disease rather than a cause.
Some of the limitations of this study should be acknowledged. Proteinuria was evaluated with the dipstick method. Our study did not differentiate between micro- and macroalbuminuria at baseline and we are therefore unable to distinguish risk factors associated with different severities of proteinuria. Another limitation of this study was the inability to determine whether factors predictive of RRT were causative factors or consequences of already existent renal disease. For example, while the presence of proteinuria has been regarded as a marker of the severity of the glomerular pathology, some investigators have proposed that proteinuria may play a causative role in renal damage32.
There is some debate over the exact criteria for classifying patients as having type 1 or type 2 diabetes. Although we cannot clearly distinguish between type 1 and type 2 diabetes based on duration of diabetes, BMI, and insulin use, our C-peptide analyses suggest that errors in classification are low33. Our ability to determine the exact duration of type 2 diabetes is not possible and is comparable to all other studies of this type.
The generalizability of our study is limited by the fact that our study population is recruited from major ophthalmic clinical centers caring for patients with diabetic retinopathy instead of general medical clinics caring for their diabetes. Also, a patient's need for renal dialysis or transplant was determined by the patient's physician, and not by a standardized protocol. Therefore, the results of this study may be affected by the different treatment thresholds maintained by different physicians, and the availability of organs for transplantation.
In this study, we found that the major modifiable risk factors associated with RRT are serum lipids, glycemia, and blood pressure. Better control of hyperglycemia and hypertension have been demonstrated to have favorable effects on diabetic retinopathy and nephropathy34,35 but, as yet, no large clinical trials have investigated the effect of better control of serum lipids on renal disease. Other baseline factors associated with renal disease in type 1 and type 2 diabetes included serum creatinine, proteinuria, hypoalbuminemia, and possibly fibrinogen. Many of these risk markers are also markers of vascular pathology and inflammation. Interestingly, the risk factors for severe renal disease in this study are similar to the risk factors for high-risk PDR and severe visual loss in the same population26. Therefore, we emphasize that persons with diabetes and retinopathy should strictly control modifiable risk factors such as glycemia, blood pressure, and serum lipids in order to possibly slow the further development of microvascular complications.
It is tantalizing to propose that treatment of dyslipidemia may reduce the risk of diabetic nephropathy. Several small trials have attempted to address this question36,37,38,39 and some have suggested benefit37,38. While it is unlikely that lipid-lowering trials will choose renal disease as a primary end point, there are several large lipid-lowering trials in patients with diabetes that could consider renal disease as a secondary end point. Similarly, ongoing studies of fibrinogen and other inflammatory markers in cardiovascular disease could also assess the effects of therapies that modify these risk factors on renal events.
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Acknowledgments
The ETDRS was supported by contracts from the National Eye Institute, National Institutes of Health, and the U.S. Department of Health and Human Services.
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