Race and ethnicity influences on cardiovascular and renal events in patients with diabetes mellitus

Race and ethnicity influences on cardiovascular and renal events in patients with diabetes mellitus

Race and ethnicity influences on cardiovascular and renal events in patients with diabetes mellitus Eldrin F. Lewis, MD, MPH, a Brian Claggett, PhD, a...

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Race and ethnicity influences on cardiovascular and renal events in patients with diabetes mellitus Eldrin F. Lewis, MD, MPH, a Brian Claggett, PhD, a Patrick S. Parfrey, MD, b Emmanuel A. Burdmann, MD, PhD, c John J. V. McMurray, MD, d Scott D. Solomon, MD, a Andrew S. Levey, MD, e Peter Ivanovich, MD, f Kai-Uwe Eckardt, MD, g Reshma Kewalramani, MD, h Robert Toto, MD, i and Marc A. Pfeffer, MD, PhD a Boston, MA; Newfoundland and Labrador, Canada; do Rio Preto, Brazil; Scotland, UK; Chicago, IL; Erlangen, Germany; Thousand Oaks, CA; and Dallas, TX

Background The incidence of end-stage renal disease (ESRD) has been consistently shown to be higher among blacks and Hispanics compared to whites with unmeasured risk factors and access to care as suggested explanations. In a high-risk cohort with frequent protocol-directed follow-up, we evaluated the influence of race on cardiovascular (CV) outcomes and incidence of ESRD. Methods

TREAT was a randomized, double-blind, placebo-controlled study. This secondary analysis focused on role of race on outcomes. TREAT enrolled 4,038 patients with type 2 diabetes, chronic kidney disease (estimated glomerular filtration rate 20-60 mL/min per 1.73 m 2), and anemia (hemoglobin level ≤11 g/dL) treated with either darbepoetin alfa or placebo. We compared self-described black and Hispanic patients to white patients with regard to baseline characteristics and outcomes, including mortality, CV outcomes (myocardial infarction, stroke, heart failure, resuscitated sudden death, and coronary revascularization), and incident ESRD. Multivariate adjusted Cox models were developed for these outcomes.

Results Black and Hispanic patients were younger, more likely women, had less prior CV disease, and higher blood pressure. During a mean follow-up of 2.4 years with comparable access to care, blacks and Hispanics had a greater risk of ESRD but a significant lower risk of myocardial infarction and coronary revascularization than whites. After adjusting for confounders, blacks remained at significantly greater risk of ESRD than whites (hazard ratio 1.53, 95% CI 1.26-1.85, P b .001), whereas this ESRD risk did not persist among Hispanics. Conclusion

Despite similar access to care and lower CV event rates, the risk of ESRD was higher among blacks and Hispanics than whites. For blacks, but not Hispanics, this increase was independent of known attributable risk factors. (Am Heart J 2015;0:1-8.e4.)

The incidence and prevalence of end-stage renal disease (ESRD) in the United States have increased steadily over the past 3 decades with an estimated

From the aCardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, bDivision of Nephrology, Health Sciences Center, St Johns, Newfoundland and Labrador, Canada, cFaculdade de Medicina de São José, do Rio Preto, Brazil, dWestern Infirmary, University of Glasgow, Scotland, UK, eDivision of Nephrology, Tufts Medical Center, Boston, MA, fDivision of Nephrology/Hypertension, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, gDepartment of Nephrology and Hypertension, University of Erlangen-Nuremberg, Erlangen, Germany, hGlobal Clinical Development, Amgen, Thousand Oaks, CA, and iDepartment of Medicine, University of Texas SW, Dallas, TX. Clinical trial registration: ClinicalTrials.gov no. NCT00093015. Support: This parent trial was supported by Amgen, Inc. The subsequent analysis for this manuscript did not require additional support. Submitted November 7, 2014; accepted May 10, 2015. Reprint requests: Eldrin F. Lewis, MD, MPH, Brigham and Women's Hospital, Cardiovascular Division, 75 Francis St, Boston, MA 02115. E-mail: [email protected] 0002-8703 © 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ahj.2015.05.008

16,000 patients beginning treatment for ESRD in 2011 and a prevalence of N600,000 patients on dialysis or with a kidney transplant. 1 The rate of ESRD is 3.4 times greater among African Americans or blacks than whites in the United States, and the incidence is also increasing among Hispanics in various studies. 1-5 The factors that may partially explain this heightened risk for chronic kidney disease (CKD) progression among blacks include lack of access to care, poorer control of ESRD risk factors such as hypertension and diabetes, genetic polymorphisms such as apolipoprotein L1 (APOL1), socioeconomic status (SES), and lifestyle habits 6-10 Clinical trials are often designed to focus on either renal or cardiovascular (CV) events and generally do not have sufficient number of minority patients at risk for ESRD progression to be powered for hard conclusions. We used a standard of care treated population with diabetes and advanced CKD with strong minority participation to address the hypothesis that comparable access to care afforded in a randomized clinical trial with bimonthly or monthly follow-up would reduce the clinical disparity in

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development of ESRD between black and Hispanic patients as compared with white patients. We also aimed to determine the impact of race on the relative occurrence of nonfatal CV events and death.

Methods Study population and design TREAT 11 was a prospective, randomized, double-blind, placebo-controlled trial that enrolled 4,038 patients with type 2 diabetes mellitus, estimated glomerular filtration rate (eGFR) of 20 to 60 mL/min per 1.73 m 2 (calculated using the 4-variable Modification of Diet in Renal Disease Study formula), and iron-replete anemia. Patients were randomized to darbepoetin alfa or placebo and followed up for mean of 2.4 years with no significant difference in coprimary end points but a 2-fold increase in stroke with darbepoetin alfa. 11,12 At the time of enrollment, patients were asked by study staff to define their race into 1 of 9 categories: Aborigine, American Indian or Alaskan, Asian, black or African American, Hispanic or Latino, Japanese, Native Hawaiian or Pacific Islander, white or Caucasian, or other. Patients were grouped into “black,” “Hispanic,” and “white” with these terminologies used for simplicity for the purpose of this analysis. The 115 (2.9%) of patients who were in any of the other 6 categories were excluded from the primary analysis; however, they were added to the white patient designation for a sensitivity analysis (online Appendix A). The term race is used to represent race and ethnicity for simplicity. Blood and urine samples collected at baseline on all patients were analyzed for creatinine (used for eGFR calculation) every 2 to 4 weeks and other key variables detailed in online Appendix B. All patients provided written informed consent for participation in the primary trial. Outcomes End points were adjudicated by a central clinical end points committee. End-stage renal disease was defined as (a) the initiation of dialysis that persisted for N30 days, (b) the initiation of dialysis with death within 30 days, (c) physician recommendation to initiate dialysis with documented patient refusal, or (d) kidney transplantation. Death events were classified as CV and non-CV with subcategories or as unknown when insufficient information was provided. Definitions of all end points were previously reported. 12 Statistical analysis Baseline characteristics were stratified according to racial classification: black, Hispanic, and white. Categorical variables were compared across racial categories using Fisher exact or χ 2 tests, and continuous variables were compared using Kruskal-Wallis tests.

Mixed-effects models were fitted that incorporated all observations available before the time of ESRD (or end of study visit) for systolic blood pressure, serum creatinine, eGFR, and log-transformed urinary proteinto-creatinine ratio. For each observation for each patient, the number of days before ESRD at which the observation was obtained was modeled via restricted cubic splines to allow for a flexible, potentially nonlinear relationship over time. Random-effect intercept terms at the patient level were incorporated to allow for within-patient correlation. The univariate association between race and ESRD and between race and each component of the composite of death or nonfatal CV events was analyzed using Cox proportional hazards regression models, and incidence rates were calculated for each outcome grouped by race. Descriptive statistics were performed to assess number of patients who had a nonfatal CV event before ESRD. Four progressive multivariable models were performed with (a) ESRD and (b) death and nonfatal CV events as the outcomes to identify the independent association between race and these outcomes. Contents of the models are detailed in online Appendix B. Model 1 adjusted for age and sex. Model 2 added clinical variables and factors known to be predictive for developing ESRD in the TREAT renal model. 13 Model 3 further adjusted for renal and interim time-updated factors. Model 4 further adjusted for interim nonfatal CV events. To further eliminate potential confounding, a sensitivity analysis was performed in which all patients were censored at the time of a nonfatal CV event. TREAT was sponsored by Amgen. No additional funding was received to support this work. The academic leadership generated the concept for this manuscript. The primary data were at Brigham and Women's Hospital, and all authors had full access to the data for analysis. The first and senior authors wrote the manuscript with critical input from all other coauthors.

Results Among the 4,038 patients enrolled in TREAT, 815 (20.2%) were self-reported black, 538 (13.3%) were Hispanic, and 2570 (63.6%) were white. Black and Hispanic patients were younger and had a lower proportion of women, less coronary artery disease, heart failure, or myocardial infarctions (MIs), and higher blood pressure and serum hemoglobin A1C (HbA1C) than whites (Table I). Black patients had a higher body mass index and baseline eGFR than whites, whereas Hispanic patients had a lower body mass index and eGFR. Hispanics had a higher baseline urine protein-creatinine ratio and lower use of β-blockers. There was no difference between the groups with respect to use of an angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs).

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Table I. Baseline characteristics by racial/ethnic classification

USA/Canada (%) Age (y) Women (%) Known duration of diabetes (y) Serum HbA1c (%) Retinopathy (%) Body mass index (kg/ m 2) CV disease history (%) Coronary artery disease Heart failure MI Stroke Hypertension Peripheral artery disease Atrial fibrillation (%) Current smoker (%) Blood pressure (mm Hg) Systolic Diastolic Heart rate (beats/min) eGFR (mL/min/1.73 m 2) Serum creatinine (mg/dL) Urine protein-creatinine ratio (g/g) Serum CRP Medication (%) Insulin Oral hypoglycemic agents ACE inhibitor or ARB β-Blocker Aldosterone receptor blocker Statin Aspirin Prior ESA use Primary management Nephrologist Internal medicine Endocrinologist Cardiologist

Hispanic (n = 538)

Black (n = 815)

White (n = 2570)

P

280 (52.0%) 63.0 (56.0, 70.0) 220 (40.9%) 17.4 (10.6, 23.9) 7.4 (6.4, 8.5) 313 (59.4%) 28.8 (25.0, 33.0) 247 (45.9%) 153 (28.4%) 92 (17.1%) 51 (9.5%) 46 (8.6%) 477 (88.7%) 83 (15.4%) 14 (2.6%) 27 (5.0%)

758 (93.0%) 65.0 (58.0, 72.0) 309 (37.9%) 14.8 (8.1, 21.2) 7.3 (6.5, 8.5) 351 (44.2%) 32.3 (27.8, 38.4) 502 (61.6%) 292 (35.8%) 239 (29.3%) 128 (15.7%) 113 (13.9%) 763 (93.6%) 140 (17.2%) 46 (5.6%) 59 (7.2%)

1383 (53.8%) 70.0 (62.0, 77.0) 1142 (44.4%) 15.1 (7.7, 21.7) 6.8 (6.2, 7.7) 1199 (45.7%) 30.2 (26.3, 35.0) 1825 (71.0%) 1301 (50.6%) 991 (38.6%) 539 (21.0%) 271 (10.5%) 2388 (92.9%) 608 (23.7%) 357 (13.9%) 115 (4.5%)

b.001 b.001 .0032 b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001 .005 .001 b.001 b.001 .008

137.0 (120.0, 148.0) 70.0 (64.0, 80.0) 72.0 (64.0, 80.0) 31.6 (25.3, 40.3) 2.02 ± 0.8 1.4 (0.3-4.2) 3.0 (3.0-4.7)

138.0 (126.0, 150.0) 74.0 (68.0, 80.0) 72.0 (64.0, 80.0) 34.9 (26.3, 45.0) 2.25 ± 1.5 0.4 (0.1-2.0) 3.3 (3.0-7.6)

135.0 (122.0, 148.0) 70.0 (64.0, 80.0) 72.0 (64.0, 80.0) 33.8 (26.2, 42.2) 1.92 ± 0.61 0.4 (0.1-1.6) 3.0 (3.0-6.9)

b.001 b.001 .061 b.001 b.001 b.001 b.001

260 (48.3%) 302 (56.1%) 430 (79.9%) 203 (37.7%) 224 (41.6%) 263 (48.9%) 179 (33.3%) 56 (10.4%)

413 (50.7%) 499 (61.2%) 634 (77.8%) 412 (50.6%) 355 (43.6%) 523 (64.2%) 348 (42.7%) 97 (11.9%)

1263 (49.1%) 1414 (55.0%) 2060 (80.2%) 1320 (51.4%) 909 (35.4%) 1501 (58.4%) 1131 (44.0%) 216 (8.4%)

.656 .008 .339 b.001 b.001 b.001 b.001 .008

332 (61.7%) 124 (23.0%) 67 (12.5%) 15 (2.8%)

424 (52.0%) 242 (29.7%) 86 (10.6%) 62 (7.6%)

1248 (48.6%) 571 (22.2%) 435 (16.9%) 282 (11.0%)

b.001

Data are presented as median (interquartile range), mean ± SD, or percentages. Abbreviations: CRP, C-reactive protein; ESA, erythropoietin-stimulating agent.

Follow-up by race/ethnicity Mean follow-up visits per year were similar to whites (15.4) for blacks (15.2, P = .32) and Hispanics (15.3, P = .70). Adherence to study medication was similar in the 3 groups based upon mean total injections received per year (14.0 in blacks vs 14.1 in Hispanics vs 14.3 in whites). Mean systolic blood pressure significantly declined in black patients (−0.23 mm Hg/year, P = .032) and white patients (−0.95 mm Hg/year, P b .001) but increased in Hispanic patients (+0.30 mm Hg, P = .037), and the between-group differences were all significant (P b .001 for interaction). There were different blood pressure patterns in patients who developed ESRD in comparison to patients who did not (Figures 1 and 2). Approximately 72.3% of black patients received new antihypertensive drugs during follow-up compared with 77.7% of Hispanics and 76.2% of whites (P = .036). Serious adverse events were less frequent among

Hispanic (53%) and black (57%) patients in comparison to white patients (64%, P b .001). Figure 1 depicts the changes in eGFR, serum creatinine and urine protein-creatinine ratio. Urine proteincreatinine ratio increased more significantly in blacks than whites (16.0% vs 8.4% per year, P b .001 for interaction) despite similar starting points; this difference was not seen in Hispanics (7.1% vs 8.4% per year, P = .49 for interaction). However, Hispanic patients started with a higher urine protein-creatinine ratio that remains stable during follow-up. Overall, the decline in eGFR was similar between the groups, although a steep incline in serum creatinine was seen as patients approached ESRD. Mean changes in serum HbA1C were similar between blacks and whites, and there were early differences in insulin use that were detectable at year 2 (46% black vs 40% Hispanics vs 39% white, P = .038) but not beyond this time. There were no changes in heart rate, serum

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Figure 1

Changes in blood pressure, renal function, and proteinuria before onset of ESRD only in patients who developed ESRD. Mixed-effects models were fitted that incorporated all observations available before the time of ESRD.

hemoglobin, or serum transferrin saturation during follow-up.

Outcomes by race A total of 650 patients developed ESRD, including 105 Hispanics (19.5%), 185 blacks (22.7%), and 360 whites (14.0%). The incidence rate of ESRD was higher among black patients at 10.1 (8.8, 11.7) per 100 patient-years and Hispanic patients at 9.3 (7.7, 11.3) compared with a rate of 6.1 (5.5, 6.8) per 100 patient-years in white (P b .001). Black (63.6 years, P b .001) and Hispanic (60.9 years, P b .001) patients were younger than whites (67.3 years) at onset of ESRD. Last available eGFR before ESRD was similar among the 3 groups (19.3 blacks vs 15.9 Hispanics vs 19.0 whites, P = .11 for difference). Among patients with ESRD, 43 (23.2%) of 185 of black patients and 20 (19.1%) of 105 of Hispanic patients had ≥1 nonfatal CV events before ESRD, which was not statistically different from the 91 (25.3%) of 360 of white patients (P = .412). These nonfatal events occurred a mean of 181 days before ESRD. Among patients with eventual ESRD, the monthly decline in eGFR was greater (0.41 mL/min per 1.73 m 2 per month [0.38-0.45]) than in patients who did not develop ESRD (0.07 mL/min per 1.73 m 2 per month [0.06-0.08]). Among those developing ESRD, eGFR declines were

similar in black or Hispanic patients versus white patients, but there was a faster eGFR decline in Hispanics who did not develop ESRD during the trial (Figure 2). After adjusting for factors predicting ESRD in TREAT 13 and factors predicting CV events in TREAT, 14 selfdescribed black patients still had a significantly higher risk of ESRD development (hazard ratio [HR] 1.71, 95% CI 1.42-2.07, P b .001). This is in contrast to Hispanic patients who had adjusted rates for ESRD that were similar to white patients (HR 1.03, 95% CI 0.81-1.29, P = .83). After adding serial interim measurements as timevarying covariates, the association between black race and ESRD remained (HR 1.55, 95% CI 1.28-1.87) (Table II). Using ESRD as a time-varying covariate, the development of ESRD was associated with a heightened adjusted risk of subsequent death compared with patients who did not develop ESRD (HR 3.77 [95% CI 3.06-4.64], P b .001). Mortality was numerically lower for black and Hispanic patients both before and after ESRD (Table III), but this was not statistically significant (P for interaction = .19).

Cardiovascular events Black patients had lower adjusted rates for mortality, coronary revascularization, and MI; Hispanic patients had lower adjusted rates for MI than whites. The mortality

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Figure 2

Changes in blood pressure, renal function, and proteinuria before final visit only in patients who did not develop ESRD. Mixed-effects models were fitted that incorporated all observations available before the time of the final visit of the study.

Table II. Multivariable models for association of race on risk of ESRD Hispanic vs white Models Unadjusted Model 1 Model 2 Model 3 Model 4

HR 1.53 1.34 1.02 1.03 1.01

(1.23-1.91) (1.08-1.67) (0.81-1.30) (0.80-1.32) (0.79-1.29)

Black vs white P

b.001 .009 .85 .82 .95

HR 1.65 1.50 1.68 1.61 1.60

(1.38-1.97) (1.26-1.80) (1.38-2.04) (1.32-1.96) (1.31-1.96)

Incidence rates (per 100 patient-years) P

Hispanic

Black

White

P

b.001 b.001 b.001 b.001 b.001

9.3 (7.7-11.3)

10.1 (8.8-11.7)

6.1 (5.5-6.8)

b.001

Model 1, adjusted for race, age, and sex; model 2, adjusted for model 1 covariates and additional baseline variables including body mass index, insulin use, eGFR, serum urea nitrogen, log (urinary protein-creatinine ratio), serum albumin, prior stroke, prior peripheral arterial disease, prior heart failure, cardiac arrhythmia, serum hemoglobin, log (serum ferritin), serum C-reactive protein, history of acute kidney injury, duration of diabetes, systolic blood pressure, and diastolic blood pressure; model 3, model 2 covariates and time-updated variables including systolic blood pressure, log (urinary protein-creatinine ratio), HbA1c, and eGFR as time-varying covariates; model 4, model 3 covariates and postbaseline nonfatal CV events (MI, stroke, and heart failure).

rate was lower in black (5.2/100 patient-years) and Hispanic patients (4.8/100 patient-years) compared to white patients (7.5/100 patient-years) pre-ESRD. Cardiovascular events were similar or less frequent among black and Hispanic patients than in white patients (Table III). Among the patients who developed ESRD, the post-ESRD mortality rate was also lower among black (19.2/100 patient-years) and Hispanic (19.5/100 patient--

years) patients compared to white (37.4/100 patient-years) patients. There were no differences between the groups for stroke, heart failure, and resuscitated sudden death. On a relative basis, the incidence rate for ESRD was higher than the rate for death in blacks and Hispanics. This contrasts the higher incidence rate of death than ESRD among whites. After removing patients from follow-up at

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Table III. Incidence rates and multivariable models for association between race on risk of death and CV events Incidence rates (per 100 patient-years) Outcomes

White

All-cause death 9.3 CV death 5.9 Stroke 1.7 MI 3.3 Heart failure 5.0 Coronary 2.5 revascularization Resuscitated sudden death 1.6 ESRD † 6.1 Renal composite † 13.6

(8.6-10.1) (5.3-6.5) (1.4-2.1) (2.9-3.8) (4.5-5.6) (2.1-2.9)

Hispanic 6.4 3.6 0.8 1.4 3.9 1.6

(5.2-8.0) (2.7-4.8) (0.4-1.5) (0.9-2.3) (2.9-5.2) (1.0-2.5)

P .003 .002 .026 .001 .010 .06

Black 6.3 4.2 1.9 1.9 4.7 1.5

(5.3-7.5) (3.4-5.2) (1.3-2.6) (1.3-2.6) (3.8-5.8) (1.0-2.1)

Hispanics vs whites HR⁎

P b.001 .003 .68 .001 .591 .008

0.86 0.74 0.46 0.49 1.03 0.73

(0.66-1.10) (0.53-1.04) (0.23-0.91) (0.29-0.83) (0.73-1.46) (0.43-1.23)

Blacks vs whites HR⁎

P .23 .08 .02 .008 .87 .24

(1.3-1.9) 1.3 (0.8-2.1) .44 1.7 (1.2-2.3) .836 0.79 (0.43-1.46) .45 (5.5-6.8) 9.3 (7.7-11.3) b.001 10.1 (8.8-11.7) b.001 1.02 (0.81-1.30) .85 (12.7-14.5) 14.4 (12.3-16.7) .42 14.7 (13.1-16.6) .228 0.98 (0.82-1.18) .84

0.80 0.79 1.03 0.56 1.05 0.60

(0.65-0.98) (0.61-1.02) (0.68-1.57) (0.38-0.81) (0.80-1.37) (0.39-0.93)

P .03 .07 .87 .003 .72 .02

1.12 (0.73-1.72) .60 1.68 (1.38-2.04) b.001 1.24 (1.06-1.44) .006

⁎ Each fully adjusted model includes race, age, sex, heart failure, log (urinary protein-creatinine ratio), serum C-reactive protein, electrocardiographic abnormality, serum albumin, coronary heart disease, arrhythmia, serum HbA1C, blood reticulocytes, serum urea nitrogen, insulin use, cerebrovascular disease, loop diuretic use, serum hemoglobin, smoking status, blood transfusion, heart rate (per 10 beats), peripheral artery disease, body mass index (per 10 kg/m2), blood white cell count, hyperuricemia/gout, gastrointestinal bleeding in past 5 years, systolic blood pressure (per 10 mm Hg), eGFR (per 10 mL/min per 1.73 m2), lung disease, diabetes complications, duration of diabetes, and treatment randomization (darbepoetin alfa vs placebo). † The ESRD and renal composite models used the renal model variables detailed in Table II. Renal composite was a predefined composite end point that consists of time to first of ESRD or all-cause mortality.

the time of any interim nonfatal CV event, there remained a significant difference in the adjusted risk for ESRD among black patients (HR 1.46 [95% CI 1.17-1.82]).

Discussion Severe renal disease requiring renal replacement therapy disproportionately impacts black and Hispanic patients. The explanations for these disparities have included biological differences, access to care, comorbid illnesses, SES, lifestyle habits, and competing risks due to better overall survival among minority CKD patients who happen to be younger. 3 Although these factors leading to disparity are quite important to mitigate among predialysis patients, clinicians should search for novel strategies to prevent disease progression. In a contemporary-treated population with diabetes, CKD, and anemia, we have demonstrated a 53% higher risk of ESRD among black patients despite similar follow-up visits, reasonably controlled hypertension, and well-managed diabetes. This difference persisted after adjusting for demographic differences, clinical conditions, medications, and established surrogate measures of quality of care such as blood pressure control and HbA1C. As an internal control, black and Hispanic patients had similar to lower risks of CV morbidity and death than whites further suggesting that this population was adequately treated. We also examined eGFR at the time of ESRD, the occurrence of interim CV events and death, and markers of compliance, and none of these factors appeared to explain this excess risk of ESRD among blacks. Among Hispanic patients, the unadjusted risk of ESRD was higher than white patients, but this difference did not remain significant after adjusting for many of these similar factors. As in other studies, the development of ESRD

increased the risk of subsequent death almost 4-fold regardless of race. The use of the trial-based population in TREAT attempts to support the hypothesis that risk for ESRD among blacks extends beyond access to care, blood pressure control, diabetes management, and competing risks of mortality and morbidity, as have been reported widely. Despite the inherent limitations of this population, this ESRD difference would be magnified in the community where these disparities are greater. Several other observations are consistent with our findings. The US Renal Data System has captured virtually every patient who receives treatment for ESRD since 2002 and was linked to the Southern Community Cohort Study, which followed up approximately 80,000 black and white patients enrolled in clinics serving lower SES patients. Black patients had a 3.5-fold increased risk of ESRD compared with whites despite similar SES, and similar predictors of ESRD were confirmed. The AfricanAmerican Study of Kidney Disease and Hypertension enrolled only black patients and excluded those with diabetes 15 and demonstrated varied progression to ESRD over a 9-year period. The intensity of blood pressure control did not attenuate this progression, although use of ACE inhibitors was required as inclusion criteria for study enrollment. The overall proportion of patients (17%) progressing to ESRD in TREAT was higher than in other clinical trial and population cohorts, likely a reflection of the combination of diabetes and anemia with a mean eGFR at baseline of 34 mL/min per 1.73 m 2. Our study demonstrates a similar slope of decrements in eGFR in blacks and whites, which is contrary to the findings of an unselected population in Kaiser Permanente. 16 Moreover, the patients who did not develop ESRD had relatively stable renal function during follow-up

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in all groups, suggesting a cohort of patients who may remain stable for a period of time. A recent study confirmed that even a modest rate of decline in eGFR is a strong predictor of ESRD. 17 Although modest differences in systolic blood pressure existed during follow-up among races, this did not adequately explain the propensity of blacks to develop ESRD. Interestingly, the urinary protein-creatinine ratio increased more in black patients than in other groups, and this event was independently associated with ESRD development. Although proteinuria may be a reflection of vascular-based injuries and confers increased risk for CV and renal events, 18-20 black patients in TREAT had more proteinuria despite less interim CV events; nevertheless, proteinuria may be an additional marker to identify at-risk black patients earlier in CKD trajectory. The similar (or better) CV outcomes of blacks in TREAT diminishes the possibility of competing risks as an explanation for the disparity in ESRD, as previously suggested. 21 Most patients did not experience a CV event before ESRD, and these events did not explain the excess risk among blacks or whites with a competing risk analysis. Subsequent mortality post-ESRD was lower in blacks and Hispanics compared to whites, which may be a reflection of predialysis access to care and contributes to recent reports on variable postdialysis risks between blacks and whites. 22,23 Moreover, the inclusion of younger patients in TREAT supplements findings of studies in the older Medicare population. Given the persistent risk of ESRD among black patients despite adjusting for many of the factors used to explain these differences in prior publications, continued efforts are required to attenuate this risk. Alternative explanations include genetic factors such as G1 and G2 variants of APOL1, 24 transforming growth factor β, 25 nonmuscle myosin heavy chain type II isoform A, 26 and rheumatologic disorders such as lupus that may lead to inflammation. Apolipoprotein L1 recently identified black patients at risk for more rapid decline in eGFR 27 but is not as predictive of eGFR declines in diabetic kidney disease, a factor that may not be as important given the misclassification of cause of CKD in up to 25% of patients with diabetes. 28 However, even among patients with 2 APOL1 gene risk variants, there may be a role for addressing modifiable risk factors as a strategy to attenuate progression to ESRD. 29 Societal and patient-level factors such as health literacy, stress, maladaptive coping mechanisms, lifestyle habits (including but not limited to nutritional and physical activity pattern), and patient mistrust in the system are proposed as additional factors contributing to the racial differences in ESRD; however, these factors are difficult to measure in large cohorts. There are several limitations of our study that merit discussion. The patients all had advanced CKD, diabetes, and anemia, which impacts generalizability to a less ill population. Criteria for initiation of renal replacement

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therapy were not standardized. The follow-up period is relatively short, and there may be alternative factors that influence ESRD risk during long-term follow-up or before enrollment. The lack of consent for DNA extraction makes it difficult to assess genetic factors that may influence risk. Socioeconomic, behavioral, and physiological factors were not assessed in the studied population. Despite similar access to care via protocol-specific visit schedules, residual differences existed with regard to blood pressure and diabetes management and control as well as proteinuria, all of which were adjusted for in the multivariable models; however, other disparities in access to care may persist and cannot be measured. The proportion of the population who was Hispanic was smaller than the other 2 groups and patients who enter clinical trials may not be representative of the general population. Self-reporting of black race might be inaccurate in Latin American countries, although N90% of blacks were in North America; moreover, patients could only check 1 box for race/ethnicity. Finally, factors that influence differential mortality after ESRD is better analyzed in other cohorts due to limited power. In conclusion, self-reported black patients with diabetes, anemia, and CKD are much more likely to develop ESRD as compared to self-reported white patients, even after adjusting for confounding factors. The excess risk of ESRD in the setting of lower to similar risk of CV morbidity among blacks and reasonably controlled blood pressure and diabetes is concerning. Developing novel strategies for early management of these patients predialysis and for prognostication will be crucial next steps as we attempt to reduce disparities.

Disclosures Dr Pfeffer reports receiving consulting fees from Abbott, Amgen, AstraZeneca, Biogen, Boehringer Ingelheim, Boston Scientific, Bristol-Myers Squibb, Centocor, CVRx, Genentech, Cytokinetics, Daiichi Sankyo, Genzyme, Medtronic, Novartis, Roche, Sanofi-Aventis, Servier, and VIA Pharmaceutics and grant support from Amgen, Baxter, Celladon, Novartis, and Sanofi-Aventis and being named coinventor on a patent for the use of inhibitors of the renin-angiotensin system in selected survivors of MI; Dr Burdmann, receiving consulting fees from Amgen and Sigma Pharma and grant support from Amgen and Roche; Dr Kewalramani, being employee of and owning stock in Amgen; Dr Eckardt, receiving consulting fees from Amgen and Lecture and consultancy fees from Abbott, Affymax, Amgen, Astellas, Astra Zeneca, Johnson & Johnson, Roche, Sandoz/Hexal, SigmTau, and Vifor and grant support from Fresenius; Dr Ivanovich, receiving consulting fees from Amgen, Baxter, Biogen, and Reata; Dr Levey, receiving grant support from Amgen; Dr Lewis, receiving grant support from Amgen; Dr McMurray, receiving grant support from

8 Lewis et al

Amgen; Dr Parfrey, receiving consulting and lecture fees from Amgen and lecture fees from Ortho Biotech; Dr Solomon, receiving grant support from Amgen; and Dr Toto, receiving consulting and lecture fees from Amgen and grant support from Novartis, Reata, and Abbott; there are no conflicts for Dr Brian Claggett.

References 1. USRDS. United States Renal Data System Annual Data Report 2013: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. 2013. 2. Cowie CC, Port FK, Wolfe RA, et al. Disparities in incidence of diabetic end-stage renal disease according to race and type of diabetes. N Engl J Med 1989;321(16):1074-9. 3. Lipworth L, Mumma MT, Cavanaugh KL, et al. Incidence and predictors of end stage renal disease among low-income blacks and whites. PLoS One 2012;7(10):e48407. 4. Lora CM, Daviglus ML, Kusek JW, et al. Chronic kidney disease in United States Hispanics: a growing public health problem. Ethn Dis 2009;19(4):466-72. 5. McClellan W, Tuttle E, Issa A. Racial differences in the incidence of hypertensive end-stage renal disease (ESRD) are not entirely explained by differences in the prevalence of hypertension. Am J Kidney Dis 1988;12(4):285-90. 6. Hossain MP, Goyder EC, Rigby JE, et al. CKD and poverty: a growing global challenge. Am J Kidney Dis 2009;53(1):166-74. 7. Hsu CY, Lin F, Vittinghoff E, et al. Racial differences in the progression from chronic renal insufficiency to end-stage renal disease in the United States. J Am Soc Nephrol 2003;14(11):2902-7. 8. Powe NR, Melamed ML. Racial disparities in the optimal delivery of chronic kidney disease care. Med Clin North Am 2005;89(3):475-88. 9. Robbins JM, Vaccarino V, Zhang H, et al. Socioeconomic status and type 2 diabetes in African American and non-Hispanic white women and men: evidence from the Third National Health and Nutrition Examination Survey. Am J Public Health 2001;91(1):76-83. 10. Shoham DA, Vupputuri S, Kaufman JS, et al. Kidney disease and the cumulative burden of life course socioeconomic conditions: the Atherosclerosis Risk in Communities (ARIC) study. Soc Sci Med 2008;67(8):1311-20. 11. Pfeffer MA, Burdmann EA, Chen CY, et al. A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. N Engl J Med 2009;361(21):2019-32. 12. Pfeffer MA, Burdmann EA, Chen CY, et al. Baseline characteristics in the Trial to Reduce Cardiovascular Events With Aranesp Therapy (TREAT). Am J Kidney Dis 2009;54(1):59-69. 13. Desai AS, Toto R, Jarolim P, et al. Association between cardiac biomarkers and the development of ESRD in patients with type 2 diabetes mellitus, anemia, and CKD. Am J Kidney Dis 2011;58(5):717-28.

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14. McMurray JJ, Uno H, Jarolim P, et al. Predictors of fatal and nonfatal cardiovascular events in patients with type 2 diabetes mellitus, chronic kidney disease, and anemia: an analysis of the Trial to Reduce cardiovascular Events with Aranesp (darbepoetin-alfa) Therapy (TREAT). Am Heart J 2011;162(4):748-55. 15. Li L, Astor BC, Lewis J, et al. Longitudinal progression trajectory of GFR among patients with CKD. Am J Kidney Dis 2012;59(4): 504-12. 16. Derose SF, Rutkowski MP, Crooks PW, et al. Racial differences in estimated GFR decline, ESRD, and mortality in an integrated health system. Am J Kidney Dis 2013;62(2):236-44. 17. Coresh J, Turin TC, Matsushita K, et al. Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality. JAMA 2014;311(24):2518-31. 18. Gutierrez OM, Judd SE, Muntner P, et al. Racial differences in albuminuria, kidney function, and risk of stroke. Neurology 2012;79(16):1686-92. 19. McClellan WM, Warnock DG, Judd S, et al. Albuminuria and racial disparities in the risk for ESRD. J Am Soc Nephrol 2011;22(9): 1721-8. 20. Gutierrez OM, Khodneva YA, Muntner P, et al. Association between urinary albumin excretion and coronary heart disease in black vs white adults. JAMA 2013;310(7):706-14. 21. Derose SF, Rutkowski MP, Levin NW, et al. Incidence of end-stage renal disease and death among insured African Americans with chronic kidney disease. Kidney Int 2009;76(6):629-37. 22. Kucirka LM, Grams ME, Lessler J, et al. Association of race and age with survival among patients undergoing dialysis. JAMA 2011;306(6):620-6. 23. Arce CM, Goldstein BA, Mitani AA, et al. Trends in relative mortality between Hispanic and non-Hispanic whites initiating dialysis: a retrospective study of the US Renal Data System. Am J Kidney Dis 2013;62(2):312-21. 24. Foster MC, Coresh J, Fornage M, et al. APOL1 variants associate with increased risk of CKD among African Americans. J Am Soc Nephrol 2013;24(9):1484-91. 25. Suthanthiran M, Gerber LM, Schwartz JE, et al. Circulating transforming growth factor-beta1 levels and the risk for kidney disease in African Americans. Kidney Int 2009;76(1):72-80. 26. Kao WH, Klag MJ, Meoni LA, et al. MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nat Genet 2008;40(10):1185-92. 27. Parsa A, Kao WH, Xie D, et al. APOL1 risk variants, race, and progression of chronic kidney disease. N Engl J Med 2013;369(23): 2183-96. 28. Freedman BI, Langefeld CD, Lu L, et al. Differential effects of MYH9 and APOL1 risk variants on FRMD3 association with diabetic ESRD in African Americans. PLoS Genet 2011;7(6):e1002150. 29. Freedman BI, Skorecki K. Gene-Gene and Gene-Environment Interactions in Apolipoprotein L1 Gene-Associated Nephropathy. Clin J Am Soc Nephrol 2014;9(11):2006-13.

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Appendix A. Repeated analysis that includes the additional 2.9% of patients along with the white patients to allow for comparisons of outcomes to black and Hispanic patients Supplementary Table I. Baseline characteristics by black, Hispanic, or white/other Hispanic (n = 538) USA/Canada (%) Age (y) Women (%) Known duration of diabetes (y) HbA1C (%) Retinopathy (%) Body mass index CV disease history (%) Coronary artery disease Heart failure MI Stroke Hypertension Peripheral artery disease Atrial fibrillation (%) Current smoker (%) Blood pressure (mm Hg) Systolic Diastolic Heart rate (beats/min) eGFR Serum creatinine (mg/dL) Urine protein-creatinine ratio (g/g) CRP Medication (%) Insulin Oral hypoglycemic agents ACE inhibitor or ARB β-Blocker Aldosterone receptor blocker Statin Aspirin Prior ESA use

Black (n = 815)

280 (52.0%) 63.0 (56.0-70.0) 220 (40.9%) 17.4 (10.6-23.9) 7.4 (6.4-8.5) 313 (59.4%) 28.8 (25.0-33.0) 247 (45.9%) 153 (28.4%) 92 (17.1%) 51 (9.5%) 46 (8.6%) 477 (88.7%) 83 (15.4%) 14 (2.6%) 27 (5.0%)

758 (93.0%) 65.0 (58.0-72.0) 309 (37.9%) 14.8 (8.1-21.2) 7.3 (6.5-8.5) 351 (44.2%) 32.3 (27.8-38.4) 502 (61.6%) 292 (35.8%) 239 (29.3%) 128 (15.7%) 113 (13.9%) 763 (93.6%) 140 (17.2%) 46 (5.6%) 59 (7.2%)

137.0 (120.0-148.0) 70.0 (64.0-80.0) 72.0 (64.0-80.0) 31.6 (25.3-40.3) 168.0 (132.6-212.2) 1.4 (0.3-4.2) 3.0 (3.0-4.7)

138.0 (126.0-150.0) 74.0 (68.0-80.0) 72.0 (64.0-80.0) 34.9 (26.3-45.0) 176.8 (141.4-229.8) 0.4 (0.1-2.0) 3.3 (3.0-7.6)

260 (48.3%) 302 (56.1%) 430 (79.9%) 203 (37.7%) 224 (41.6%) 263 (48.9%) 179 (33.3%) 56 (10.4%)

413 (50.7%) 499 (61.2%) 634 (77.8%) 412 (50.6%) 355 (43.6%) 523 (64.2%) 348 (42.7%) 97 (11.9%)

White/other⁎ (n=2685)

P

1477 (55.0%) 70.0 (62.0-76.0) 1197 (44.6%) 15.1 (7.9-21.6) 6.8 (6.2-7.7) 1199 (45.7%) 30.0 (26.1-34.9) 1893 (70.5%) 1346 (50.1%) 1016 (37.8%) 562 (20.9%) 288 (10.7%) 2491 (92.8%) 625 (23.3%) 365 (13.6%) 118 (4.4%)

b.001 b.001 .002 b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001 .006 .002 b.001 b.001 .005

135.0 (122.0-148.0) 70.0 (64.0-80.0) 72.0 (64.0-80.0) 33.8 (26.3-42.2) 159.1 (132.6-203.3) 0.4 (0.1-1.6) 3.0 (3.0-6.7)

b.001 b.001 .047 b.001 b.001 b.001 b.001

1316 (49.0%) 1492 (55.6%) 2159 (80.4%) 1375 (51.2%) 965 (35.9%) 1578 (58.8%) 1186 (44.2%) 232 (8.6%)

.640 .016 .260 b.001 b.001 b.001 b.001 .016

Data are presented as median (interquartile range), mean ± SD, or percentages. Abbreviations: CRP, C-reactive protein; ESA, erythropoietin-stimulating agent. ⁎ This group includes 2570 whites, 78 Asians, 11 Japanese, 9 Native Hawaiian or Pacific Islanders, 9 other, 5 American Indian or Alaskans, and 3 Aborigines.

Supplementary Table II. Multivariable models for association of race on risk of ESRD Hispanic vs white/other Models Unadjusted Model 1 Model 2 Model 3 Model 4

HR 1.52 1.34 1.03 0.95 0.84

(1.23-1.89) (1.08-1.67) (0.82-1.29) (0.75-1.20) (0.67-1.07)

Black vs white/other

P b.001 .009 .82 .66 .16

HR 1.64 1.50 1.72 1.56 1.54

(1.38-1.96) (1.26-1.80) (1.43-2.07) (1.30-1.89) (1.28-1.86)

Incidence rates (per 100 patient-years) P

Hispanic

Black

White

P

b.001 b.001 b.001 b.001 b.001

9.3 (7.7-11.3)

10.1 (8.8-11.7)

6.2 (5.6-6.8)

b.001

Model 1, adjusted for race, age, and sex; model 2, adjusted for model 1 covariates and additional baseline variables including body mass index, insulin use, eGFR, serum urea nitrogen, log (urinary protein-creatinine ratio), serum albumin, prior stroke, prior peripheral arterial disease, prior heart failure, cardiac arrhythmia, serum hemoglobin, log (serum ferritin), serum C-reactive protein, history of acute kidney injury, systolic blood pressure, and diastolic blood pressure; Model 3, model 2 covariates and time-updated variables including systolic blood pressure, log (urinary protein-creatinine ratio), and eGFR as time-varying covariates; Model 4, model 3 covariates and postbaseline nonfatal CV events (MI, stroke, and heart failure).

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Supplementary Table III. Incidence rates and multivariable models for association between race on risk of death and CV events Incidence rates (per 100 patient-years) Outcomes All-cause death CV death Stroke MI Heart failure Coronary revascularization Resuscitated sudden death ESRD † Renal Composite †

White/other 9.0 (8.3-9.7) 5.7 (5.2-6.3) 1.7 (1.4-2.1) 3.2 (2.8-3.7) 5.0 (4.4-5.6) 2.5 (2.1-2.9) 1.5 (1.3-1.9) 6.2 (5.6-6.8) 13.4 (12.5-14.3)

Hispanic 6.4 3.6 0.8 1.4 3.9 1.6 1.3 9.3 14.4

(5.2-8.0) (2.7-4.8) (0.5-1.5) (0.9-2.3) (2.9-5.2) (1.0-2.5) (0.8-2.1) (7.7-11.3) (12.3-16.7)

P .006 .004 .029 .001 .11 .07 .51 b.001 .33

Black 6.3 4.2 1.9 1.9 4.7 1.5 1.7 10.1 14.7

(5.3-7.5) (3.4-5.2) (1.3-2.6) (1.3-2.6) (3.8-5.8) (1.0-2.1) (1.2-2.3) (8.8-11.7) (13.1-16.6)

Hispanics vs white/other

Black vs white/other

HR⁎

HR⁎

P b.001 .007 .63 .002 .66 .009 .71 b.001 .16

0.85 0.72 0.53 0.51 0.86 0.67 0.81 1.03 1.11

(0.67-1.08) (0.53-0.99) (0.27-1.01) (0.31-0.85) (0.62-1.17) (0.42-1.09) (0.47-1.38) (0.82-1.29) (0.94-1.32)

0.80 0.80 1.17 0.64 1.03 0.61 1.05 1.72 1.13

(0.66-0.97) (0.63-1.02) (0.80-1.71) (0.45-0.91) (0.81-1.30) (0.41-0.92) (0.71-1.55) (1.43-2.07) (0.99-1.30)

⁎ Each fully adjusted model includes race, age, sex, heart failure, log (urinary protein-creatinine ratio), serum C-reactive protein, electrocardiographic abnormality, serum albumin, coronary heart disease, arrhythmia, serum HbA1C, blood reticulocytes, serum urea nitrogen, insulin use, cerebrovascular disease, loop diuretic use, serum hemoglobin, smoking status, blood transfusion, heart rate (per 10 beats), peripheral artery disease, body mass index (per 10 kg/m2), blood white cell count, hyperuricemia/gout, gastrointestinal bleeding in past 5 years, systolic blood pressure (per 10 mm Hg), eGFR (per 10 mL/min per 173 m2), lung disease, diabetes complications, and treatment randomization (darbepoetin alfa vs placebo). † The ESRD and renal composite model used the renal model variables detailed in Supplementary Table II. Renal composite was a predefined composite end point that consists of time to first of ESRD or all-cause mortality.

Appendix B. Additional methods The TREAT was a prospective, randomized, doubleblind, placebo-controlled trial that enrolled 4,038 patients with type 2 diabetes mellitus, eGFR of 20 to 60 mL/min per 1.73 m 2 (calculated using the 4-variable Modification of Diet in Renal Disease Study formula), and iron-replete anemia (hemoglobin level ≤11.0 g/dL and transferrin saturation of N15%). Patients were randomized to darbepoetin alfa or placebo and followed up for mean of 2.4 years, and overall, no significant difference was observed in either the coprimary (CV composite of death, MI, heart failure, stroke, or myocardial ischemia) or the renal composite (death or end-stage renal disease) end points. However, there was a 2-fold increase in stroke with randomization to darbepoetin alfa. Blood and urine samples collected at baseline on all patients were analyzed for creatinine (used for eGFR calculation), HbA1C, fasting glucose, lipid profile, and urine protein-creatinine ratio. Comorbid illness, behavioral and psychosocial factors, and medications were assessed at baseline. Blood pressure and heart rate were obtained (after the patient was seated or semirecumbent for at least 5 minutes) at baseline and at each follow-up visit, which occurred every 2 to 4 weeks. Mean systolic and diastolic blood pressures were assessed monthly. Serum creatinine was measured as frequent as every 2 weeks throughout follow-up, and eGFR was calculated using 4-variable Modification of Diet in Renal Disease Study equation. Nonfatal CV events included MI, stroke, heart failure, and hospitalization for myocardial ischemia. The statistical testing for online Supplementary Figures 1 and 2 are detailed below. To investigate the changes in time

leading up to ESRD, mixed-effects models were fitted that incorporated all observations available before the time of ESRD for systolic blood pressure, serum creatinine, eGFR, and urinary protein-to-creatinine ratio. For each observation for each patient, the number of days before ESRD at which the observation was obtained was modeled via restricted cubic splines to allow for a flexible, potentially nonlinear relationship over time. Random-effect intercept terms at the patient level were incorporated to allow for within-patient correlation. Additional mixed-effects model were fit, which further included data from patients who did not experience ESRD. For these patients, the explanatory variable was calculated as the number of days before the end of follow-up for ESRD. Model 1 was adjusted for age and sex. Model 2 added clinical variables and factors known to be predictive for developing ESRD in the TREAT renal model. These factors included body mass index, insulin use, eGFR, serum urea nitrogen, log (urinary protein-creatinine ratio), serum albumin, prior stroke, prior peripheral arterial disease, prior heart failure, cardiac arrhythmia, serum hemoglobin, log (serum ferritin), serum C-reactive protein, history of acute kidney injury, systolic blood pressure, and diastolic blood pressure. Model 3 further adjusted for renal model and added other time-updated factors that may mediate the association between race and ESRD, including frequency of study-related clinical visits, serial systolic blood pressure, serial proteinuria, and serial eGFR during follow-up. Model 4 further adjusted for interim nonfatal CV events. To account for the competing risk of death, a sensitivity analysis was performed in which all patients with a nonfatal CV event were excluded to identify a healthier cohort and analysis repeated.

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Appendix C. Additional baseline characteristics of patients stratified by race/ethnicity Table. .

Diabetes—laser treatment CV disease history (%) Amputations Pacemaker AICD Former smoker (%) Serum albumin (g/dL) Screening serum hemoglobin (g/dL) Blood white blood cells Blood platelets Serum transferrin saturation (%) Serum ferritin Serum total cholesterol(mg/dL) Serum LDL Serum HDL Serum triglycerides (mg/dL) Medication (%) Vitamin K antagonist Oral iron Intravenous iron Investigator type Nephrologists Cardiologist Endocrinologist/diabetologist Internal or family medicine Other

Hispanic (n = 538)

Black (n = 815)

203 (37.7%) 247 (45.9%) 44 (8.2%) 23 (4.3%) 3 (0.6%) 179 (33.3%) 3.8 (3.5-4.1) 10.5 (9.8-10.9) 6.9 (5.7-8.3) 255.0 (206.0-310.0) 23.0 (18.0-29.0) 134.0 (63.0-268.0) 174.7 (146.8-210.7) 90.0 (67.0-118.0) 45.0 (39.0-55.0) 175.0 (123.5-241.5)

226 (27.7%) 502 (61.6%) 56 (6.9%) 31 (3.8%) 8 (1.0%) 342 (42.0%) 3.9 (3.6-4.2) 10.3 (9.6-10.9) 6.1 (4.9-7.5) 243.0 (200.0-292.0) 23.0 (18.0-28.0) 152.0 (78.0-319.0) 171.7 (145.8-204.7) 89.0 (68.0-114.0) 50.0 (41.0-61.0) 130.0 (96.0-184.0)

White/other (n = 2685)

P

745 (27.7%) 1893 (70.5%) 137 (5.1%) 160 (6.0%) 46 (1.7%) 1046 (39.0%) 4.1 (3.8-4.3) 10.5 (9.9-11.0) 6.8 (5.5-8.2) 236.0 (190.0-287.0) 23.0 (18.0-28.0) 127.0 (65.0-240.0) 167.7 (139.8-198.7) 82.0 (61.0-109.0) 45.0 (37.0-55.0) 161.0 (113.0-239.0)

.0001 .0001 .0086 .029 .059 .0056 .0001 .0003 .0001 .0001 .43 .0001 .0001 .0001 .0001 .0001 .0001 .022 .10 .0001

18 (3.3%) 235 (43.7%) 6 (1.1%)

30 (3.7%) 310 (38.0%) 7 (0.9%)

229 (8.5%) 1163 (43.3%) 49 (1.8%)

15 (2.8%) 67 (12.5%) 124 (23.0%) 332 (61.7%) 0 (0.0%)

62 86 242 424 1

285 (10.6%) 451 (16.8%) 594 (22.1%) 1319 (49.1%) 36 (1.3%)

(7.6%) (10.6%) (29.7%) (52.0%) (0.1%)

Data are presented as median (interquartile range), mean ± SD, or percentages. Abbreviations: AICD, automatic implantable cardioverter-defibrillator; LDL, low-density lipoprotein; HDL, high-density lipoprotein.

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Supplementary Figure 1

A, Proportion of patients with systolic blood pressure ≥160 mm Hg during follow-up by race. B, Proportion of patients with diastolic blood pressure ≥100 mm hg during follow-up by race.

Supplementary Figure 2

Proportion of patients with HbA1C ≥10% during follow-up by race.