The 558,000 individuals in the U.S. receiving maintenance dialysis experience tremendous mortality, with a median survival of ∼48 months (1). Comorbid diabetes is present in >60% of incident cases of dialysis-dependent kidney failure and is associated with higher mortality rates, primarily driven by cardiovascular causes (1,2). Renal impairment limits the use of many antihyperglycemic agents, rendering insulin the mainstay diabetes treatment for most patients receiving dialysis. However, insulin-induced hypoglycemia is common due to autonomic neuropathy, hypoglycemia unawareness, and impaired renal gluconeogenesis (3). Management of glycemia is therefore challenging, and frequent oscillations between hyper- and hypoglycemia contribute to poor cardiovascular outcomes in patients with dialysis-dependent kidney failure (2,4).

Glucagon-like peptide 1 receptor agonists (GLP-1 RAs) improve glycemic control without causing hypoglycemia and confer cardiovascular risk reduction on people with type 2 diabetes. Some GLP-1 RAs do not require dose adjustments for kidney insufficiency; however, no clinical trials in the U.S. have evaluated GLP-1 RA safety, tolerability, or cardiovascular efficacy in the hemodialysis population, a population with a cardiovascular mortality rate exceeding that of the general population five- to sevenfold (1). We undertook this study to describe the utilization patterns of antihyperglycemic agents, including GLP-1 RAs, among U.S. patients with hemodialysis-dependent kidney failure.

Using 2012–2017 data from the U.S. Renal Data System, a claims-based national registry that captures the vast majority of U.S. dialysis patients, we identified adults with diabetes receiving in-center hemodialysis at the start of each calendar quarter who had continuous Medicare coverage during the preceding 180 days. During each calendar quarter, we used Medicare Part D prescription drug claims to determine the percentage of patients with prescription fills for antihyperglycemic agents recommended for use in dialysis-dependent kidney failure by medication class and, separately, stratified by concomitant insulin fill status. We also described the clinical characteristics of the most contemporary (October 2017) quarterly cohort. This study was approved by the University of North Carolina at Chapel Hill Institutional Review Board (no. 18-0297). A waiver of consent was granted.

Insulin was the most prescribed antihyperglycemic agent, followed by sulfonylureas (SUs), dipeptidyl peptidase 4 inhibitors (DPP-4is), and thiazolidinediones, in October 2017 (Fig. 1A). From 2012 to 2017, DPP-4i use rose, GLP-1 RA use rose minimally, and SU use fell. Less than 5% of patients received combination therapy of insulin plus a second agent. DPP-4is and SUs were the most common agents used with insulin (Fig. 1B). Only 752 individuals (0.6%) filled a prescription for GLP-1 RAs in October 2017; 66% of those individuals also filled a prescription for insulin.

Figure 1

Antihyperglycemic prescription fills in the U.S. hemodialysis population. Panels A and B display the percentage of adult patients with dialysis-dependent kidney failure and diabetes with an antihyperglycemic agent prescription fill between January 2012 and October 2017 by medication class (A) and stratified by concomitant insulin prescription fill status (use, solid lines; nonuse, dashed lines) (B).

Figure 1

Antihyperglycemic prescription fills in the U.S. hemodialysis population. Panels A and B display the percentage of adult patients with dialysis-dependent kidney failure and diabetes with an antihyperglycemic agent prescription fill between January 2012 and October 2017 by medication class (A) and stratified by concomitant insulin prescription fill status (use, solid lines; nonuse, dashed lines) (B).

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Disregarding kidney disease as an atherosclerotic cardiovascular disease (ASCVD) risk factor, 64% of study patients met American Diabetes Association (ADA) ASCVD criteria, and 98% were at high risk for ASCVD regardless of antihyperglycemic treatment class (Table 1). Compared with people prescribed insulin alone, individuals prescribed GLP-1 RAs without insulin were younger, more likely to be obese and non-White, and had fewer claims for hypoglycemia and cardiovascular hospitalizations (Table 1). Of the full patient cohort, only 9.5% of patients had an endocrinology claim in the prior 6 months.

Table 1

Patient characteristics

All (N = 129,865)No drug (N = 75,903)Insulin (N = 43,212)Insulin alone (N = 38,735)SU (N = 8,473)DPP-4i (N = 5,981)TZD (N = 1,210)AGI (N = 122)GLP-1 RA (N = 752)GLP-1 RA + insulin (N = 497)GLP-1 RA + no insulin (N = 255)
Age, years, mean ± SD 64 ± 13 64 ± 13 62 ± 12 62 ± 13 65 ± 11 66 ± 12 66 ± 12 67 ± 11 60 ± 11 60 ± 11 60 ± 11 
Sex of patient (female), n (%) 60,626
(46.7) 
34,538
(45.5) 
21,481
(49.7) 
19,355
(50.0) 
3,514
(41.5) 
2,825
(47.2) 
476
(39.3) 
60
(49.2) 
388
(51.6) 
246
(49.5) 
137
(53.7) 
Race, n (%)            
 White 71,690
(55.2) 
38,673
(51.0) 
26,716
(61.8) 
23,909
(61.7) 
5,204
(61.4) 
3,492
(58.4) 
701
(57.9) 
69
(56.6) 
462
(61.4) 
327
(65.8) 
135
(52.9)* 
 Black 48,911
(37.7) 
32,087
(42.3) 
13,509
(31.3) 
12,259
(31.6) 
2,462
(29.1) 
1,781
(29.8) 
350
(28.9) 
28
(23.0) 
226
(30.1) 
129
(26.0) 
97
(38.0)* 
 Other 9,264
(7.1) 
5,143
(6.8) 
2,987
(6.9) 
2,567
(6.6) 
807
(9.5) 
708
(11.8) 
159
(13.1) 
25
(20.5) 
64
(8.5) 
41
(8.2) 
23
(9.0)* 
 Hispanic 24,849
(19.1) 
12,738
(16.8) 
9,416
(21.8) 
8,160
(21.1) 
2,166
(25.6) 
1,642
(27.5) 
323
(26.7) 
28
(23.0) 
171
(22.7) 
117
(23.5) 
54
(21.2) 
Obesity, n (%) 36,417
(28.0) 
18,783
(24.7) 
15,009
(34.7) 
13,413
(34.6) 
2,199
(26.0) 
1,625
(27.2) 
351
(29.0) 
33
(27.0) 
402
(53.5) 
281
(56.5) 
121
(47.5)* 
Prior kidney transplant, n (%) 6,306
(4.9) 
4,321
(5.7) 
1,739
(4.0) 
1,645
(4.2) 
174
(2.1) 
151
(2.5) 
29
(2.4) 
<11 21
(2.8) 
12
(2.4) 
<11 
Hypoglycemia hospitalization, n (%) 6,692
(5.2) 
3,521
(4.6) 
2,832
(6.6) 
2,625
(6.8) 
316
(3.7) 
223
(3.7) 
23
(1.9) 
<11 25
(3.3) 
16
(3.2) 
<11* 
Cardiologist claim, n (%) 74,295
(57.2) 
44,054
(58.0) 
24,698
(57.2) 
22,248
(57.4) 
4,309
(50.9) 
3,293
(55.1) 
576
(47.6) 
68
(55.7) 
425
(56.5) 
300
(60.4) 
125
(49.0)* 
Endocrinologist claim, n (%) 12,354
(9.5) 
4,883
(6.4) 
6,670
(15.4) 
6,016
(15.5) 
532
(6.3) 
834
(13.9) 
110
(9.1) 
22
(18.0) 
153
(20.3) 
112
(22.5) 
41
(16.1) 
ADA definition for ASCVD, n (%) 82,699
(63.7) 
47,659
(62.8) 
28,740
(66.5) 
25,845
(66.7) 
4,880
(57.6) 
3,874
(64.8) 
693
(57.3) 
84
(68.9) 
478
(63.6) 
328
(66.0) 
150
(58.8)* 
High risk for ASCVD, n (%) 127,037
(97.8) 
73,932
(97.4) 
42,589
(98.6) 
38,186
(98.6) 
8,280
(97.7) 
5,907
(98.8) 
1,185
(97.9) 
121
(99.2) 
747
(99.3) 
494
(99.4) 
253
(99.2) 
All (N = 129,865)No drug (N = 75,903)Insulin (N = 43,212)Insulin alone (N = 38,735)SU (N = 8,473)DPP-4i (N = 5,981)TZD (N = 1,210)AGI (N = 122)GLP-1 RA (N = 752)GLP-1 RA + insulin (N = 497)GLP-1 RA + no insulin (N = 255)
Age, years, mean ± SD 64 ± 13 64 ± 13 62 ± 12 62 ± 13 65 ± 11 66 ± 12 66 ± 12 67 ± 11 60 ± 11 60 ± 11 60 ± 11 
Sex of patient (female), n (%) 60,626
(46.7) 
34,538
(45.5) 
21,481
(49.7) 
19,355
(50.0) 
3,514
(41.5) 
2,825
(47.2) 
476
(39.3) 
60
(49.2) 
388
(51.6) 
246
(49.5) 
137
(53.7) 
Race, n (%)            
 White 71,690
(55.2) 
38,673
(51.0) 
26,716
(61.8) 
23,909
(61.7) 
5,204
(61.4) 
3,492
(58.4) 
701
(57.9) 
69
(56.6) 
462
(61.4) 
327
(65.8) 
135
(52.9)* 
 Black 48,911
(37.7) 
32,087
(42.3) 
13,509
(31.3) 
12,259
(31.6) 
2,462
(29.1) 
1,781
(29.8) 
350
(28.9) 
28
(23.0) 
226
(30.1) 
129
(26.0) 
97
(38.0)* 
 Other 9,264
(7.1) 
5,143
(6.8) 
2,987
(6.9) 
2,567
(6.6) 
807
(9.5) 
708
(11.8) 
159
(13.1) 
25
(20.5) 
64
(8.5) 
41
(8.2) 
23
(9.0)* 
 Hispanic 24,849
(19.1) 
12,738
(16.8) 
9,416
(21.8) 
8,160
(21.1) 
2,166
(25.6) 
1,642
(27.5) 
323
(26.7) 
28
(23.0) 
171
(22.7) 
117
(23.5) 
54
(21.2) 
Obesity, n (%) 36,417
(28.0) 
18,783
(24.7) 
15,009
(34.7) 
13,413
(34.6) 
2,199
(26.0) 
1,625
(27.2) 
351
(29.0) 
33
(27.0) 
402
(53.5) 
281
(56.5) 
121
(47.5)* 
Prior kidney transplant, n (%) 6,306
(4.9) 
4,321
(5.7) 
1,739
(4.0) 
1,645
(4.2) 
174
(2.1) 
151
(2.5) 
29
(2.4) 
<11 21
(2.8) 
12
(2.4) 
<11 
Hypoglycemia hospitalization, n (%) 6,692
(5.2) 
3,521
(4.6) 
2,832
(6.6) 
2,625
(6.8) 
316
(3.7) 
223
(3.7) 
23
(1.9) 
<11 25
(3.3) 
16
(3.2) 
<11* 
Cardiologist claim, n (%) 74,295
(57.2) 
44,054
(58.0) 
24,698
(57.2) 
22,248
(57.4) 
4,309
(50.9) 
3,293
(55.1) 
576
(47.6) 
68
(55.7) 
425
(56.5) 
300
(60.4) 
125
(49.0)* 
Endocrinologist claim, n (%) 12,354
(9.5) 
4,883
(6.4) 
6,670
(15.4) 
6,016
(15.5) 
532
(6.3) 
834
(13.9) 
110
(9.1) 
22
(18.0) 
153
(20.3) 
112
(22.5) 
41
(16.1) 
ADA definition for ASCVD, n (%) 82,699
(63.7) 
47,659
(62.8) 
28,740
(66.5) 
25,845
(66.7) 
4,880
(57.6) 
3,874
(64.8) 
693
(57.3) 
84
(68.9) 
478
(63.6) 
328
(66.0) 
150
(58.8)* 
High risk for ASCVD, n (%) 127,037
(97.8) 
73,932
(97.4) 
42,589
(98.6) 
38,186
(98.6) 
8,280
(97.7) 
5,907
(98.8) 
1,185
(97.9) 
121
(99.2) 
747
(99.3) 
494
(99.4) 
253
(99.2) 

Shown are patient characteristics by antihyperglycemic medication class as of October 2017. Unless otherwise specified in the column header, table columns are not mutually exclusive, and patients listed in a column may have filled prescriptions for multiple classes. t tests and χ2 tests were used for comparisons of individuals with GLP-1 RA fills who did not have concomitant insulin fills (GLP-1 RA without insulin) with individuals with insulin fills alone (insulin alone) (

*

P < 0.05). ASCVD is defined according to the ADA Standards of Medical Care in Diabetes (5) as a history of an acute coronary syndrome or myocardial infarction, stable or unstable angina, coronary heart disease with or without revascularization, other arterial revascularization, stroke, or peripheral artery disease assumed to be atherosclerotic in origin. Patients at high risk for ASCVD include those with end organ damage such as left ventricular hypertrophy or retinopathy or with multiple cardiovascular risk factors (e.g., advanced age, hypertension, smoking, dyslipidemia, and obesity). Kidney disease was excluded from the definition given that all patients had dialysis-dependent kidney failure. AGI, α-glucosidase inhibitors; TZD, thiazolidinedione.

While our study does have limitations (e.g., lack of data beyond 2017 and use of Medicare claims prescription data, which lack definitive adherence information), our findings show that despite increasing awareness of the untoward effects of hypoglycemia, insulin and SUs were the antihyperglycemic agents most prescribed to hemodialysis patients in 2017. Prescription of combination therapy with SU and insulin was three times more common than prescription of GLP-1 RAs, agents with no hypoglycemia risk in the general population (5). Although GLP-1 RAs have yet to be rigorously tested among individuals receiving dialysis, GLP-1 RAs have the potential to confer glycemic control without increasing hypoglycemia risk in these vulnerable patients who are at risk for hypoglycemia independent of diabetes status (2). Finally, according to the ADA Standards of Medical Care in Diabetes, 100% of people with type 2 diabetes treated with dialysis should receive GLP-1 RA therapy (5). Lack of clinical trials of GLP-1 RAs in the dialysis-dependent kidney disease population is a barrier to implementation of this potentially high-impact intervention.

In addition, our study emphasizes the need for collaboration between endocrinologists and nephrologists. We found that few individuals with dialysis-dependent kidney failure and comorbid diabetes had a recent endocrinology claim. This finding may relate to patient reluctance to engage in care outside of their burdensome thrice-weekly hemodialysis treatments and/or nephrologist discomfort with newer antihyperglycemic agents and may contribute to low use of GLP-1 RAs among hemodialysis patients. Optimizing diabetes care with newer agents, like GLP-1 RAs, that confer benefits beyond glycemia could improve both patient-reported and biomedical outcomes for individuals with dialysis-dependent kidney failure and represents an opportunity for interdisciplinary collaborations.

Acknowledgments. The data reported here were provided by the U.S. Renal Data System under Data Use Agreement 2018-23d to J.E.F.

Funding and Duality of Interest. M.M.A. and J.E.F. are supported by R01 HL152034, awarded by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH). M.M.A. reports receiving investigator-initiated research funding from the Renal Research Institute (a subsidiary of Fresenius Medical Care, North America), the Agency for Healthcare Research and Quality, and the NHLBI and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the NIH, and she reports receiving honoraria from the American Society of Nephrology (Journal of the American Society of Nephrology editorial fellow) and the International Society of Nephrology (Kidney International Reports statistical reviewer). J.E.F. reports receiving speaking honoraria from the American Society of Nephrology, the National Kidney Foundation, and multiple universities. She reports receiving research funding from the NHLBI and NIDDK, the Patient-Centered Outcomes Research Institute, the Robert Wood Johnson Foundation, and the Renal Research Institute (a subsidiary of Fresenius Medical Care, North America). She reports serving on a medical advisory board for Fresenius Medical Care, serving on a data safety monitoring board for the NIDDK, serving on an advisory committee to the NIDDK, and serving as a member of the Kidney Disease Improving Global Outcomes (KDIGO) Executive Committee (since 2020) and Kidney Health Initiative board of directors (since 2019). She is the Kidney Health Initiative patient preferences project chairperson (since 2019). She is on the American Journal of Kidney Diseases editorial board (2017–2021) and the Clinical Journal of the American Society of Nephrology editorial board (since 2017). She is a Nephrology Dialysis and Transplantation hemodialysis theme editor (since 2018), is on the Kidney Medicine editorial board (since 2019), and is a Kidney360 associate editor (since 2019). She reports receiving consulting fees from AstraZeneca and Fresenius Medical Care, North America. K.R.K. is supported by the University of North Carolina Department of Medicine and School of Medicine Physician Scientist Training Program. V.P., T.S., and J.B.B. are supported by UL1TR002489, awarded by the National Center for Advancing Translational Science of the NIH. T.S. receives investigator-initiated research funding and support as principal investigator (R01 AG056479) from the National Institute on Aging and as a co-investigator (R01 HL118255 and R01MD011680) from the NIH. He also receives salary support as Director of Comparative Effectiveness Research, NC TraCS Institute, UNC Clinical and Translational Science Award (UL1TR002489). He also receives support from the Center for Pharmacoepidemiology (current members: GlaxoSmithKline, UCB Biosciences, Takeda, AbbVie, and Boehringer Ingelheim), from pharmaceutical companies (Novo Nordisk), and from a generous contribution from Dr. Nancy A. Dreyer to the Department of Epidemiology, University of North Carolina at Chapel Hill. He owns stock in Novartis, Roche, and Novo Nordisk. J.B.B.’s contracted consulting fees and travel support for contracted activities are paid to the University of North Carolina by Novo Nordisk. He has grant support from Dexcom, NovaTarg Therapeutics, Novo Nordisk, Sanofi, Tolerion, vTv Therapeutics, and the NIH. He is a consultant to Alkahest, Altimmune, Anji Pharmaceuticals, AstraZeneca, Bayer, Boehringer Ingelheim, CeQur, Cirius Therapeutics, Inc., Dasman Diabetes Institute (Kuwait), Eli Lilly, Fortress Biotech, GentiBio, Glycadia Pharmaceuticals, Glyscend, Janssen, Mediflex, MedImmune, Medscape, Mellitus Health, Pendulum Therapeutics, Praetego, Stability Health, Valo Health, and Zealand Pharma. He has stocks/options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio Pharmaceuticals, Praetego, and Stability Health. No other potential conflicts of interest relevant to this article were reported.

This manuscript underwent privacy review by an NIDDK project officer and received clearance. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as official policy or interpretation of the U.S. government.

Author Contributions. K.R.K. contributed to study design, data interpretation, and drafting of the manuscript. V.P. contributed to study design, data collection, statistical analysis, data interpretation, and critical review of the manuscript. M.M.A., T.S., J.B.B., and J.E.F. participated in study design, data interpretation, and critical review of the manuscript. J.E.F. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the 82nd Scientific Sessions of the ADA, New Orleans, LA, 3–7 June 2022.

1.
United States Renal Data System
.
USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States
.
Bethesda, MD
,
National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases
,
2021
2.
Rhee
CM
,
Kalantar-Zadeh
K
,
Tuttle
KR
.
Novel approaches to hypoglycemia and burnt-out diabetes in chronic kidney disease
.
Curr Opin Nephrol Hypertens
2022
;
31
:
72
81
3.
Galindo
RJ
,
Beck
RW
,
Scioscia
MF
,
Umpierrez
GE
,
Tuttle
KR
.
Glycemic monitoring and management in advanced chronic kidney disease
.
Endocr Rev
2020
;
41
:
756
774
4.
Galindo
RJ
,
Ali
MK
,
Funni
SA
, et al
.
Hypoglycemic and hyperglycemic crises among U.S. adults with diabetes and end-stage kidney disease: population-based study, 2013-2017
.
Diabetes Care
2022
;
45
:
100
107
5.
American Diabetes Association Professional Practice Committee
.
Standards of Medical Care in Diabetes—2022
.
Diabetes Care
2021
;
45
(
Suppl. 1
):
S1
S264
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