contemporary management of diabetes focus on sglt2i and

Contemporary management of Diabetes focus on SGLT2i and GLP1-RA

12th Annual Orange County Symposium for

Cardiovascular Disease Prevention: Crossroads in Cardiovascular Disease Prevention

Yehuda Handelsman, MD, FACP, FNLA, FASPC, MACESaturday October 31, 2020

Yehuda Handelsman, MD, FACP, FNLA, FASPC, MACE

Medical Director & Principal investigator

Metabolic Institute of America

Program Chair & Director

18th WCIRDC 12/3-6/2020, Live-Interactive-Online5th Heart in Diabetes 6/18-20/2021, New City, NY

Solo practice

Endocrinology, Diabetes & Metabolism

Tarzana, California

• Research Grant - Amgen, Applied Therapeutic, AZ, BMS, BI, Gan & Lee, Lexicon Novo Nordisk,

Sanofi.

• Advisory/Consultant – Amarin, Amgen, Applied Therapeutic, AZ, BI, Esperion, Gilead, Janssen,

Merck, Merck-Pfizer, Novartis, Novo-Nordisk, Regeneron, Sanofi Vertis

• Speaker’s Bureau – Amarin, AZ, Janssen, Merck, Novo-Nordisk

Dr Handelsman & his immediate family do not have ownership

interest & or stocks of any Pharmaceutical or device company

Handelsman disclosures

Diabetes and Co-Morbidities

12th Annual Orange County Symposium

for Cardiovascular Disease Prevention: Crossroads in Cardiovascular Disease Prevention

Prevalence of total, diagnosed, and undiagnosed diabetes among US adults aged 20 and over, by age group: 2013-2016

Diabetes prevalence among US adults

*Type 2 diabetes accounts for approximately 90%-95% of all diagnosed cases of diabetes in the US.2

1. Mendola ND, et al. NCHS Data Brief. 2018;319:1-8. 2. Centers for Disease Control and Prevention. Type 2 diabetes. https://www.cdc.gov/diabetes/basics/type2.html. Updated August 15, 2018. Accessed January 9, 2019.

0

5

10

15

20

25

30

20-39 40-59 60 and older

Pe

rcen

tage

Diagnosed

Undiagnosed

1.81.7

11.1

5.2

21.0

7.2

3.5

16.3

28.2

Life expectancy for the US population declined from 2016 to 2017

Life expectancy

for the US

population

declined from

78.7 years in 2016 to 78.6 years in 2017

Murphy SL, et al. NCHS Data Brief. 2018;328:1-8.

Age-adjusted death rates for 7 of the 10 leading causes of

death increased

• Influenza: 5.9% increase

• Unintentional injuries: 4.2% increase

• Suicide: 3.7% increase

• Diabetes: 2.4% increase

• Alzheimer’s disease: 2.3%

• Stroke: 0.8%

• Chronic lower respiratory disease: 0.7%

Predictors of Strokes, MI, and HF in Patients with T2D

MI= myocardial infarction; HF= heart failure; T2D= type 2 diabetes

Rawshani A, et al. N Engl J Med. 2018;379:633-644.

Myocardial InfarctionStrokes Heart Failure

Increasing importance Increasing importance Increasing importance

T2DM- ASCVD and Heart Failure

If 5 RF were controlled(HgA1c, smoking, LDLc, BP,

albuminuria)HR for AMI–0.84 (0.75-0.93)

HR for stroke–0.95 (0.84-1.07)

Risk for Cardiovascular Events is Greatest When Both Diabetes and CKD Are Present

Foley RN, et al. J Am Soc Nephrol. 2005;16:489-495.

Incidence per

100 Patient-Years

x 2.8

x 2.3

x 1.7x 2.1

x 2.0

x 2.5

CHF=congestive heart failure; AMI=acute myocardial infarction;

CVA/TIA=cerebrovascular accident/transient ischemic attack;

PVD=peripheral vascular disease; ASVD=atherosclerotic vascular disease.

*ASVD was defined as the first occurrence of AMI, CVA/TIA, or PVD.

Practice Recommendations



Glucose Reduction-DPP4 Inhibitors, GLP-1 Receptor Agonists, and SGLT2 Inhibitors Added to Metformin

Absolute Changes from Baseline; Not Head-to-Head Trials

Davies MJ et al. Diabetes Care 2018;41:2669

2018 ADA-EASD Consensus & 2019 ADA Standards of Care: Glucose-Lowering Meds in T2DM - Overall Approach

Davies MJ et al. Diabetes Care 2018;41:2669-2701

2018 ADA-EASD Consensus & 2019 ADA Standards of Care: Glucose-Lowering Meds in T2DM – Established ASCVD / CKD


Management of Hyperglycemia In T2DM, 2018. A Consensus Report from ADA & EASD:

INTENSIFYING TO INJECTABLES


SGLT2 Inhibitors



SGLT2 InhibitorsCanagliflozin, Dapagliflozin, Empagliflozin, Ertugliflozin

Invokana [Package Insert] Janssen Pharmaceuticals, Inc. Titusville, NJ.; Lavalle-gonzález FJ, Januszewicz A, Davidson J, et al. Diabetologia. 2013; StenlöfK, Cefalu WT, Kim KA, et al. Diabetes Obes Metab. 2013;15(4):372-82; Burki TK. Lancet. 2012;379(9815):507.

Mechanism

Inhibits sodium-glucose transport protein subtype 2 (SGLT2) which is responsible for at least 90% of glucose reabsorption in the kidney causing blood glucose is eliminated in the urine

Efficacy On Average A1C 0.7-1.1%

AdvantagesInsulin-independent glucose reduction, Low risk of hypoglycemia, Weight loss (to 4% BW), Blood pressure-lowering

Disadvantages

Mild osmotic diuresis, initial Polyuria, potential lightheadedness, Genital Micotic infections (females≈10%), Increased LDL cholesterol,

ContraindicationsSevere kidney disease eGFR < 30 mL/min/1.73 m²

Glucose Control with SGLT2 Inhibitors

Placebo-Adjusted Change from Baseline

(Not Head-to-Head Trials)

*Absolute change from baseline (active-controlled trial).

1. Stenlof K, et al. Diabetes Obes Metab. 2013;15:372-382. 2. Ferrannini E, et al. Diabetes Care. 2010;33:2217-2224. 3. Roden M, et al. Lancet Diabetes Endocrinol. 2013;1:208-219. 4. Cefalu WT,

et al. Lancet. 2013;382:941-950. 5. Nauck MA, et al. Diabetes Care. 2011;34:2015-2022. 6. Haring HU, et al. Diabetes Care. 2014;37:1650-1659. 7. Yale J-F, et al. Diabetes Obes Metab.

2013;15:463-473. 8. Wilding JPH, et al. Ann Intern Med. 2012;156:405-415. 9. Rosenstock J, et al. Diabetes Care. 2014;37:1815-1823.

Monotherapy Add-on to Metformin Add-on to Insulin +/- OAs

Can1 Dap2 Emp3 Can4 Dap5 Emp6 Can7 Dap8 Emp9

Baseline A1C

(%)

8.1 7.8 7.9 8.1 8.2 7.9 8.2 8.6 8.3

Pla

ceb

o-a

dju

ste

d

A

1C

(%

)

*

*

1.1

-0.9

-0.4

-0.66-0.52 -0.57

-0.86

-0.64

-0.46

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

Weight Change with SGLT2 Inhibitors

Absolute Change from Baseline


W

eig

ht

(kg

) Monotherapy Add-on to Metformin Add-on to Insulin +/- OAs


-3.4

-4.0

-1.4

-3.2 -3.2

-1.6

-2.48 -2.46

-2.04

-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

1. Stenlof K, et al. Diabetes Obes Metab. 2013;15:372-382. 2. Ferrannini E, et al. Diabetes Care. 2010;33:2217-2224. 3. Roden M, et al. Lancet Diabetes Endocrinol. 2013;1:208-219. 4.

Cefalu WT, et al. Lancet. 2013;382:941-950. 5. Nauck MA, et al. Diabetes Care. 2011;34:2015-2022. 6. Haring HU, et al. Diabetes Care. 2014;37:1650-1659. 7. Yale J-F, et al. Diabetes Obes

Metab. 2013;15:463-473. 8. Wilding JPH, et al. Ann Intern Med. 2012;156:405-415. 9. Rosenstock J, et al. Diabetes Care. 2014;37:1815-1823.

Blood Pressure Changes with SGLT2 Inhibitors25



1. Stenlof K, et al. Diabetes Obes Metab. 2013;15:372-382. 2. Ferrannini E, et al. Diabetes Care. 2010;33:2217-2224. 3. Roden M, et al. Lancet Diabetes Endocrinol. 2013;1:208-219. 4.

Cefalu WT, et al. Lancet. 2013;382:941-950. 5. Nauck MA, et al. Diabetes Care. 2011;34:2015-2022. 6. Haring HU, et al. Diabetes Care. 2014;37:1650-1659. 7. Yale J-F, et al. Diabetes

Obes Metab. 2013;15:463-473. 8. Wilding JPH, et al. Ann Intern Med. 2012;156:405-415. 9. Rosenstock J, et al. Diabetes Care. 2014;37:1815-1823.

Monotherapy Add-on to Metformin Add-on to Insulin +/- OAs


-5.0-4.6

-6.4

-3.6-4.3

-6.7

-5.0 -5.2

-3.8

-8

-7

-6

-5

-4

-3

-2

-1

0

S

ysto

lic B

P (

mm

Hg

)

Key Outcomes in the CANVAS Program and EMPA-REG

Hazard ratio (95% CI)

1.00.5 2.0

Favors PlaceboFavors SGLT2i*CANVAS Program endpoints comparable with EMPA-REG OUTCOME.

0.25

CV death, nonfatal myocardial infarction, or nonfatal stroke

CANVAS Program

EMPA-REG OUTCOME

Nonfatal myocardial infarction

Progression to macroalbuminuria*

Renal composite*

Hospitalization for heart failure

CV death

Nonfatal stroke

CV death or hospitalization for heart failure

All-cause mortality

1. Zinman B et al. N Engl J Med. 2015; 373(22):2117-2128.; 2. Wanner K et al. N Engl J Med. 2016; 375(4):323-334.

DECLARE- TIMI 58

0.87 (95% CI, 0.74 to 1.01)*

CVOT: EMPA-REG (0% 1◦P) CANVAS (34% 1◦P) DECLARE (59%1◦P) CREDENCE (50%1◦P)

SGLT2-i Empagliflozin Canagliflozin Dapagliflozin Canagliflozin

3-P MACE 14% RRR(HR=0.86; 0.74-0.99)

14% RRR(HR=0.86; 0.75-0.97)

NS(HR=0.93; 0.84-1.03)

20% RRR(HR=0.80; 0.67-0.95)

CV Death 38% RRR(HR=0.62; 0.49-0.77)

NS(HR=0.87; 0.72-1.06)

NS(HR=0.98; 0.82-1.17)

22% RRR(HR=0.78; 0.61-1.00)

CV Death/HHF 34% RRR(HR=0.66; 0.55-0.79)

22% RRR(HR=0.78; 0.67-0.91)

17% RRR(HR=0.83; 0.73-0.95)

31% RRR(HR=0.69; 0.57-0.83)

All-cause death

32% RRRHR=0.68 (0.57-0.82)

NS(HR=0.93; 0.82-1.04)

NS(HR=0.83; 0.68-1.02)

Non-fatal MI NS(HR=0.87; 0.70-1.09)

NS(HR=0.85; 0.69-1.05)

NS(HR=0.89; 0.77-1.01)

Non-fatal Stroke

NS(HR=1.24; 0.92-1.67)

NS(HR=0.90; 0.71-1.15)

NS(HR=1.01; 0.84-1.21)

HHF 35% RRR(HR=0.65; 0.50-0.85)

33% RRR(HR=0.67; 0.52-0.87)

27% RRR(HR=0.73; 0.61-0.88)

39% RRR(HR=0.61; 0.47-0.80)

CKD Progress’n

39% RRR(HR = 0.61; 0.53-0.70)

40% RRR(HR=0.60; 0.47-0.77)

24% RRR(HR=0.76; 0.67-0.87)

30% RRR(HR=0.70; 0.59-0.82)

Time to first HHF – subgroup analysis by ASCVD

29

ASCVD, atherosclerotic cardiovascular disease; CI, confidence interval HHF, hospitalization for heart failure.

Zelnicker TA et al. Lancet. 2019;393(10166):31-39

HHF

Meta-analysis of SGLT2i Trials – Renal Composite

Zelniker TA, et al. Lancet. 2019;393(10166):31-39.

Improvement in CV Outcomes with Empagliflozin is Independent of Glycemic Control

Inzucchi SE, et al. Circulation. 2018;138(17):1904-1907.

SGLT2 Inhibitors and Potential CV Impact

Weight loss and

reduced visceral fat

Uric acid

Na+H+/IC

Na+ Shift

Inflammation &

Oxidative stress

SNS activity

Arterial

stiffnessGlucose

Blood pressure

&

Heart rate Plasma

Volume

Ang 1-7

AT2 receptor

Insulin

Resistance

Ketones

GLP1- receptor agonists



GLP-1 Receptor Agonists

FDA-Approved Agents

• Lixisenatide

• Dulaglutide

• Exenatide

• Exenatide ER

• Liraglutide

• Semaglutide

• Rybelsus

• (Albiglutide)

Key Features

• Injectable administration

• Mimic action of native GLP-1

• Increase glucose-dependent insulin secretion

• Suppress Endogenous Glucose production

• Reduces glucagon Level

• Slow gastric emptying

• Promote weight loss

• Correct known pathophysiologic defects in T2DM

ER, extended release; GLP-1, glucagon-like peptide 1.

Garber AJ, et al. Endocr Pract. 2013;19(suppl 2):1-48.

Monotherapy Add-on to Metformin Add-on to SU

Alb1 Dul2 Exe3 Exe

ER4

Lir5 Alb6 Dul7 Exe8 Exe

ER9

Lir10 Alb11,* Exe12 Exe

ER13,†

Lir14

Baseline A1C (%) 8.1 7.6 7.8 8.5 8.3 8.1 8.1 8.2 8.6 8.4 8.2 8.6 8.3 8.5

Glucose Control with GLP-1 Receptor Agonists

-1.0-0.9

-0.8-0.8

-1.4

-1.0

-0.7-0.9

-1.5-1.5 -1.5-1.4

-1.1

-1.5

-2

-1.5

-1

-0.5

0

Placebo-Adjusted Change from Baseline


*Metformin with or without SU or TZD. †Metformin with or without SU. ‡Absolute change from baseline (active-controlled trial).

1. Tanzeum (albiglutide) injection prescribing information. Research Triangle Park, NC: GlaxoSmithKline; 2014.

2. Umpierrez G, et al. Diabetes Care. 2014;37:2168-2176. 3. Moretto TJ, et al. Clin Ther. 2008;30:1448-1460. 4. Russell-Jones D, et al. Diabetes

Care. 2012;35:252-258. 5. Garber A, et al. Lancet. 2009;373:473-481. 6. Ahrén B, et al. Diabetes Care. 2014;37:2141-2148. 7. Dungan KM, et al.

Lancet. 2014;384:1349-1357. 8. DeFronzo RA et al. Diabetes Care. 2005;28:1092-1100. 9. Bergenstal RM, et al. Lancet. 2010;376:431-439. 10.

Pratley RE, et al. Lancet. 2010;375:1447-1456. 11. Pratley RE, et al. Lancet Diabetes Endocrinol. 2014;2:289-297. 12. Buse JB, et al. Diabetes Care.

2004;27:2628-2635. 13. Diamant M, et al. Lancet. 2010;375:2234-2243. 14. Marre M, et al. Diabet Med. 2009;26:268-278.

Pla

ce

bo-a

dju

ste

d

A

1C

(%

)

‡

‡

‡ ‡

‡

‡

‡

‡

Monotherapy Add-on to Metformin Add-on to SU

Alb1 Dul2 Exe3 Exe

ER4

Lir5 Alb6 Dul7 Exe8 Exe

ER9

Lir10 Alb11,* Exe12 Exe

ER13,†

Lir14

Weight Change with GLP-1 Receptor Agonists

-0.9-1.2

-0.6

-2.3-2.6

-1.6

-3.1-2.8

-2.6

-2-2.3

-0.2

-2.5

-3.4-4

-3

-2

-1

0

*Metformin with or without SU or TZD. †Metformin with or without SU.

1. Tanzeum (albiglutide) injection prescribing information. Research Triangle Park, NC: GlaxoSmithKline; 2014.

2. Umpierrez G, et al. Diabetes Care. 2014;37:2168-2176. 3. Moretto TJ, et al. Clin Ther. 2008;30:1448-1460. 4. Russell-Jones D, et al. Diabetes Care. 2012;35:252-258. 5. Garber A, et al. Lancet.

2009;373:473-481. 6. Ahrén B, et al. Diabetes Care. 2014;37:2141-2148. 7. Dungan KM, et al. Lancet. 2014;384:1349-1357. 8. DeFronzo RA et al. Diabetes Care. 2005;28:1092-1100. 9. Bergenstal

RM, et al. Lancet. 2010;376:431-439. 10. Pratley RE, et al. Lancet. 2010;375:1447-1456. 11. Pratley RE, et al. Lancet Diabetes Endocrinol. 2014;2:289-297. 12. Buse JB, et al. Diabetes Care.

2004;27:2628-2635. 13. Diamant M, et al. Lancet. 2010;375:2234-2243. 14. Marre M, et al. Diabet Med. 2009;26:268-278.

W

eig

ht

(kg

)



Blood Pressure Changes With Liraglutide

Monotherapy vs

Glimepiride

52 Weeks1

Add-on to

Metformin

26 Weeks2

Add-on to

Metformin

26 Weeks3

Add-on to

Sulfonylurea

26 Weeks4,5

Add-on to

Met + TZD

26 Weeks6

Add-on to

Met + SU

26 Weeks7

N 746 1091 665 1041 821 581

Treatment† Glim Lir Met Glim

+

Met

Lir+

Met

Sit+

Met

Lir+

Met

SU Rosi

+

SU

Lir+

SU

Rosi

+

Met

Lir+

Rosi+

Met

Met+

SU

Glar+

Met+

SU

Lir+

Met+

SU

*P<0.05 vs comparator.

†All liraglutide dosages shown are 1.8 mg QD.

1. Garber A, et al. Lancet. 2009;373:473-481. 2. Nauck M, et al. Diabetes Care. 2009;32:84-90.

3. Pratley RE, et al. Lancet. 2010;375:1447-1456. 4. Marre M, et al. Diabet Med. 2009;26:268-278.

5. Colagiuri S, et al. Diabetes. 2008;57(suppl 2): Abstr. 554-P. 6. Zinman B, et al. Diabetes Care. 2009;32:1224-1230. 7. Russell-Jones D, et al. Diabetologia. 2009;52:2046-2055

-1.8-2.3

-0.7

0.4

-0.9 -0.9 -1.1

0.5

-3.6

-2.3

-0.7

-2.8

-5.6

-4.0

-6

-5

-4

-3

-2

-1

0

1

S

ysto

lic B

P

(mm

Hg)

*

*

*

*

GLP1 RA Meta-analysis + REWIND

REWIND data were added to meta-analysis of Zelniker et al. Circulation 2019:2022

Trials Patients Events Weights HR (95% CI)

ELIXA 6068 805 13.4 1.02 (0.89, 1.17)

LEADER 9340 1302 21.1 0.87 (0.78, 0.97)

SUSTAIN 6 3297 254 4.1 0.74 (0.58, 0.95)

EXSCEL 14752 1744 28.9 0.91 (0.83, 1.00)

HARMONY 9463 766 12.8 0.78 (0.68, 0.90)

REWIND 9901 1257 19.7 0.88 (0.79, 0.99)

OVERALL 0.88 (0.84, 0.93)

0.5 1 2

Gerstein HC et al. Presented at ADA 2019 June 10

GLP-1 Receptor Agonists and CVT OutcomesGLP-1 RA Composite

MACECV Death Nonfatal

MINonfatal

StrokeHHF All-cause

Mortality

LEADER1 Liraglutide 0.87* 0.78* 0.86 0.89 0.87 0.85*

SUSTAIN-62

Semaglutide 0.74* 0.98 0.88 0.61* 1.11 1.05

EXSCEL3 Exenatide 0.91 0.88 0.97 0.85 0.94 0.86

REWIND4 Dulaglutide 0.88* 0.91 0.96 0.76 0.93 0.90

*Statistically significant1. Marso et al. NEJM. 2016;375(4):311-22, 2. Marso et al. NEJM. 2016;375(19):1834-1844, 3. Holman et al. NEJM 2017; 377:1228-1239, 4. Gerstein HC, et al. Lancet2019;394(10193):121-130

Primary and subgroup analyses for REWIND study

H Gerstein et al, Lancet 2019

Potential MOA of GLP-1 RAs Beneficial Effects on CV Outcomes?

• More research is needed to determine why some GLP-1 RAs have favorable effects on mortality and other CV end points—these effects are only partially explained by favorable effects on glycemic control, blood pressure, and weight

. Modified from Drucker DJ. Cell Metab. 2016;24:15-30.

No Effect of GLP-1 RA’s on Hospitalizations for HF

ELIXA LEADER

SUSTAIN-6EXSCEL

HR=0.96 (0.75–1.23)

15

10

5

00 12 24 36

Perc

en

t

Month

HR=0.87 (0.73–1.05)

HR=0.94 (0.78–1.13)

HR=1.11 (0.77–1.61)

Placebo

Lixisenatide

Semaglutide

Placebo

Placebo

Liraglutide

Exenatide

Placebo

REWIND: Renal Composite OutcomeNew Macroalbuminuria, 30% fall in eGFR, or Renal Replacement Rx

Gerstein HC et al. Lancet 2019; On Line June 10

HR 0.85 (95% CI 0.77, 0.93)

P = 0.0004

HR 0.85 (95% CI 0.77, 0.93) P=0.0004

SGLT2i in HFrEF Management



DAPA-HF Primary Outcome in

Patients with HFrEF

DAPA-HFNo diabetes/diabetes subgroup: Primary endpoint

*Defined as history of type 2 diabetes or HbA1c ≥6.5% at both enrollment and randomization visits.

https://professional.heart.org/professional/ScienceNews/UCM_505121_DAPA-HF---Results-in-Non-Diabetic-Patients-Clinical-Trial-Details.jsp

Dapagliflozin (n=2373)

Placebo(n=2371)

All patients 386/2373 502/2371

Type 2 diabetes at baseline*

Yes 215/1075 271/1064

No 171/1298 231/1307

HR(95% CI)

0.74 (0.65, 0.85)

0.75 (0.63, 0.90)

0.73 (0.60, 0.88)

1.251.00.80.5

Placebo BetterDapagliflozin Better

Change in NT-proBNP From Baseline to Month 8*

-196

101

-250

-200

-150

-100

-50

0

50

100

150

Dapagliflozin Placebo

pg

/mL

Median Baseline NT-proBNP (pg/mL)

Placebo

SD±2944

1428

(IQR 857–2665)

1446

(IQR 857–2641)

SD±2387

*Exploratory endpoint.

IQR=interquartile range; SD=standard deviation.

McMurray JJV et al. N Engl J Med. 2019;381(21):1995-2008.

Difference at month 8:

–303 pg/mL (95% CI: –457 to –150)

P<0.001

Placebo

EMPEROR-Reduced: Time to Cardiovascular Death or Hospitalization for Heart Failure (Primary Endpoint)

40% higher

than in DAPA-HFPlacebo

PlaceboEmpagliflozin

Cu

mula

tive

incid

ence

(%)

462 patients with event

Rate: 21.0/100 patient-years

Placebo

Empagliflozin

EMPEROR-Reduced: Time to Cardiovascular Death or Hospitalization for Heart Failure (Primary Endpoint)

PlaceboEmpagliflozin

Cu

mula

tive

incid

ence

(%)





HR 0.75

(95% CI 0.65, 0.86)

P < 0.0001

SGLT2i in CKD Management



CREDENCE Primary Outcome:ESKD, Doubling of Serum Creatinine, or Renal or CV Death

0

5

10

15

20

25

0 26 52 78 104 130 156 182

Parti

cip

an

ts w

ith

an

even

t (%

)

Months since randomization

Hazard ratio, 0.70 (95% CI, 0.59–0.82)P = 0.00001

6 12 18 24 30 36 42

340 participants

245 participants

Placebo

Canagliflozin

No. at risk

Placebo 2199 2178 2132 2047 1725 1129 621 170

Canagliflozin 2202 2181 2145 2081 1786 1211 646 196

Parti

cip

an

ts w

ith

an

even

t (%

)

KEY RENAL INCLUSIONS:• eGFR 30 to 90 mL/min/1.73 m2

• UACR 300 to 5000 mg/g

Perkovic V, et al. N Engl J Med 2019;380:2295

HJ Heerspink et al. N Engl J Med 2020;383:1436-1446.

DAPA-CKD Primary and Secondary Outcomes.Primary- A composite of a sustained decline in the estimated GFR of at least

50%, end-stage kidney disease, or death from renal or cardiovascular causes

HJ Heerspink et al. N Engl J Med 2020;383:1436-1446.

DAPA-CKD Change from Baseline

in Estimated GFR.

HF and CKD

The Cardiorenal Syndrome



Renal and CV Disease are Closely Interconnected in T2D

55CV = cardiovascular; Na = sodium; RAAS = renin-angiotensin-aldosterone system; T2D = type 2 diabetes mellitus.

Adapted from Connelly K et al. Cell Metab. 2018;28:813-815.

Renal and cardiac systems should be considered together

Diabetes

Na+ Retention

Hypervolemia

RAAS activation

Neurohumoral Activation

Inflammation

Ischemia

Altered Energetics

http://www.shutterstock.com/subscribe.mhtml

CKD and Risk of Cardiovascular Events and Hospitalization

56

*CV event defined as hospitalization for coronary heart disease, heart failure, ischemic stroke and peripheral arterial disease. Based on data from the Kaiser Permanente Renal Registry (N=1,120,295 adults with no dialysis or renal transplantation; 52 years mean age; 55% women; 2.84 years median follow-up)

CKD = chronic kidney disease; CV = cardiovascular; eGFR = estimated glomerular filtration rate; ESRD = end-stage renal disease.

Go AS, et al. N Engl J Med. 2004;351:1296-1305.

• ESRD substantially increases the risk of death, CVD, and the use of specialized healthcare

• Reduced eGFR is also associated with increased risk of death, CV events, and hospitalization

CV Events* Hospitalization

2.113.65

11.29

21.8

36.6

0

5

10

15

20

25

30

35

40

≥60 45-59 30-44 15-29 <15

Ag

e-S

tan

dard

ized

Rate

of

Card

iov

asc

ula

r E

ven

ts

(per

100 p

ers

on

/yr)

Estimated GFR (ml/min/1.73m2)

No. of Events 73,108 34,690 18,580 8809 3824

13.54 17.22

45.26

86.75

144.61

0

20

40

60

80

100

120

140

160

≥60 45-59 30-44 15-29 <15

Ag

e-S

tan

dard

ized

Rate

of

Ho

sp

itali

za

tio

n(p

er

100 p

ers

on

/yr)

Estimated GFR (ml/min/1.73m2)

No. of Events 366,757 106,543 49,177 20,581 11,593

Incidence rates of HF are higher in those with CKD compared to those without

Declining Renal Function is Associated with Incident HF

57

Data from the Framingham Heart Study were used to evaluate associations between reduced eGFR and incident HF.

CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; HF = heart failure; HFpEF = heart failure with preserved ejection fraction; HFrEF = heart failure with reduced ejection fraction.

Nayor M, et al. Eur J Heart Fail. 2017;19:615-623.

Cu

mu

lati

ve i

ncid

en

ce o

f H

F

Years

CKD HFrEF

CKD HFpEF

No CKD HFrEF

No CKD HFpEF

0 2 4 6 8 10 12

8%

6%

4%

2%

0%

7281764479948318859688458983

No. at Risk

511596648711783854906CKDNo CKD

-10

-8

-6

-4

-2

0

0 26 52 78 104 130

Ad

just

ed m

ean

ch

ange

fro

m b

asel

ine

(SE

)in

eG

FR(m

L/m

in/1

.73

m²)

Weeks after randomization

Placebo

Empagliflozin

Empagliflozin

Placebo2.1 ml/min/1.73m2/year

(95% CI: 1.5 – 2.7)P < 0.0001

During double-blind treatment

EMPEROR-Reduced: Slope of Decline in Glomerular Filtration Rate — Hierarchical Endpoint #3

Mean c

hange fro

m b

aselin

e in

eG

FR

(m

l/m

in/1

.73 m

2) – 2

– 4

– 6

– 8

0

0 4 52 76 100 124

– 10

Weeks After Randomization

Difference in slope

In 966 patients, eGFR was

reassessed at the end of the trial

23-42 days after the withdrawal of

double-blind therapy, thus allowing

unconfounded assessment of the

effects of treatment. Over 16

months, eGFR deteriorated by

– 4.2 ml/min/1.73 m2

on placebo

– 0.9 m/min/1.73 m2 on

empagliflozin

P < 0.00014 12 32

Practice Recommendations-

2019-20 Update



*In the ADA Standards of Medical Care in Diabetes 2020, SGLT2 inhibitors are recommended in patients with T2D and established HF to reduce risk of HHF2

ASCVD, atherosclerotic cardiovascular disease; HFrEF, heart failure with reduced ejection fraction; HHF, hospitalisation for heart failure

1. Buse JB et al. Diabetes Care 2020;43:487; 2. American Diabetes Association. Diabetes Care 2020;43:S1; 3. Davies MJ et al. Diabetes Care 2018;41:2669

ADA–EASD- 2019 Update- Consensus Report recommends

SGLT2i & GLP1-ra for patients with T2D and ASCVD risk

“SGLT2 inhibitors are recommended in patients

with T2D and HF, particularly those with HFrEF,

to reduce HHF, MACE and CV death*

SGLT2 inhibitors should be used to prevent HHF,

MACE and CV death, and the progression of CKD

in patients with T2D and CKD”1

ADA–EASD 2019 Consensus Report update

These recommendations have been also incorporated into the ADA Standards of Medical Care in Diabetes 20202 and

should be considered in conjunction with the ADA–EASD 2018 consensus report3

Changes for 2019 based on new information

J Buse et al, Diabetes Care / Diabetologia 2020

1. Addition of GLP-1RA or SGLT2i independent of A1c

2. Consideration of GLP-1RA in selected patients for primary prevention

3. Targeting patients with HF and diabetic nephropathy with SGLT2i

Important modifications in the 2019 ADA-EASD Position

Guidelines Support Use of SGLT2 Inhibitors & GLP1-ra

to Prevent ASCVD Risk in Patients With T2D

aPosition statement that does not represent an update of the 2017 ACC/AHA/HFSA heart failure guideline update.

AACE=American Association of Clinical Endocrinologists; ACE=American College of Endocrinology; ADA=American Diabetes Association; HFSA=Heart Failure Society of America; SGLT2i=sodium-glucose cotransporter-2 inhibitor.

1. American Diabetes Association. Diabetes Care. 2020;43(suppl 1):S1-S212; 2. Garber AJ et al. Endocr Pract. 2020;26(1):107-139; 3. Dunlay SM et al. Circulation. 2019;140(7):e294-e324.

Both ADA and AACE/ACE

recommend the use of an SGLT2iwith demonstrated CV benefit or

proven efficacy for prevention of hospitalization for HF in

patients with T2D independent of A1C or glycemic control1,2

ADA1 AACE/ACE2

A joint statement from the AHA/HFSA also suggests SGLT2i use as part of

a prevention strategy in patients with T2D at high risk for HF3,a

New in 2020

THANK YOU QUESTIONS?

Nava Handelsman

contemporary management of diabetes focus on sglt2i and

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