CKD in Type 2 Diabetes Webinar: Contemporary Approaches to Renoprotection

Virtual Webinar
June 26, 2021
Chronic Kidney Disease in Type 2 Diabetes:
Contemporary Approaches to Renoprotection
Supported by an educational grant from Bayer HealthCare Pharmaceuticals, Inc.

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Susanne B. Nicholas, MD, MPH, PhD
Associate Professor of Medicine
Nephrologist and Hypertension Specialist
Department of Medicine, Nephrology
Division
David Geffen School of Medicine at UCLA
Los Angeles, California
Faculty
George L. Bakris, MD
Professor of Medicine
Director, Comprehensive Hypertension
Center
University of Chicago Medicine
Chicago, Illinois
Vivian A. Fonseca, MD, FRCP
Tullis-Tulane Alumni Chair in Diabetes
Chief, Section of Endocrinology
Tulane University School of Medicine
New Orleans, Louisiana

Disclosures
The faculty reported the following financial relationships or relationships to products or devices they or
their spouse/life partner have with commercial interests related to the content of this CME/CE activity:
George L. Bakris, MD, has disclosed that he has received funds for research support from Alnylam,
Bayer HealthCare, Novo Nordisk, Quantum Genomics, and Vascular Dynamics; and consulting fees from
Alnylam, Astra Zeneca, Bayer HealthCare, Horizon, Ionis, KBP Biosciences, Merck, Novo Nordisk,
Quantum Genomics, and Vascular Dynamics.
Vivian A. Fonseca, MD, FRCP, has disclosed that he has received funds for research support paid to his
institution from Fractyl and Jaguar Gene Therapy; consulting fees and fees for honoraria lectures from
Abbott, AstraZeneca, Asahi, Bayer, Intarcia, Novo Nordisk, Sanofi-Aventis, and Takeda; and has
ownership interest in Amgen, BRAVO4Health, and Mellitus.
Susanne B. Nicholas, MD, MPH, PhD, has disclosed that she has received funds for research support
from Bayer, Goldfinch Bio, and Travere; consulting fees from Amgen, AstraZeneca, Bayer, Boehringer
Ingelheim/Lilly, and Janssen; and fees for non-CME/CE services from AstraZeneca, Bayer, Boehringer
Ingelheim/Lilly, and Janssen.

Program Agenda
 Chronic Kidney Disease in Type 2 Diabetes: Overview
‒ Vivan A. Fonseca, MD, FRCP
 Chronic Kidney Disease in Type 2 Diabetes: Pathogenesis
‒ Susanne B. Nicholas, MD, MPH, PhD
 Diabetic Kidney Disease and Treatment: Where Are We Now?
‒ George L. Bakris, MD

Vivian A. Fonseca MD, FRCP
Tullis-Tulane Alumni Chair in Diabetes
Chief, Section of Endocrinology
Tulane University School of Medicine
New Orleans, Louisiana
Overview

Why Treat Advanced CKD: Is it Too Late?
 Prevent/delay progression to dialysis/treatment
 Prevent progression of other complications (blindness, amputation)
 Prevent CV events, including CHF
 Improve quality of life
 Reduce cost of care of ESRD

Diabetic Kidney Disease Is a Serious Matter
 Kidney disease is a frequent diabetic complication
‒ Type 1 diabetes ~30%
‒ Type 2 diabetes ~40%
 Diabetes is the most common cause of CKD and ESRD in the developed and
developing worlds
‒ Diabetes prevalence in US ESRD patients: 66%-86% depending on race
 Diabetic kidney disease amplifies CVD risk
‒ Much of diabetes-associated excess CVD risk occurs in diabetic kidney disease
National Kidney Foundation. https://www.kidney.org/atoz/content/diabetes

Screening for Diabetic Kidney Disease
 Early detection is critical
 All patients with T1D should be screened for microalbuminuria beginning 5 yr after diagnosis and
annually thereafter
 All patients with T2D should be screened for microalbuminuria at diagnosis with a spot UACR or
timed urine collection.
‒ If negative, repeat annually thereafter
‒ If positive, a spot UACR of 2 out of 3 specimens collected over 3-6 mo (to account for normal
variability)
‒ Normal range is <30 mg/g
‒ Calculation of eGFR
‒ eGFR persistently <60 mL/min/1.73 m2 is considered abnormal
ADA. Diabetes Care. 2021;44:S151.

ESRD Incidence Counts and Rates by Primary Diagnosis
in the US
 Prevalence rates of ESRD
attributable to DKD are
progressively increasing despite
incidence rates that are
stabilizing or improving
USRDS Annual Data Report. Vol 2 – ESRD. 2014. Slide credit: clinicaloptions.com
*Rates adjusted for age, gender, and race.
50
40
30
20
10
0
Number
of
Patients
(in
Thousands)
Diabetes
Hypertension
Glomerulonephritis
Cystic Kidney
Counts
Rates*
50
40
30
20
10
Rate/Million
Population
82 86 94 98 02 06
90 10

Prevalence of CKD in the US Population by eGFR and
Albuminuria Stages
 Percentage of US population by eGFR and albuminuria
category (KDIGO 2009 and NHANES III [1988-1994])
 Combined stages G3-G5 and A2-A3 account for 13.9% of
the population
 Stages G3-G5 and A2-A3 account for 6.7% and 9.1% of
the population, respectively
Albuminuria Stages, Description, and Range (mg/g) [by UACR]
A1 A2 A3
All
Optimal and high-optimal High Very high
<10 10-29 30-299 >300
eGFR
Stages,
Description,
and
Range
(mL/min/1.73
m
2
)
G1 High and optimum
>105 23.6 5.7 1.9 0.1 31.4
90-104 20 4.7 1.7 0.3 26.7
G2 Mild
75-89 17.3 4.1 1.6 0.2 23
60-74 8.2 2.7 1.3 0.1 12.2
G3a Mild to moderate 45-59 2.5 1.1 0.8 0.2 4.7
G3b Moderate to severe 30-44 0.6 0.4 0.4 0.2 1.5
G4 Severe 15-29 0.1 0.1 0.1 0.1 0.4
G5 ESRD <15 0 0 0 0.1 0.1
All 72.2 18.8 7.8 1.3 100
Levey. Lancet. 2012;379:165. Slide credit: clinicaloptions.com

*P <.001
75.0
60.0-74.9
45.0-59.9
<45.0
eGFR (mL/min/1.73 m2)
12
Cardiovascular Outcomes Worsen With CKD
Progression: Postmyocardial Infarction Prognosis
 3-yr follow-up of patients with MI in the VALIANT trial (N = 14,527)
Estimated
Event
Rate
(%)
Anavekar. NEJM. 2004;351:1285. Slide credit: clinicaloptions.com
0
10
20
30
40
50
60
Composite
Endpoint*
Death
From CV
Causes
Reinfarction CHF Stroke Resuscitation

*Adjusted for age, sex, race/ethnicity, previous cardiovascular disease, blood pressure category, use of antihypertensive medication, diabetes mellitus, smoking status,
body mass index, physical activity level, low-density lipoprotein, high-density lipoprotein cholesterol, low triglyceride level, and C-reactive protein category.
eGFR
(mL/min/1.73 m2)
Normal
ACR <30 mg/g
Micro-
albuminuria
ACR 30-299 mg/g
Macro-
albuminuria
ACR ≥300 mg/g
Relative
Risk
of
CV
Death*
≥90
60-89
15-59
Cardiovascular Mortality Risk Increases With
Progression of CKD
 13 yr of follow-up on participants in NHANES III study 1988–2000 (N = 15,762;
P <.05)
Astor. Am J Epidemiol. 2008;167:1226. Slide credit: clinicaloptions.com
5
4
3
2
1
0

*ASVD was defined as the first occurrence of AMI, CVD/TIA, or PVD.
Incidence/100
Patient-Yr
x 2.8
x 2.3
x 1.7
x 2.1
x 2.0
x 2.5
Risk for Cardiovascular Events Is Greatest When Both
Diabetes and CKD Are Present
 Retrospective analysis of 5% of US Medicare population 1990-1999 (N = 1,091,201)
Foley. J Am Soc Nephrol. 2005;16:489. Slide credit: clinicaloptions.com
0
10
20
30
40
50
60
CHF AMI CVA/TIA PVD ASVD* Death
No diabetes/no CKD
Diabetes/no CKD
No diabetes/CKD
Diabetes/CKD

Patients
(%)
*Relative to diabetes alone.
15.7
32.3
29.5
T2D,
No CKD
No T2D,
CKD
T2D,
CKD
No T2D,
No CKD
10.3
Mortality Among Medicare Patients
Mortality Risk Doubles* in Comorbid T2D and CKD
 Retrospective analysis of US Medicare enrollees 1996-2000 (N = 1.1 million)
Collins. Kidney Int. 2003;64:S24. Slide credit: clinicaloptions.com
0
10
20
30
40

Primary Outcome
Death any cause
CVD death
All-Cause Mortality in CKD
Intensive
Standard
ACCORD: Mortality, CVD Outcomes, and Severe
Hypoglycemia in Diabetes With CKD
 Most CKD defined by microalbuminuria: 69%,
eGFR <60 mL/min/1.73m2: 22%
CKD at BL Glycemia Arm
Hypoglycemia Requiring Assistance
Events, n (%) Annual Incidence
Non-CKD Standard 172 (5.2) 1.1
Non-CKD Intensive 500 (15.3) 3.5
CKD Standard 165 (9.1) 2.0
CKD Intensive 398 (21.5) 5.3
Papademetriou. Kidney Int. 2015;87:649. Slide credit: clinicaloptions.com
Secondary Outcomes
Nonfatal MI
Any stroke
Nonfatal stroke
PO/Rev/nonfatal
CHF
Major coronary
Any CHF
Non-CKD
Rate/Yr (# Events)
CKD
Rate/Yr (# Events)
HR
(95% Cl)
CKD to Non-CKD HR
1.60% (497) 3.21% (537) 1.86 (1.65, 2.11)
1.03% (304) 1.80% (321) 1.62 (1.38-1.90)
0.25% (81) 0.64% (112) 2.41 (1.81-3.22)
0.22% (71) 0.58% (101) 2.49 (1.84-3.38)
1.03% (330) 2.14% (381) 1.97 (1.70-2.29)
0.22% (142) 1.06% (187) 2.19 (1.76-2.73)
4.23% (1228) 7.58% (1131) 1.64 (1.51-1.77)
2.01% (617) 3.47% (575) 1.56 (1.39-1.75)
0.48% (153) 1.70% (289) 3.20 (2.62-3.89)
1 2 4
0.5
CKD better Non-CKD better
Proportion
of
Event-Free
Participants
Intensive
Standard
Follow-up Time
0.6
0.7
0.8
0.9
1.0
0 2 4 6 8
105
83
311
285
1396
1401
1739
1725
1836
1800
Log-rank P = .0098

33%*
18%
20%
ADVANCE: Tight Glucose and BP Control Reduces
New or Worsening Nephropathy
 Factorial, randomized, placebo-controlled trial of routine blood
pressure lowering and intensive glucose control in T2D (N = 11,140)
*P = .005 vs standard glucose control and placebo.
Mean follow-up: 4.3 yr
No.
of
Events
81
100 96
120
Standard Glucose
Control
Intensive Glucose
Control
Placebo
ACE inhibitor + diuretic
Zoungas. Diabetes Care. 2009;32:2068. Slide credit: clinicaloptions.com
New or Worsening Nephropathy
150
125
100
75
50

Cardiovascular Disease in Patients With or Without
Chronic Kidney Disease
WITH WITHOUT
House. Am J Kidney Dis. 2018;72:284. Slide credit: clinicaloptions.com
CKD: 2011 No CKD: 2011
None: 38.7%
CHF 42.9%
CVA/TIA 26.7%
AMI 15.1%
None: 61.7%
AMI 6.4%
CHF 18.5%
CVA/TIA 20.3%

Risk of MI and All-Cause Mortality in People With CKD
vs Diabetes
 Retrospective analysis of population-based cohort from Alberta, Canada (N = 1,268,029)
Tonelli. Lancet. 2012;380:807. Slide credit: clinicaloptions.com
Median follow-up:
48 mo

Change in Albuminuria and Risk of ESRD and All-cause
Mortality
 Retrospective analysis
of individuals with
≥2 ambulatory ACR tests
over ≥2 yr in healthcare
utilization cohort in
Stockholm, Sweden
2006-2011 (N = 19,897)
‒ Mean age: 59 yr
‒ T2D: 61%
‒ Median baseline ACR:
1.9 mg/mmol
Gray area represents 95% CIs
Distribution of 2-Yr ACR Fold Changes
Carrero. Kidney Int. 2017;91:244 Slide credit: clinicaloptions.com
Adjusted
HR
Adjusted
HR
ACR Fold Change
ACR Fold Change
100
30
10
3
1
.3
.1
.03
.01
.016 .03 .06 .12 .25 .5 1 2 4 8 16 32 64
ESRD risk
Mortality risk
16 32 64
1 2 4 8
.016 .03 .06 .12 .25 .5
.5
.7
1
1.5
2
3
4
6

Angiotensin-II Receptor Antagonists Provide
Renoprotection in T2D
RENAAL1
Risk reduction: 20%
P = .02
IDNT2
 Primary composite endpoint: doubling of serum creatinine, ESRD, or death
RESIDUAL RISK RESIDUAL RISK
1. Brenner. NEJM. 2001;345:861. 2. Lewis. NEJM. 2001;345:851. Slide credit: clinicaloptions.com
Risk reduction: 16%
P = .02

Cumulative Incidence of All-Cause Mortality by ACEi and
ARB Discontinuation Status
 Retrospective analysis of individuals initiating ACEi or ARB therapy between 2004-2018 and
experiencing subsequent decline in eGFR <30 mL/min/1.73 m2 in integrated healthcare system in
Pennsylvania (N = 3909)
 Mean age (SD):
73.7 yr (12.6)
 Female: 61.6%
 Diabetes: 49%
 Mean baseline
eGFR: 23 mL/min/
1.73 m2
 Median follow-up:
2.9 yr
Full Sample
eGFR Decrease ≤40% Within 1 yr
Propensity Score-Matched Sample
eGFR Decrease ≤40% Within 1 yr
Qiao. JAMA Intern Med. 2020;180:718. Slide credit: clinicaloptions.com
Survival
Probability
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5
Yr Since Baseline
ACEi/ARB treatment continued
ACEi/ARB treatment discontinued
0 1 2 3 4 5
0.4
0.5
0.6
0.7
0.8
0.9
1
Survival
Probability
Yr Since Baseline
ACEi/ARB treatment discontinued
ACEi/ARB treatment continued
Patients at Risk, n
Continued 3062 2622 2154 1751 1393 1113 1160 963 773 632 485 362
Discontinued 1189 886 691 540 423 318 1160 864 675 528 415 314

Meta-analysis of SGLT2 Inhibitors on the Composite of
Worsening Renal Function, ESRD, or Renal Death
Zelniker. Lancet. 2019;393:31. Slide credit: clinicaloptions.com
0.10 0.25 0.50 1.00 2.50
HR (95% CI)
HR
Weight (%)
Patients Events Events/
1000 Patient-Yr
Treatment Placebo Treatment Placebo
0.66 (0.41-1.07)
0.74 (0.48-1.15)
0.60 (0.35-1.02)
0.67 (0.51-0.89)
0.61 (0.37-1.03)
0.58 (0.41-0.84)
0.54 (0.40-0.73)
0.56 (0.46-0.70)
0.21 (0.09-0.53)
0.44 (0.25-0.78)
0.50 (0.34-0.73)
0.44 (0.32-0.59)
33.5
39.6
27.0
16.8
34.4
27.0
11.7
27.5
60.8
NA
15.1
15.2
NA
7.4
7.8
NA
8.1
4.9
1196
NA
606
2406
NA
3838
1043
NA
4137
605
NA
659
1232
NA
3894
486
NA
4025
NA
83
59
NA
118
186
NA
48
120
NA
11.4
8.9
NA
4.6
4.2
NA
3.8
2.5
eGFR <60 mL/min/1.73 m2
EMPA-REG OUTCOME
CANVAS Program
DECLARE-TIMI 58
Fixed effects model for eGFR <60 (P = .0054)
eGFR < 60 to < 90 mL/min/1.73 m2
EMPA-REG OUTCOME
CANVAS Program
DECLARE-TIMI 58
Fixed effects model for eGFR 6 to < 90 (P < .0001)
eGFR ≥90 mL/min/1.73 m2
EMPA-REG OUTCOME
CANVAS Program
DECLARE-TIMI 58
Fixed effects model for eGFR ≥90 (P < .0001)

Renal Risk in Cohorts Studied With SGLT2 inhibitors
Kluger. Cardiovascular Diabetol. 2019;18:99. Slide credit: clinicaloptions.com
UACR categories (mg/g)
<30 Normal to
Mild Increase
30-300 Moderate Increase >300 Severe
increase
A1 A2 A3
eGFR
Categories
(mL/min/1.73
m
2
)
≥90 Normal G1
60-89
Mild reduction
G2
Declare TIMI-58
CANVAS
EMPA-REG OUTCOME
45-59 Mild to
moderate reduction
G3a CREDENCE
30-44 Moderate to
severe reduction
G3b
15-29 Severe
reduction
G4
<15 Kidney failure G5
Increasing
Risk
Increasing Risk

182
3 13 26 52 78 104 130 156
CREDENCE: eGFR in Participants With Baseline
eGFR <30 mL/min/1.73 m2
Mean baseline, mL/min/1.73 m2
Canagliflozin, n 82 82 77 78 71 57 50 36 22 7
Placebo, n 89 88 85 81 76 65 59 33 21 8
43.0% reduction in the rate of
eGFR decline with canagliflozin
from Wk 3 to end of study
Acute eGFR slope*
Difference: -0.88 mL/min/1.73 m2 (95% CI: -3.16 to 1.39)
Chronic eGFR slope†
Difference: 2.54 mL/min/1.73 m2/yr (95% CI: 0.90-4.17)
*Measured from baseline to Wk 3.
†Measured from Wk 3 until the end of the study.
Placebo 26.5
Canagliflozin 26.3
P = .003
Bakris. Clin J Am Soc Nephrol. 2020;15:1705. Slide credit: clinicaloptions.com
Wk Since Randomization
0
35
30
25
20
15
10
5
0
Mean
eGFR
(mL/min/1.73
m
2
)

Participants With an
Event/1000 Patient-Yr
P Heterogeneity
Canagliflozin Placebo HR (95% CI)
ESKD
All 20.4 29.4 0.68 (0.54-0.86) .11
30-<45 mL/min/1.73 m2 48.5 63.2 0.76 (0.56-1.01)
45-60 mL/min/1.73 m2 11.3 26.8 0.41 (0.24-0.71)
60-<90 mL/min/1.73 m2 7.2 8.1 0.89 (0.46-1.72)
Doubling of Serum Creatinine
All 20.7 33.8 0.60 (0.48-0.76) .16
30-<45 mL/min/1.73 m2 34.7 55.6 0.61 (0.44-0.85)
45-60 mL/min/1.73 m2 16.7 37.1 0.44 (0.28-0.69)
60-<90 mL/min/1.73 m2 13.7 16.3 0.83 (0.52-1.34)
CREDENCE: Renal Outcomes by Baseline eGFR
Favors Canagliflozin Favors Placebo
1.0
0.5 2.0 4.0
0.25
Jardine. J Am Soc Nephrol. 2020;31:1128. Slide credit: clinicaloptions.com

Mechanisms of Cardiovascular Benefits of
SGLT2 Inhibitors
Lopaschuk. JACC: Basic to Translational Science. 2020;5:632. Reproduced with permission. Slide credit: clinicaloptions.com

Albuminuria Categories
Description and Range
(mg albumin/g creatinine)
A1
Optimal
and high-
normal
A3
Very high
and
nephrotic
A2
High
G1 High and optimal >90
G2 Mild 60 to 89
G3a Mild-moderate 45 to 59
G3b Moderate-severe 30 to 44
G4 Severe 15 to 29
G5 Kidney failure <15
Canagliflozin: CREDENCE1 (CKD & T2D)
Trial population:
• eGFR 30 to <90 mL/min/1.73 m2
• UACR 300 to ≤5000 mg/g
Finerenone: FIDELIO2 & FIGARO (CKD & T2D)
• Trial population:
• eGFR 25 to <60 mL/min/1.73 m2
• UACR 30 to <600 mg/g
• POSITIVE RESULT ANNOUNCED!
Dapagliflozin: DAPA-CKD3 (CKD)
• eGFR 25 to ≤75 mL/min/1.73 m2
• UACR 200 to ≤5000 mg/g
Empagliflozin: EMPA-KIDNEY4 (CKD)
• eGFR 20 to <45 mL/min/1.73 m2 OR
• eGFR 45 to <90 mL/min/1.73 m2 with
UACR ≥200 mg/g (or protein creatinine
ratio ≥300 mg/g)
2019
2020
2021
2023/4
eGFR
stages,
description
and
range
(mL/min/1.73
2
)
Semaglutide: FLOW trial5
Trial population
eGFR 50 to ≤75 and UACR >300 mg/g OR
eGFR 25 to <50 and UACR >100 mg/g
2023/4
Summary of Ongoing Renal Outcome Trials
to Be Completed by 2023-2024
1. Perkovic. NEJM. 2019;380:2295. 2. Bakris. NEJM. 2020;383:2219. 3. Heerspink. NEJM. 2020;383:1436. 4. NCT03594110. 5.
NCT03819153. Slide credit: clinicaloptions.com

ADA. Diabetes Care. 2021;44:S1. Slide credit: clinicaloptions.com
COMPELLING NEED TO
MINIMIZE WEIGHT GAIN OR
PROMOTE WEIGHT LOSS
SGLT2i2
+HF
 Particularly
HFrEF
(LVEF <45%)
To avoid
therapeutic inertia
reassess and modify
treatment regularly
(3-6 months)
FIRST-LINE Therapy is Metformin and Comprehensive Lifestyle (including weight management and physical activity)
INDICATORS OF HIGH-RISK OR ESTABLISHED ASCVD, CKD, OR HF†
NO
CONSIDER INDEPENDENTLY OF BASELINE A1C OR
INDIVIDUALIZED A1C TARGET, OR METFORMIN USE*
+ASCVD/Indicators of High Risk
GLP-1 RA with
proven CVD
benefit1
If A1C above target
SGLT2i with proven
benefit in this
population5,6,7
COMPELLING NEED TO MINIMIZE
HYPOGLYCEMIA
DPP-4i GLP-1 RA SGLT2i TZD
If A1C
above target
If A1C
above target
If A1C
above target
If A1C
above target
SGLT2i
OR
TZD
SGLT2i
OR
TZD
GLP-1 RA
OR
DPP-4i
OR
TZD
SGLT2i
OR
DPP-4i
OR
GLP-1 RA
If A1C above target
GLP-1 RA with
good efficacy
for weight loss10
GLP-1 RA with
good efficacy for
weight loss8
SGLT2i
EITHER/OR
If A1C above target
COST IS A MAJOR ISSUE9-10
SU4 TZD12
TZD12 SU4
If A1C above target
If A1C above target
IF A1C ABOVE INDIVIDUALIZED TARGET PROCEED AS BELOW
 Established ASCVD
 Indicators of high ASCVD risk (age
≥55 years with coronary, carotid,
or lower extremity artery stenosis
>50%, or LVH
SGLT2i with
proven CVD
benefit1
Either/or
If further intensification is required
or patient is unable to tolerate GLP-
1 RA and/or SGLT2i choose agents
demonstrating CV benefit and/or
safety:
 For patients on a GLP-1 RA,
consider adding AGLT2i with
proven CVD benefit and vice
versa
 TZD2
 DPP-4i if not on GLP-1 RA
 Basal insulin3
 SU4
+CKD
PREFERABLY
SGLT2i with primary
evidence of reducing CKD
progression
OR
SGLT2i with evidence of
reducing CKD progression
in CVOTs5,6,8
OR
GLP-1 RA with proven CVD
benefit1 if SGLT2i not
tolerated or
contraindicated
DKD and Albuminuria6
For patients with T2D and CKD8
(e.g., eGFR <60 mL/min/1.73
m2) and thus at increased risk
of cardiovascular events
NO
GLP-1 RA with
proven CVD
benefit1
SGLT2i with
proven CVD
benefit1
Either/or
Continue with addition of other agents as outlined above
If A1C above target
Consider the addition of SU4 OR basal insulin:
 Choose later generation SU with lower risk of hypoglycemia
 Consider basal insulin with lower risk of hypoglycemia9
If A1C above target
Insulin therapy basal insulin
with lowest acquisition cost
OR
Consider other therapies
based on cost
If quadruple therapy required,
or SGLT2i and/or GLP-1 RA not
tolerated or contraindicated,
use regimen with lowest risk of
weight gain
PREFERABLY
DPP-4i (if not on GLP-1 RA)
based on weight neutrality
If DPP-4i not tolerated or
contraindicated or patient
already on GLP-1 RA,
cautious addition of:
▪ SU4 ▪ TZD2 ▪ Basal Insulin
ADA Clinical Practice Guidelines: Glucose-Lowering Medications in T2D

Guidelines: Diabetes and CKD Management of
Hypertension
Old1 New2 Today?
 Target BP in diabetes and CKD
stages 1-4 should be <130/80
mm Hg (B)
 Hypertensive persons with
diabetes and CKD should be
treated with an ACE inhibitor
or an ARB, usually in
combination with a diuretic
(A)
 Recommendations are the
same as for non-diabetic CKD
 Without increased
albuminuria (ACR >30 mg/g),
less intensive target of
<140/90 mm Hg is
recommended and no
preference for RAS inhibition
 Avoid combination RAAS
blockade
 Shouldn’t we aim for 130/ 80
or less in all CKD patients?
 RAAS blockade + SGLT2
inhibitor in all
 Spironolactone?
 Do not stop when eGFR
<30 mL/min/1.73 m2
1. NFK-KDOQI. Am J Kidney Dis. 2007;49:S88. 2. KDIGO. Kidney Inter Suppl. 2012;2:337. Slide credit: clinicaloptions.com

Advanced CKD in T2D: Summary
 Advanced CKD is a high-risk clinical entity with high morbidity and mortality
 CKD doubles the risk of cardiovascular events and death in patients with T2D
 It is never too late to improve glycemic control, but strategy is different
 CKD stage should be considered when choosing an antidiabetic therapy, avoiding
hypoglycemia
 Many changes in treatment are needed, making management challenging
 GLP-1 receptor agonists reduce CV risk and are safe
 SGLT-2 inhibitors reduce CKD progression and HHF and other CVD risks
 Additional BP reduction is important but challenging
 Novel approaches are needed to improve prognosis

Susanne B. Nicholas, MD, MPH, PhD
Associate Professor of Medicine
Nephrologist and Hypertension Specialist
Department of Medicine, Nephrology Division
David Geffen School of Medicine at UCLA
Los Angeles, California
Pathogenesis

Pathogenic Mechanisms Involved
in Diabetic Kidney Disease

Natural History of Diabetic Kidney Disease
*Kidney complications: anemia, bone and mineral metabolism, retinopathy, and neuropathy.
Alicic. CJASN. 2017;12:2032. Slide credit: clinicaloptions.com
Diagnosis
Yr 2 5 10 20 30
Hyperglycemia
Cellular injury Mesangial expansion glomerulosclerosis, tubulointerstitial fibrosis, and inflammation
Microalbuminuria Macroalbuminuria
GFR High Normal Low ESRD
Hypertension
Kidney complications*
Cardiovascular disease, infections, death

Mechanistic Links Between Prediabetes, Diabetes, DKD,
and End-Stage Kidney Disease
Prediabetes, Diabetes
Chronic hyperglycemia, metabolic syndrome, dyslipidemia, increased fatty acid metabolism
Hemodynamic
Inflammation
cytokines, chemokines
Oxidative stress
ROS
Apoptosis/autophagy
Mitochondrial dysfunction
mitophagy
Diabetic nephropathy
Extracellular matrix accumulation
Glomerular nodular sclerosis
Glomerular basement membrane thickening
Glomerular hyalinosis
podocytopathy
End-stage kidney
disease
Nicholas. NephSAP. 2020;19:110. Slide credit: clinicaloptions.com

Structural Changes in Diabetic Kidney Disease
Alicic. CJASN. 2017;12:2032. Reproduced with permission.
Normal Kidney Glomerulus Diabetic Kidney Glomerulus

Diabetic Glomerulopathy
Alicic. CJASN. 2017;12:2032. Reproduced with permission. Slide credit: clinicaloptions.com
Normal Glomerulus Diffuse mesangial expansion Nodularity, mesangiolysis
Kimmelstiel-Wilson nodules Dilated capillaries-
microaneurysms
Obsolescent glomerulus

Electron Microscope Images of Diabetic Glomerulopathy

Glomerular and Tubular Damage in DKD
Zeni. J Nephrol. 2017;30:701. Slide credit: clinicaloptions.com
Direct Glomerular Damage Direct Tubular Damage
Decrease in Albumin Endocytosis
Podocyte Barrier Damage
Glomerular Leakage Reduced Retrieval
Increased Protein Delivery to PT and Reserve Capacity Exceeded, Resulting in
Microalbuminuria
GLU-Na PT
Hyperreabsorbtion
Hyperfiltration
Vascular
Imbalance Hyperglycemia SGLT2 Up-Regulation
Damage due to diabetes
Tubular interaction
Glomerular interaction
Rise of Intra-
Glomerular Pressure
Inhibition of Tubuloglomerular Feedback
Reduction of Hydraulic Pressure in Bowman’s Space
PT GLU Overload

Biomarkers Associated with Predicting DKD
Colhoun. Diabetologia. 2018;61:996. Reprinted under Creative Commons license:
http://creativecommons.org/licenses/by/4.0. Slide credit: clinicaloptions.com
Glomerulus
Cystatin C
𝝰1-Microglobulin
𝝱2-Microglobulin
Albumin
Distal tubule
Osteopontin
NGAL
Copeptin
Collecting duct
Copeptin
Proximal tubule
KIM-1
NGAL
L-FABP
FGF23
Loop of Henle
Osteopontin
Uromodulin
(Tamm-Horsfall protein)
Inflammation/endothelial
damage/fibrosis
𝝰1-Antitrypsin
TGF-𝝱1
MCP-1
VEGF
MR-proADM
NT-proBNP
TNFR1, TNFR2
SDMA/ADMA
FGF21
CKD273
CD5L
MMPs
Endostatin

Classification of Tubular Urinary Biomarkers in DKD
Urinary Biomarkers in DKD
Structural Biomarkers Functional Biomarkers Pathophysiological Biomarkers
 Biomarkers reflecting glomerular endothelial cells
and podocytes (α-actinin-4, glycosaminoglycans,
lipocalin-type, prostaglandin-D synthase, nephrin,
podocalyxin, podocin, synaptopodin, vascular
endothelial growth factor A, Wilms tumor-1)
 Biomarkers of glomerular and tubular basement
membrane and extracellular matrix proteins
alterations (fibronectin, laminin, matrix
metalloproteinase-9, transforming growth
factor-β-induced protein h3, type I collagen
fragments, type IV collagen)
 Biomarkers of tubular epithelial cells damage
(alkaline phosphatase and ɣ-glutamyltransferase,
cubilin and megalin, glycoprotein nonmetastatic
melanoma protein B, kidney injury molecule-1, liver-
type fatty acid binding protein, neutrophil gelatinase-
associated lipocalin, N-acetyl-β-D-glucosaminidase)
 Functional glomerular
barrier damage (albumin,
angiotensinogen, ceruloplasmin,
immunoglobulin G, transferrin)
 Functional tubular reabsorptive
damage (α1-macroglobulin,
β2-macroglobulin, albumin, cystatin
C, retinol binding protein 4)
 Oxidative stress (advanced glycation
end products, heart fatty acid
binding protein, pentosidine,
8-hydroxy-2’-deoxyguanosine,
8-oxo-7,8-dihydro-2’-deoxyguanosine)
 Inflammation (interleukin-6,
monocyte chemoattractant protein-1,
nitric oxide, orosomucoid, tumor
necrosis factor-α)
 Intra-renal renin-angiotensin system
(urine/plasma renin ratio)
 Growth factors (connective tissue
growth factor, transforming growth
factor β1)
Zeni. J Nephrol. 2017;30:701. Slide credit: clinicaloptions.com

Pathogenic Mechanisms of DKD
Mora-Fernández. J Physiol. 2014;592:3997. Slide credit: clinicaloptions.com
Genetic factors Environmental factors
Diabetes
Pathogenic mechanisms for renal injury
Hyperglycemia
Renin-angiotensin-aldosterone system
Activation of cell signaling pathways and transcription factors
Diabetic kidney disease
Renal functional and structural changes
Cellular and extracellular matrix-related effects
Metabolic
Advanced glycation
Polyol
Protein kinase C
Oxidative stress
Inflammatory
Inflammatory cells
Adhesion molecules
Chemokines
Inflammatory cytokines
Hemodynamic
Systemic hypertension
Impaired renal vascular regulation
Intraglomerular hypertension
Altered sodium/fluid balance
Differentiation
Proliferation
Hypertrophy
Apoptosis
↑ Collagen and fibronectin
↑ Connective tissue
↑ Inhibition metalloproteinases
↓ Matrix degradation

Definition of Glomerular Hyperfiltration in DKD
 Glomerular hyperfiltration: eGFR 120-175 mL/min/1.73 m2 or
>2 standard deviation increase in eGFR above mean in healthy
age-matched individuals
‒ Occurs in 70% of patients with type 1 diabetes and 50% of patients with
type 2 diabetes
‒ Predicts glomerular structural pathology and progressive decline in GFR
‒ Predicts cardiovascular events and all-cause mortality in type 2 diabetes

Normal vs. Diabetic Nephron:
Altered Renal Hemodynamics

Four Phases of Hyperfiltration and Relation to
Whole Kidney GFR and Urine Albumin Excretion
Tonneijck. JASN. 2017;28:1023. Slide credit: clinicaloptions.com
180
150
135*
120
90
60
30
Whole
Kidney
GFR
(mL/min/1.7
3m
2
)
5000
1000
200
20
Urinary
Albumin
Excretion
(mg/24
hr)
UAE
GFR
~Nephon mass 100% 100% 50% 0%
Hypofiltration
Normal filtration
Phase 2
Hyperfiltration
at whole-kidney level
Normal
filtration
Phase 1
Renal
functional
reserve
Improved
HbA1c

Renal Inflammation, Oxidative Stress,
and Accelerated Fibrosis

Inflammation and Oxidative Stress in DKD
 Glomerular and tubular injury
 DKD is marked by chronic, low-grade inflammation and oxidative stress
 Dysregulation of homeostatic processes of apoptosis and autophagy
may lead to podocyte loss, albuminuria, and tubular damage in DKD
 Both glomerular and tubular damage contribute to albuminuria and
both processes can be targeted in DKD management

Altered Metabolism, Hyperglycemia,
Oxidative Stress
DKD triggers
Metaflammation
Mediators
Cytokines: IL-1, IL-6, IL-8, IL-12, IL-18, TNF, GM-CSF,
IL-10, IL-11, TGF- Chemokines: MCP 1, CCR2, CCR2
Signaling
pathways
Nrf2-Keap1
JAK1/STAT2
ASK1
PDE
Glomerulosclerosis, extracellular
matrix expansion, interstitial fibrosis
Albuminuria, declining eGFR
DKD pathology
Clinical signs
Inflammatory Pathways in DKD
Proinflammatory Macrophage
Anti-inflammatory Macrophage
Matoba. Int J Mol Sci. 2019;20:3393. Slide credit: clinicaloptions.com

Direct Deleterious Effects of Aldosterone/MR Activation
Bauersachs. Hypertension. 2015;65:257. Slide credit: clinicaloptions.com
Kiran D. Mir-Hudgeons

MR at the Crossroad of Metabolic Functions
Zennaro. Trends in Endocrinol Metabolism. 2009;20:444. Slide credit: clinicaloptions.com
Hypertension
Nephrosclerosis
Proteinuria
Inflammation, dysfunctional
adipose tissue
Water and salt homeostasis Adipocyte differentiation thermoregulation
Vascular function
Cardiac structure and function
Salt and water appetite
Central BP regulation
Activation HPA axis
Cardiac fibrosis
Arrhythmia Vascular inflammation
and remodeling
Endothelial dysfunction
Altered stress response
Increased vulnerability
Aldosterone Cortisol
MR

Kolkhof. J Endocrinol. 2017;234:T125. Image courtesy of Creative Commons: https://creativecommons.org/licenses/by/3.0. Slide credit: clinicaloptions.com
MRAs: 60 Yrs of Research and Development
1957
1960
1962
1968
1974
1975
1977
1982
1986
1987
1989
1999
2003
2011
2012
2013
2015
2016
Spirolactones:
Kagawa et al.
(1957), Liddle
(1957)
Gynecomastia
associated with
spironolactone
use: Smith (1962)
ARTS-HF:
Filippatos et
al. (2016)
Esaxeronone
preclinical: Arai et al.
(2015a,b); ARTS-DN:
Bakris et al. (2015)
ARTS: Pitt et al. (2013)
Finerenone preclinical:
Barfacker et al. (2012)
EMPHASIS-HF: Zannad et al. (2011)
EMPHESUS:
Pitt et al.
(2003)
Launch of
eplerenone
for heart
failure
Cloning of MR:
Arriza et al. (1987)
Eplerenone
preclinical: de
Gasparo et al.
(1987)
RALES: Pitt et al.
(1999)
Eplerenone
first-in-man:
de Gasparo
et al. (1989)
Mespirenone: Losert et al. (1986)
Partial
purification
of renal
aldosterone-
binding
proteins:
Herman et
al. (1968)
Structure-activity
relationship of
24 Spirolactones:
Funder et al.
(1974)
Prorenoate:
Hofmann et
al. (1975),
Ramsay et al.
(1975)
Mexrenoate:
Hofmann et
al. (1977)
Spirorenone: Bittler et al. (1982)
Launch of
spironolactone
as diuretic

In Vitro Potency of MR Antagonists
Kolkhof. J Endocrinol. 2017;234:T125. Slide credit: clinicaloptions.com
Agonist
Antagonist
Spironolactone
IC50 (nM)
Eplerenone
IC50 (nM)
Finerenone
IC50 (nM)
Aldosterone 24 990 18
Cortisol 19 360 5
Corticosterone 41 940 24

Finerenone Reduces Downstream Pro-inflammatory
and Profibrotic Factors
Agarwal. Eur Heart J. 2021;42:152. Slide credit: clinicaloptions.com
Different MR ligands
Aldosterone Cortisol Finerenone
MR conformational change on ligand binding
MR unbound MR + aldosterone MR + finerenone
Cytoplasm
Differential recruitment of MR cofactors
Different MR complexes formed
MR + aldosterone + cofactor complex formed Cofactor recruitment inhibited by finerenone
Nucleus
MR cofactors
Differential gene expression
Gene transcription profile includes pro-inflammatory and
pro-fibrotic gene expression
Gene transcription profile includes less pro-inflammatory
and pro-fibrotic gene expression
OUTCOME: Increased inflammation and fibrosis due to
MR overactivation
OUTCOME: Decreased inflammation and fibrosis due to
MR antagonism by finerenone
 X

Finerenone Attenuates Neointima Lesion Formation
Dutzman. PLOS One. 2017;12:e0184888. Image courtesy of Creative Commons:
https://creativecommons.org/licenses/by/4.0. Slide credit: clinicaloptions.com
Vehicle Finerenone
1 mg/kg/day
Finerenone
10 mg/kg/day
A. B.
100
80
60
40
20
0
Luminal
Stenosis
(in
%)
*
**
****

Interconnected Cardiovascular Systems:
Kidney, Vasculature, and Heart

DKD and Other Diabetic Complications:
A Strong Association
Thomas. Nat Rev Dis Primers. 2015;1:15018. Slide credit: clinicaloptions.com
Cognitive
impairment
Periodontal
disease
Eye disease
Erectile
dysfunction
Neuropathy
Coronary
heart disease
Diabetic
cardiomyopathy
Peripheral
vascular disease
Foot disease
Depression
and anxiety
Cerebrovascular
disease
Bladder
dysfunction
DKD

Aldosterone and the MR in Renal Pathophysiology
Bertocchio. Kidney Int. 2011;79:1051. Slide credit: clinicaloptions.com
Kidney Diseases Proposed Mechanisms
Nephroangiosclerosis Vasoconstriction
Diabetic nephropathy Oxidative stress
Cyclosporine nephrotoxicity Inflammation
Proteinuric nephropathies Alteration of glomerulus filtration barrier
End-stage renal disease Glomerulosclerosis

Benefits of MRAs in Renal Ischemia:
A Proposed Mechanism
Barrera-Chimal. JASN. 2017;28:1216. Reproduced with permission. Slide credit: clinicaloptions.com

Beneficial Effects of MR Antagonism
Jaisser. Pharmacol Rev. 2016;68:49. Reproduced with permission. Slide credit: clinicaloptions.com
MR Antagonism
beneficial for:
ADIPOSE TISSUE:
Obesity
HEART:
Heart Failure
Myocardial infarction
Arrhythmia
Fibrosis
KIDNEY:
Hypertension
Ischemic insult
Glomerular injury
IMMUNE CELLS:
Inflammation
SKIN:
Epidermal atrophy
BLOOD VESSELS:
Vasoconstriction
Endothelial dysfunction
Hypertension
Atherosclerosis
Remodeling
RETINA:
Retinal edema
Neoangiogenesis
Central serous chorioretinitis

Glycemic Control and Residual Incidence of CKD
Thomas. Nat Rev Dis Primers. 2015;1:15018. Slide credit: clinicaloptions.com
A1C (%)
Microalbuminuria
(Hazard)
Proportion
of
Patients
(%)
18
16
14
12
10
8
6
4
2
0
6
5
4
3
2
1
0
13
0 5 6 7 8 9 10 11 12

Summary and Conclusions
 The mechanisms involved in the pathogenesis of DKD include:
‒ Metabolic
‒ Hemodynamic
‒ Inflammation and fibrosis
 Direct glomerular and tubular injury
 Mineralocorticoid receptor overactivation is key player in DKD pathogenesis
 Antagonism of the MR can have beneficial effects in DKD and other complications
of diabetes
 Finerenone is a novel non-steroidal MRA that is more potent that spironolactone or
eplerenone

Yr
2010 2015 2020 2025 2030
Asia
(0.97→2.16)
Africa
(0.08→0.24)
Europe
(0.53→0.83)
Latin America
(0.37→0.90)
North America
(0.64→1.26)
Oceania
(0.03→0.05)
0
1.0
2.0
3.0
Number
of
RRT
(x
million)
Region
World
Number
of
RRT
(x
million)
0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Yr
2010 2015 2020 2025 2030
2.62
3.13
3.78
4.53
5.44
Liyanage. Lancet. 2015;385:1975.
Number of People Receiving Renal Replacement Therapy
Is Projected to Double

George L. Bakris, MD
Director, Comprehensive Hypertension Center
University of Chicago Medicine
Chicago, Illinois
Diabetic Kidney Disease Treatment:
Where Are We Now

KDIGO: Composite Ranking for Relative Risks by GFR
and Albuminuria
66
Levey. Kidney Int. 2011;80:17-28. Slide credit: clinicaloptions.com
Composite ranking for relative risks by
GFR and albuminuria (KDIGO 2009)
Albuminuria stages, description, and range (mg/g)
A1 A2 A3
Optimal and high-normal High Very high and nephrotic
<10 10-29 30-299 300-1999 ≥2000
eGFR
Stages,
Description,
and
Range
(ml/min/1.73m
2
)
G1 High and optimum
>105
90-104
G2 Mild
75-89
60-74
G3a Mild-moderate 45-59
G3b Moderate-severe 30-44
G4 Severe 15-29
G5 Kidney failure <15

Angiotensin-II Receptor Antagonists Provide
Renoprotection in T2D
RENAAL1
Risk reduction: 20%
P = .02
IDNT2
 Primary composite endpoint: doubling of serum creatinine, ESKD, or death
RESIDUAL RISK RESIDUAL RISK
1. Brenner. NEJM. 2001;345:861. 2. Lewis. NEJM. 2001;345:851.
Risk reduction: 16%
P = .02

New Therapies for Patients With T2D and CKD:
Lack of Success in Outcomes
1. Tuttle. Clin J Am Soc Nephrol. 2007;2:631. 2. Mann. J Am Soc Nephrol. 2010;21:527. 3. Sharma. J Am Soc Nephrol. 2011;22:1144. 4. Packham.
J Am Soc Nephrol. 2012;23;123. 5. Parving. NEJM. 2012;367:2204. 6. Fried. NEJM. 2013;369:1892. 7. de Zeeuw. NEJM. 2013;369:2492.
Sulodexide
Various suggested
MoAs4
Ruboxistaurin
PKC-ß inhibitor1
Pirfenidone
TGF-ß production
inhibitor3
Bardoxolone methyl
Kept1-Nrf2
pathway activator7
Aliskiren
Renin inhibitor5
Lisinopril/losartan
Dual ACEi/ARB6
Avosentan
Endothelin
antagonist2
2007
2010
2011
2012
2013

Oral Glucose-Lowering Agents on
CV and Renal Outcomes
 Metformin: weak CV evidence for benefit and NO kidney outcome data
 Sulfonylureas: neutral on CV events and NO kidney outcome data
 DPP4 agents: neutral on CV events and NO kidney outcome data except
for linagliptin (neutral)
 Acarbose: CV and kidney neutral or no data
 GLP-1 agonists: positive CV data NO kidney outcome data yet
 SGLT2 inhibitors: positive CV and Kidney data

Patients with ASCVD
EMPA-REG OUTCOME
CANVAS program
DECLARE-TIMI 58
CREDENCE
VERTIS CV
Fixed-effects model (Q = 6.09; df = 4; P = .19; I2 = 34.4%)
Patients without ASCVD
CANVAS program
DECLARE-TIMI 58
CREDENCE
Fixed-effects model (Q = 1.86; df = 2; P = .40;I2 = 0%)
McGuire. JAMA Cardiol. 2021;6:148.
Meta-analysis of SGLT2 Inhibitor Trials on Composite of
Worsening of Renal Function, ESKD, or Renal Death
HR (95% CI)
0.2 1 2
Kidney outcomes by ASCVD status
Weight, %
Favors
Placebo
Favors
Treatment
HR
(95% CI)
Treatment Placebo
n/N Rate/1000
Patient-Yr
n/N Rate/1000
Patient-Yr
16.67
19.23
18.06
17.37
28.66
15.72
37.41
46.87
0.54 (0.40-0.75)
0.59 (0.44-0.79)
0.55 (0.41-0.75)
0.64 (0.47-0.87)
0.81 (0.64-1.03)
0.64 (0.56-0.72)
0.63 (0.39-1.02)
0.51 (0.37-0.69)
0.68 (0.51-0.89)
0.60 (0.50-0.73)
11.5
10.5
8.6
36.5
11.5
6.6
5.9
44.3
71/2323
NA/2900
118/3500
102/1107
108/2747
NA/1447
120/5078
122/1092
6.3
6.4
4.7
24.1
9.3
4.1
3.0
29.9
81/4645
NA/3756
65/3474
69/1113
175/5499
NA/2039
62/5108
84/1089

VERTIS
DECLARE
CANVAS Program
EMPA-REG OUTCOME
CREDENCE
DAPA-CKD 43 965
Renal Risk in Cohorts Studied With SGLT2 Inhibitors
Low
Moderately
increased
High Very high
<30
30-44
45-59
60-90
≥90
GFR
Categories
(mL/min/1.73
m
2
)
Albuminuria Categories, mg/g
A1: <30 A2: 30-300 A3: >300
D
C E
Median
UACR,
mg/g
X
13
12
18
927
Mean eGFR,
mL/min/1.73 m2
76
85
76
74
56
Sustained RRT Events
DECLARE Not reported
CANVAS Program 18
EMPA-REG OUTCOME 11
CREDENCE 176
D
C
E
V
V
x 1.31 mg/mmol-geo mean
Kluger. Cardiovascular Diabetol. 2019;18:99. Cannon. NEJM. 2020;383:1425. Heerspink. NEJM. 2020;383:1436. Slide credit: clinicaloptions.com

CREDENCE: 34 Countries, 690 Sites, 4401 Participants
Europe (n = 1368)
 Bulgaria
 Czech Republic
 France
 Germany
 Hungary
 Italy
 Lithuania
 Poland
(29)
(57)
(61)
(11)
(135)
(90)
(7)
(50)
 Romania
 Serbia
 Slovakia
 Spain
 Russia*
 Ukraine*
 United Kingdom
(59)
(40)
(66)
(141)
(133)
(371)
(118)
Asia Pacific* (n = 848)
 Australia
 China
 India
 Japan
 Korea
 Malaysia
(38)
(129)
(144)
(110)
(122)
(135)
 New Zealand
 Philippines
 Taiwan
 United Arab
Emirates
(61)
(71)
(37)
(1)
Africa (n = 62)
 South Africa* (62)
*Analyzed as part of rest of world (n = 1414) in prespecified subgroup analyses.
Central/South America
(n = 941)
 Argentina
 Brazil
 Chile
 Colombia
 Guatemala
(426)
(314)
(52)
(94)
(55)
North America (n = 1182)
 Canada
 Mexico
 United States
(172)
(303)
(707)
Agarwal. ADA 2019.

CREDENCE: Baseline Therapies
Canagliflozin
(n = 2202)
Placebo
(n = 2199)
Total
(N = 4401)
Glucose-lowering agents, %
Insulin 65.9 65.1 65.5
Metformin 57.9 57.7 57.8
Sulfonylurea 27.8 29.8 28.8
DPP-4 inhibitor 17.2 17.0 17.1
GLP-1 receptor agonist 4.0 4.3 4.2
Renal and CV protective agents, %
RAAS inhibitor >99.9 99.8 99.9
Statin 69.8 68.1 69.0
Antithrombotic 60.9 58.3 59.6
β-blocker 40.1 40.3 40.2
Diuretic 46.6 46.9 46.7
Perkovic. NEJM. 2019;380:2295. Slide credit: clinicaloptions.com

CREDENCE: Primary Endpoint Definitions
 End-stage kidney disease
‒ Chronic dialysis for ≥30 days
‒ Kidney transplantation
‒ eGFR <15 mL/min/1.73 m2 sustained
for ≥30 days by central laboratory
assessment
 Doubling of serum creatinine
‒ Doubling from the baseline average
sustained for ≥30 days by central
laboratory assessment
 Renal death
‒ Deaths in patients who have reached
ESKD who die prior to initiating RRT
and no other cause of death is
adjudicated
 Cardiovascular death
‒ Death resulting from an acute
myocardial infarction, sudden cardiac
death, death due to heart failure,
death due to stroke, death due to
cardiovascular procedures, death due
to cardiovascular hemorrhage, and
death due to other cardiovascular
causes
Perkovic. NEJM 2019;380:2295. Slide credit: clinicaloptions.com

CREDENCE: Primary Composite Outcome
HR: 0.70 (95% CI: 0.59-0.82;
P = .00001)
6 12 18 24 30 36 42
340 participants
Rate: 61.24/1000 PY
245 participants
Rate: 43.21/1000 PY
Placebo
Canagliflozin
Patients at
Risk, n
Placebo 2199 2178 2132 2047 1725 1129 621 170
Canagliflozin 2202 2181 2145 2081 1786 1211 646 196
Mo Since Randomization
Participants
With
an
Event
(%)
25
20
15
10
5
0
0

CREDENCE: Renal-Specific Compositive Outcome
HR: 0.66 (95% CI: 0.53-0.81;
P = .00006)
6 12 18 24 30 36 42
224 participants
Rate: 40.36/1000 PY
153 participants
Rate: 26.99/1000 PY
Placebo
Canagliflozin
Patients at
Risk, n
Placebo 2199 2178 2131 2046 1724 1129 621 170
Canagliflozin 2202 2181 2144 2080 1786 1211 646 196
Participants
With
an
Event
(%)
25
20
15
10
5
0
0
Perkovic. NEJM 2019;380:2295.

CREDENCE: Primary Outcome by Screening eGFR and
Albuminuria
HR (95% CI)
Interaction
P Value
Screening eGFR .11
30 to <45 mL/min/1.73 m2
0.75 (0.59-0.95)
45 to <60 mL/min/1.73 m2
0.52 (0.38-0.72)
60 to <90 mL/min/1.73 m2
0.82 (0.60-1.12)
Baseline UACR .49
≤1000 mg/g 0.76 (0.55-1.04)
>1000 mg/g 0.67 (0.55-0.81)
0.25 0.5 1.0 2.0 4.0

CREDENCE: Primary and Secondary Prevention Cohorts
Mahaffey. Circulation 2019;140:739. Slide credit: clinicaloptions.com
Placebo
Canagliflozin
HR: 0.74 (95% CI:
0.54-1.03)
Participants
With
an
Event
(%)
25
20
15
10
5
0
42
0 6 12 18 24 30 36
Primary Prevention
Cardiovascular Death and
Hospitalization for Heart Failure
Patients
at Risk, n
Placebo
Canagliflozin
1092
1089
1080
1081
1066
1059
1036
1041
890
897
586
598
306
332
85
97
Placebo
Canagliflozin
HR: 0.66 (95% CI:
0.52-0.83)
Participants
With
an
Event
(%)
25
20
15
10
5
0
42
0 6 12 18 24 30 36
Secondary Prevention
1107
1113
1085
1090
1057
1073
1008
1036
846
892
561
628
332
336
85
102
Placebo
Canagliflozin
HR: 0.85 (95% CI:
0.69-1.06)
Participants
With
an
Event
(%)
25
20
15
10
5
0
42
0 6 12 18 24 30 36
Secondary Prevention
1092
1089
1080
1081
1066
1059
1036
1041
890
897
586
598
306
332
85
97
Placebo
Canagliflozin
HR: 0.68 (95% CI:
0.49-0.94)
Participants
With
an
Event
(%)
25
20
15
10
5
0
42
0 6 12 18 24 30 36
Primary Prevention
1092
1089
1080
1081
1066
1059
1036
1041
890
897
586
598
306
332
85
97
Cardiovascular Death, Nonfatal Myocardial
Infraction, or Nonfatal Stroke

CREDENCE: Other AEs of Interest
n/N
Canagliflozin Placebo
HR
(95% CI)
Male genital mycotic infections 28/1439 3/1466 9.30 (2.83-30.60)
Female genital mycotic infections 22/761 10/731 2.10 (1.00-4.45)
Urinary tract infections 245/2200 221/2197 1.08 (0.90-1.29)
Volume depletion–related AEs 144/2200 115/2197 1.25 (0.97-1.59)
Cancer
Renal cell carcinoma 1/2200 5/2197 0.20 (0.02-1.68)
Breast* 8/761 3/731 2.59 (0.69-9.76)
Bladder 10/2200 9/2197 1.10 (0.45-2.72)
Acute pancreatitis 5/2200 2/2197 2.44 (0.47-12.59)
Diabetic ketoacidosis 11/2200 1/2197 10.80 (1.39-83.65)
*Includes female participants only.
0.125 1.0 2.0 16.0
4.0 8.0 32.0
0.5
0.25

DAPA-CKD: Primary Outcome
HR: 0.61 (95% CI: 0.51-0.72;
P = .000000028)
NNT = 19
Placebo
Dapagliflozin
197 events
312 events
Heerspink. NEJM. 2020;383:1436.
 4299 (99.9%) vital
status known
 4289 (99.7%)
completed study
 33% had
nondiabetic
kidney disease
Cumulative
Incidence
(%)
32
0 4 8 12 16 20 24 28
Patients
at Risk, n
Dapagliflozin
Placebo
2152
2152
2001
1993
1955
1936
1898
1858
1841
1791
1701
1664
1288
1232
831
774
309
270
24
22
20
18
16
14
12
10
8
6
4
2
0

DAPA-CKD: Secondary Outcome
Heerspink. NEJM. 2020;383:1436.
• Sustained ≥50% eGFR decline, ESKD, renal death
HR: 0.56 (95% CI: 0.45-0.68;
P = .000000018)
Placebo
Dapagliflozin
142 events
243 events
Cumulative
Incidence
(%)
32
0 4 8 12 16 20 24 28
Patients
at Risk, n
Dapagliflozin
Placebo
2152
2152
2001
1993
1955
1936
1898
1858
1841
1791
1701
1664
1288
1232
831
774
309
270
20
18
16
14
12
10
8
6
4
2
0

DAPA-CKD: Prespecified Subgroup Analysis
Heerspink. ESC 2020.
Dapagliflozin
Events
Placebo
Events
HR
(95% CI)
P Value
Interaction
All patients 197 312 0.61 (0.51-0.72)
With type 2 diabetes 152 229 0.64 (0.52-0.79)
Without type 2 diabetes 45 83 0.50 (0.35-0.72) .24
UACR ≤1000 mg/g 44 84 0.54 (0.37-0.77)
UACR >1000 mg/g 153 228 0.62 (0.50-0.76) .52
eGFR <45 mL/min/1.73 m2 152 217 0.63 (0.51-0.78)
eGFR ≥45 mL/min/1.73 m2 45 95 0.49 (0.34-0.69) .22
Favors dapagliflozin Favors placebo
HR (95% CI)
0.3 0.6 1.0 1.4

DAPA-CKD: CV Death or Heart Failure Hospitalization
(Secondary Outcome )
Heerspink. NEJM. 2020;383:1436. Slide credit: clinicaloptions.com
Cumulative
Incidence
(%)
10
8
6
4
2
0
0 4 8 12 16 20 24 28 32
HR: 0.71 (95% Cl: 0.55-0.92;
P = .0089)
Placebo
Dapagliflozin
138 events
100 events
Patients at Risk, n
Dapagliflozin
Placebo
2152
2152
2035
2023
2021
1989
2003
1957
1975
1927
1895
1853
1502
1451
1003
976
384
360

Bakris. Am J Kidney Dis. 2019;74:573.
SGLT2 Inhibitors Reduce Cardiorenal Risks
 SGLT2 inhibitors are cardiorenal risk–reducing drugs with glucose
lowering as a beneficial side effect
 Based on results from DAPA-CKD and DAPA-HF
‒ SGLT2 inhibitors are cardiorenal risk–reducing drugs regardless of
glucose levels

ADA. Diabetes Care. 2021;44:S1. Slide credit: clinicaloptions.com
COMPELLING NEED TO
MINIMIZE WEIGHT GAIN OR
PROMOTE WEIGHT LOSS
SGLT2i2
+HF
 Particularly
HFrEF
(LVEF <45%)
To avoid
therapeutic inertia
reassess and modify
treatment regularly
(3-6 months)
FIRST-LINE Therapy is Metformin and Comprehensive Lifestyle (including weight management and physical activity)
INDICATORS OF HIGH-RISK OR ESTABLISHED ASCVD, CKD, OR HF†
NO
CONSIDER INDEPENDENTLY OF BASELINE A1C OR
INDIVIDUALIZED A1C TARGET, OR METFORMIN USE*
+ASCVD/Indicators of High Risk
GLP-1 RA with
proven CVD
benefit1
If A1C above target
SGLT2i with proven
benefit in this
population5,6,7
COMPELLING NEED TO MINIMIZE
HYPOGLYCEMIA
DPP-4i GLP-1 RA SGLT2i TZD
If A1C
above target
If A1C
above target
If A1C
above target
If A1C
above target
SGLT2i
OR
TZD
SGLT2i
OR
TZD
GLP-1 RA
OR
DPP-4i
OR
TZD
SGLT2i
OR
DPP-4i
OR
GLP-1 RA
If A1C above target
GLP-1 RA with
good efficacy
for weight loss10
GLP-1 RA with
good efficacy for
weight loss8
SGLT2i
EITHER/OR
If A1C above target
COST IS A MAJOR ISSUE9-10
SU4 TZD12
TZD12 SU4
If A1C above target
If A1C above target
IF A1C ABOVE INDIVIDUALIZED TARGET PROCEED AS BELOW
 Established ASCVD
 Indicators of high ASCVD risk (age
≥55 years with coronary, carotid,
or lower extremity artery stenosis
>50%, or LVH
SGLT2i with
proven CVD
benefit1
Either/or
If further intensification is required
or patient is unable to tolerate GLP-
1 RA and/or SGLT2i choose agents
demonstrating CV benefit and/or
safety:
 For patients on a GLP-1 RA,
consider adding AGLT2i with
proven CVD benefit and vice
versa
 TZD2
 DPP-4i if not on GLP-1 RA
 Basal insulin3
 SU4
+CKD
PREFERABLY
SGLT2i with primary
evidence of reducing CKD
progression
OR
SGLT2i with evidence of
reducing CKD progression
in CVOTs5,6,8
OR
GLP-1 RA with proven CVD
benefit1 if SGLT2i not
tolerated or
contraindicated
DKD and Albuminuria6
For patients with T2D and CKD8
(e.g., eGFR <60 mL/min/1.73
m2) and thus at increased risk
of cardiovascular events
NO
GLP-1 RA with
proven CVD
benefit1
SGLT2i with
proven CVD
benefit1
Either/or
Continue with addition of other agents as outlined above
If A1C above target
Consider the addition of SU4 OR basal insulin:
 Choose later generation SU with lower risk of hypoglycemia
 Consider basal insulin with lower risk of hypoglycemia9
If A1C above target
Insulin therapy basal insulin
with lowest acquisition cost
OR
Consider other therapies
based on cost
If quadruple therapy required,
or SGLT2i and/or GLP-1 RA not
tolerated or contraindicated,
use regimen with lowest risk of
weight gain
PREFERABLY
DPP-4i (if not on GLP-1 RA)
based on weight neutrality
If DPP-4i not tolerated or
contraindicated or patient
already on GLP-1 RA,
cautious addition of:
▪ SU4 ▪ TZD2 ▪ Basal Insulin

FIDELIO-DKD: Rationale
1. Alicic. Clin J Am Soc Nephrol. 2017;12:2032. 2. Mora-Fernández. J Physiol. 2014;18:3997. 3. Perkovic. NEJM. 2019;380:2295.
Metabolic1,2
(poor glycemic
control)
Hemodynamic1,2
(elevated blood
pressure and/or
intraglomerular
pressure)
Residual risk
0 6 12 18 24 30 36 42
0
5
10
15
20
25
HR: 0.70 (95% CI: 0.59-0.82; P = .00001)
Patients
With
Event
(%)
Residual risk
Placebo + ACEi/ARB
Canagliflozin + ACEi/ARB
CREDENCE3
Cardiorenal composite endpoint
High residual risk of CKD progression with current therapies

MR Overactivation: Key Driver of Kidney Damage
1. Ong. J Mol Endocrinol. 2017;58:33. 2. Bauersachs. Hypertension. 2015;65:257. 3. Bertocchio. Kidney Int. 2011;79:1051.
Overactivation of the MR signalling pathway drives inflammation and fibrosis
via pro-inflammatory cytokines and fibrotic proteins,
eg, TNF-α, IL-1b, and IL-61,2
Mineralocorticoid receptors
regulate gene expression through cofactor recruitment1
In renal disease, multiple factors overactivate the MR
including aldosterone, Rac1, cortisol, and others2,3
MR overactivation results in deleterious effects on the heart and kidney, promoting cardiac
remodeling and progression of both renal and cardiovascular disease2

Finerenone: Novel, Nonsteroidal, Selective
Mineralocorticoid Receptor Antagonist
1. Kolkhof. Handb Exp Pharmacol. 2017;243:271. 2. Kolkhof. J Cardiovasc Pharmacol. 2014;64:69. 3. Grune. Hypertension. 2018;71:599.
N
H
H2
N N
N
Bulky, nonsteroidal molecule1
Unique structure results in selective and potent interaction
with the MR and regulation of
gene expression1
Exhibits antifibrotic and anti-inflammatory effects2,3

Potency and Selectivity of Mineralocorticoid Receptor
Antagonists
Kolkhof. Handb Exp Pharmacol. 2017;243:271.
Potency Selectivity Metabolites
Tissue Distribution*
(Kidney/Heart)
Spironolactone
Steroidal
High Low Multiple, active Higher in kidney
Eplerenone Low Medium No active metabolites Higher in kidney
Finerenone
Nonsteroidal
High High No active metabolites
Balanced in heart and
kidney
*Based on standard whole-body quantitative analysis in healthy rats.

FIDELIO-DKD: Hypothesis
 Finerenone is a novel, selective, nonsteroidal MRA that inhibits
inflammation and fibrosis and protects against progressive kidney and
CV dysfunction in preclinical models1
 In ARTS-DN, finerenone improved albuminuria independent of
measured changes in BP in patients with CKD and T2D2
1. Agarwal. Eur Heart J. 2021. 42:152. 2. Bakris. JAMA. 2015;314:884. 3. Bakris. Am J Nephrol. 2019;50:333.
Hypothesis: MR antagonism with finerenone slows CKD progression and reduces cardiovascular
morbidity and mortality in patients with advanced CKD and T2D3

FIDELIO-DKD: Eligibility Criteria
*Known significant nondiabetic kidney disease, including clinically relevant renal artery stenosis. †Mean sitting SBP ≥170 mm Hg or mean sitting
DBP ≥110 mm Hg at the run-in visit or mean sitting SBP ≥160 mm Hg or mean sitting DBP ≥100 mm Hg at the screening visit.
• Aged ≥18 yr with CKD and T2D
• Pretreated with optimized therapy with
either an ACEi or ARB for ≥4 wk
• Serum potassium ≤4.8 mmol/L
• Diabetic retinopathy for patients with
moderately elevated albuminuria
Key inclusion criteria
Albuminuria Categories
(mg albumin/g creatinine)
A1
Normal to mildly
elevated
A2
Moderately
elevated
A3
Severely elevated
0-29 30-299 ≥300-4999
GFR
Categories
(mL/min/1.73
m
2
)
G1 >90
G2 60-89
G3a 45-59
G3b 30-44
G4 15-29
G5 <15
• HFrEF with NYHA class II/IV
• Other kidney disease*
• A1C >12%
• Uncontrolled arterial hypertension†
Key exclusion criteria
10% 80%
10%
Bakris. Am J Nephrol. 2019;50:333. Slide credit: clinicaloptions.com

FIDELIO-DKD: Study Design
*10 mg if screening eGFR <60 ml/min/1.73 m2; 20 mg if ≥60 ml/min/1.73 m2, up titration encouraged from Month 1 if serum potassium ≤4.8 mEq/L and eGFR
stable. †Kidney failure defined as end-stage kidney disease (initiation of chronic dialysis for ≥90 days or kidney transplantation) or eGFR <15 mL/min/1.73 m2.
13,911 patients
enrolled
2.6-yr median
follow-up
Post-treatment
follow-up
Post-treatment
follow-up
Placebo
Finerenone 10 or 20 mg OD*
R
Screening
Run-in
5734 patients
randomized
Hierarchical Endpoints
Time to kidney failure,†
sustained ≥40% decrease
in eGFR from baseline, or
renal death
1. Kidney composite
Time to CV death,
nonfatal MI,
nonfatal stroke or
hospitalization for HF
2. CV composite 3. Death from any cause
4. Hospitalization for any cause
5. Change in UACR
6. Second kidney composite

FIDELIO-DKD: Patient Sample
North America
(N = 944; 16.6%)
Canada (107)
Puerto Rico (13)
United States (824)
Latin America
(N = 593; 10.5%)
Argentina (84)
Brazil (176)
Chile (31)
Colombia (182)
Mexico (120)
Europe (N = 2358; 41.6%)
Africa
(N = 99; 1.7%)
South Africa (99)
Oceania
(N = 101; 1.7%)
Australia (63)
New Zealand (38)
Austria (62)
Bulgaria (225)
Belgium (54)
Czech Republic (99)
Denmark (111)
Finland (62)
France (64)
Germany (88)
Greece (48)
Hungary (140)
Ireland (5)
Italy (206)
Lithuania (9)
Netherlands (72)
Norway (26)
Poland (112)
Portugal (130)
Romania (59)
Russia (263)
Slovakia (7)
Spain (260)
Sweden (34)
Switzerland (10)
Turkey (72)
United Kingdom (67)
Ukraine (73)
5734 patients randomized from 48 countries—5674 patients in FAS—99.7% completed the study
Asia
(N = 1579, 27.8%)
China (372)
Hong Kong (61)
Israel (252)
Japan (415)
South Korea (138)
Malaysia (77)
Philippines (77)
Taiwan (111)
Thailand (36)
Vietnam (56)

FIDELIO-DKD: Sample Baseline
Finerenone (n = 2833) Placebo (n = 2841)
Mean age, yr 65.4 65.7
Male, % 68.9 71.5
Race, %
 White
 Black
 Asian
62.7
4.9
25.3
63.9
4.4
25.4
Mean duration of T2D, yr 16.6 16.6
Mean A1C, % 7.7 7.7
Mean body mass index,kg/m2 31.1 31.3
Mean SBP, mm Hg 138.1 138.0
MeanDBP, mm Hg 75.8 75.8
Bakris. NEJM. 2020;383:2219.
 99.9% of people were on maximally titrated RAS inhibitors

FIDELIO-DKD: Baseline Laboratory Values
UACR (mg/g)
11.2%
34.3%
52.1%
2.3%
11.9%
32.7%
53.0%
2.4% 0.4%
11.8%
87.8%
0.4%
12.4%
87.2%
Finerenone Finerenone
Placebo Placebo
Mean:
44.4 ml/min/1.73 m2
Mean:
44.3 ml/min/1.73 m2
Median (IQR):
833 (441-1628)
Median (IQR):
867 (453-1645)
Mean serum potassium: finerenone 4.37 mEq/L; placebo 4.38 mEq/L
≥60 45 to <60 25 to <45 <25 <30 30 to <300 ≥300
Bakris. NEJM. 2020;383:2219.
eGFR (mL/min/1.73 m2)

FIDELIO-DKD: Albuminuria Change Over Time
Data in parenthesis are mean change from baseline
*Between baseline and Mo 4 (prespecified secondary outcome).
LS
Mean
Ratio
to
Baseline
LS mean ratio: 0.69 (0.66-0.71)*
(-34.7%)
(-4.7%)
(-41.3%)
(-3.0%)
(-29.3%)
(-39.9%)
(-2.0%)
(4.1%)
Placebo
Finerenone
Bakris. NEJM. 2020;383:2219. Slide credit: clinicaloptions.com
36
0 4 8 12 16 20 24 28 32
1.2
1.0
0.8
0.6
0.4
0.2
0.0

FIDELIO-DKD: Blood Pressure and Blood Glucose
Change in SBP Over Time Change in A1C Over Time
Mean
SBP
(mm
Hg)
(-3.20) (-2.13) (-2.84)
(-2.58)
(-1.83)
Placebo Finerenone
Mean
HbA1c
(%)
(0.03) (0.07) (0.14) (0.16) (0.09)
160
150
140
130
120
110
0 4 8 12 16 20 24 28 32 36 40 44
10
9
8
7
6
5
0 4 8 12 16 20 24 28 32 36 40 44

FIDELIO-DKD: Primary Endpoint
Kidney failure,* sustained ≥40% decrease in eGFR from baseline, or renal death
*End-stage kidney disease or an eGFR <15 mL/min/1.73 m2
Patients at Risk, n
Placebo 2833 2607 1808 787 83
Finerenone 2841 2586 1758 792 82
HR: 0.82 (95% CI: 0.73-0.93; P = .0014)
0
0
6 12 18 24 30 36 42 48
Mo to First Event
Cumulative
incidence
(%)
10
20
30
40
Placebo (600/2841)
Finerenone (504/2833)

FIDELIO-DKD: Key Secondary Endpoint
2833 2688 2017 984 111
2841 2653 1969 951 115
Patients at Risk, n
Placebo
Finerenone
Cumulative
incidence
(%)
0
0
6 12 18 24 30 36 42 48
Mo to First Event
HR: 0.86 (95% CI: 0.75-0.99; P = .0339)
10
20
15
25
5
Placebo (420/2841)
Finerenone (367/2833)
CV death, nonfatal MI, nonfatal stroke, or hospitalization for HF

FIDELIO-DKD: Treatment-Emergent Adverse Events
Safety Outcome, n (%) Finerenone (n = 2827) Placebo (n = 2831)
Any AE 2468 (87.3) 2478 (87.5)
AE related to study drug 646 (22.9) 449 (15.9)
AE leading to treatment
discontinuation
207 (7.3) 168 (5.9)
Any serious AE 902 (31.9) 971 (34.3)
Serious AE related to study drug 48 (1.7) 34 (1.2)
Serious AE leading to d/c 75 (2.7) 78 (2.8)

FIDELIO-DKD: Change in Serum Potassium Over Time
Mean
Serum
Potassium
(mmol/L)
Mean serum potassium
at baseline:
Finerenone: 4.37 ± 0.46
Placebo: 4.37 ± 0.46
(0.25)
(0.02)
(0.24)
(0.04)
(0.20)
(0.21)
(0.21)
(0.05) (0.07) (0.07)
Maximum mean difference in serum potassium between groups: 0.23 mmol/L at Mo 4
5.4
5.2
5.0
4.8
4.6
4.4
4.2
4.0
3.8
3.6
0 4 8 12 16 20 24 28 32 36 40 44

FIDELIO-DKD: Treatment-Emergent Adverse Events
Related to Hyperkalemia
*Investigator-reported treatment-emergent AEs using the MedDRA preferred terms “hyperkalemia” and “blood potassium increased.”
Patients
With
a
Treatment-Emergent
AE
(%)
25
20
15
10
5
0
Finerenone (n = 2827) Placebo (n = 2831)
516
(18.3%)
255
(9.0%)
333
(11.8%)
135
(4.8%) 64
(2.3%)
25
(0.9%)
40
(1.4%)
8
(0.3%)
0
(0%)
0
(0%)
Hyperkalemia
Related to
Study Drug
Any Hyperkalemia AE* Hyperkalemia Leading
to Permanent
Discontinuation
Hyperkalemia
Leading to
Hospitalization
Hyperkalemia
Leading to Death

Benefit–Risk in Studies Investigating RAAS Inhibition in
Similar Patient Populations
*Hyperkalemia in VA NEPHRON-D was reported as defined as potassium level >6.0 mEq/L, emergency room visit or admission for hyperkalemia
VA NEPHRON-D2
(CKD + T2D)
Lack of efficacy
Median 2.2 yr
ALTITUDE1
(CKD + T2D)
Lack of efficacy
Median 2.7 yr
Permanent
Discontinuation
due
to
Hyperkalemia
(%)*
4.8%
2.6%
9.9%
4.4%
FIDLEO-DKD
Kidney and CV efficacy
Median 2.6 yr
2.3%
0.9%
1. Parving. NEJM. 2012:367:2204. 2. Fried. NEJM. 2013;369:1892. Slide credit: clinicaloptions.com
25
20
15
10
5
0
25
20
15
10
5
0
25
20
15
10
5
0
Aliskiren + ACEi/ARB
(n = 4272)
Placebo + ACEi/ARB
(n = 4285)
ACEi + ARB (n = 724)
Placebo + ARB
(n = 724)
Finerenone +
ACEi/ARB (n = 2827)
Placebo + ACEi/ARB
(n = 2831)

1. Agarwal. Lancet. 2019;394:1540. Slide credit: clinicaloptions.com
Benefit–Risk in Studies Investigating RAAS Inhibition in
Similar Patient Populations
AMBER1
(CKD)
Efficacy not studied
12 wk
Permanent
Discontinuation
due
to
Hyperkalemia
(%)*
23.0%
6.8%
FIDLEO-DKD
Kidney and CV efficacy
Median 2.6 yr
2.3%
0.9%
40
30
20
10
0
40
30
20
10
0
Finerenone +
ACEi/ARB (n = 2827)
Placebo + ACEi/ARB
(n = 2831)
Placebo + spiro +
ACEi/ARB (n = 148)
Patiromer + spiro +
ACEi/ARB (n = 147)

Glucagon-like Peptide-1 Receptor Agonists

Holman (EXSCEL)
Marso (LEADER)
Marso (SUSTAIN-6)
Pfeffer (ELIXA)
Total (95% CI)
Heterogeneity, Tau2 = 0; Chi2 = 6.48, df = 3 (P = .091); I2 = 54%
Test for overall effect: 2-2.00 (P = .05)
0.85 (0.75-0.97)
0.87 (0.78-0.98)
0.95 (0.79-1.13)
1.12 (0.79-1.58)
0.89 (0.82-0.96)
Holman (EXSCEL)
Marso (LEADER)
Marso (SUSTAIN-6)
Pfeffer (ELIXA)
Total (95% CI)
Heterogeneity, Tau2 = 0; Chi2 = 3.83, df = 3 (P = 0.28); I2 = 22%
Test for overall effect: 2-1.10 (P = 0.27)
Meta-analysis of ALL GLP-1 Agonist CV Outcome Trials
Jia. Cardiovascular Drugs and Therapy. 2018;32:65. Slide credit: clinicaloptions.com
Favors GLP-1 Favors Placebo
0.7 0.85 0 1.2 1.5
Risk Ratio M-H, Random, 95% CI
MACE
Study or Subgroup Weight
GLP-1 Group Placebo Group
EventsTotal Events Total
839
608
108
406
7356
4668
1648
3034
16,706
905
694
146
399
7396
4675
1649
3034
16,751
33.5%
30.5%
11.2%
24.7%
100%
0.93 (0.85-1.02)
0.88 (0.76-0.97)
0.74 (0.58-0.94)
1.02 (0.89-1.16)
0.91 (0.83-1.00)
0.5 0.7 0 1.5 2
Nonfatal MI
466
281
47
270
7356
4668
1648
3034
16,706
480
317
64
261
7396
4672
1649
3034
16,751
39.1%
28.2%
6.3%
26.4%
100%
0.98 (0.86-1.10)
0.89 (0.76-1.04)
0.73 (0.51-1.06)
1.03 (0.88-1.22)
0.95 (0.86-1.04)
Holman (EXSCEL)
Marso (LEADER)
Marso (SUSTAIN-6)
Pfeffer (ELIXA)
Total (95% CI)
0.5 0.7 0 1.5 2
Nonfatal Stroke
169
159
47
67
7356
4668
1648
3034
16,706
193
177
64
60
7396
4672
1649
3034
16,751
38.5%
36.3%
11.7%
13.5%
100%
0.88 (0.72-1.08)
0.90 (0.73-1.11)
0.73 (0.51-1.06)
1.12 (0.79-1.58)
0.90 (0.79-1.02)
Holman (EXSCEL)
Marso (LEADER)
Marso (SUSTAIN-6)
Pfeffer (ELIXA)
Total (95% CI)
0.5 0.7 0 1.5 2.0
All-Cause Mortality
381
507
211
62
4668
7356
3034
1648
16,706
447
584
223
60
4672
7396
3034
1649
16,751
33.8%
43.9%
17.5%
4.7%
100%
0.89 (0.77-1.03)
0.79 (0.66-0.94)
0.96 (0.64-1.44)
0.99 (0.80-1.22)
0.88 (0.80-0.97)
Holman (EXSCEL)
Marso (LEADER)
Marso (SUSTAIN-6)
Pfeffer (ELIXA)
Total (95% CI)
Heterogeneity, Tau2 = 0; Chi2 = 1.25, df = 3 (P = 0.74); I2 = 0%
0.5 0.7 0 1.5 2
HF Hospitalization
219
218
59
122
7356
4668
1648
3034
16,706
231
248
54
127
7396
4672
1649
3034
16,751
34.9%
36.8%
8.8%
19.5%
100%
0.95 (0.79-1.14)
0.88 (0.74-1.05)
1.09 (0.76-1.57)
0.96 (0.75-1.23)
0.94 (0.84-1.04)
Holman (EXSCEL)
Marso (LEADER)
Marso (SUSTAIN-6)
Pfeffer (ELIXA)
Total (95% CI)
0.5 0.7 0 1.5 2.0
CV Death
340
219
44
156
7356
4668
1648
3034
16,706
383
278
46
158
7396
4672
1649
3034
16,751
44.6%
30.5%
5.4%
19.5%
100%

FLOW Trial: Objectives
Primary
 To demonstrate that semaglutide delays the progression of
renal impairment, and lowers the risk of renal and CV mortality
in subjects with T2D and CKD
Secondary
 To compare the effect of semaglutide vs placebo in subjects with
T2D and CKD regrading CV morbidity, peripheral artery disease,
glycemic control, body weight, blood pressure, and safety
NCT03819153.

Naaman. Diabetes Care, under review. Slide credit: clinicaloptions.com
Historical Perspective on Slowing CKD Progression
Associated With Type 2 Diabetes
Average decline in kidney function
ml/min/yr
0
2
4
6
8
10
12
1980 1987 1994 2001 2008 2015 2022
IDNT, NEJM. 2001
RENAAL, NEJM. 2001 CREDENCE, NEJM. 2019
DAPA-CKD, NEJM. 2020
FIDELIO, NEJM 2020
No Specific Therapy for CKD
Captopril Trial, NEJM. 1993
Hannadouche, BMJ. 1994
Bakris, Kidney Int. 1996
Bakris, Hypertension. 1997

Key Points
 Diabetic kidney disease is becoming more prevalent
 Newer approaches (with maximal background therapy) have slowed
CKD progression to a little less than 2-3 mL/min/yr; normal decline is
0.9 mL/min/yr
 SGLT2 inhibitors should be thought of as cardiorenal risk–reducing
agents with glucose lowering as a beneficial side effect
 Nonsteroidal MRA inhibitors should be thought of as adjunctive
therapy to slow nephropathy progression
 There are ongoing trials with different classes of agents to further
assess whether we can slow nephropathy progression

Go Online for More CCO Coverage of
Chronic Kidney Disease in Type 2 Diabetes!
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CKD in Type 2 Diabetes Webinar: Contemporary Approaches to Renoprotection

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