A Phase 3, Randomized, Double-blind, Placebo-controlled, Parallel-group, to Evaluate the Effect of Ertugliflozin on Cardiac Function in Patients With Type 2 Diabetes Who Have Inadequate Glycemic Control and Stage B Heart Failure
Phase: PHASE3
Conditions: Type2 Diabetes, Heart Failure
Sponsor: Soo Lim

1 
 
 
 
 
 
 
A Phase 3, Randomized, Double-blind, Placebo-controlled, 
Parallel group, to Evaluate the Effect of Ertugliflozin on Cardiac 
Function in Patients with Type 2 Diabetes Who Have Inadequate 
Glycemic Control and Stage B Heart Failure 
 
 
 
 
 
 
 
 
ClinicalTrials.gov ID: NCT03717194 
Date: November 10, 2016 
 

2 
 
Ertu-GLS Randomized Clinical Trial Protocol 
 
1. Objectives 
The aim of this study is to investigate the beneficial effects of ertugliflozin, a novel sodium-
glucose cotransporter 2 (SGLT2) inhibitor, on cardiac function by assessing global longitudinal 
strain (GLS) and other hemodynamic parameters through echocardiography in individuals with 
type 2 diabetes (T2D) and pre-heart failure (pre-HF) 
 
2. Hypothesis 
We hypothesize that ertugliflozin will improve cardiac function in individuals with T2D and 
pre-heart failure. 
 
3. Study design 
This randomized, double-blind, placebo-controlled, parallel-group trial aims to enroll 120 
participants. Individuals with T2D who have been on pharmacological treatment for at least 12 
weeks, without any dose adjustments prior to enrollment, will be eligible for screening. The 
screening period will last up to two weeks before randomization. To qualify for randomization, 
participants must meet an 80% compliance rate, based on pill count, and the investigator's 
discretion during the run-in phase. After randomization, participants will be blinded to their 
glycated hemoglobin (HbA1c) and fasting plasma glucose (FPG) results. To maintain blinding, 
urinary glucose excretion (UGE) results will also be masked from participants. Urine glucose, 
albumin, calcium, and creatinine will be measured separately during on-site visits. 
 
4. Study participants 
4.1. Inclusion criteria 
l 
Individuals with T2D on stable oral antidiabetic medications, excluding SGLT2 inhibitors, 
for at least 12 weeks prior to enrollment, with no dose adjustments 
l 
Estimated glomerular filtration rate (eGFR) ≥45 mL/min/1.73 m² 
l 
Pre-heart failure (pre-HF), or stage B heart failure (HF), identified based on structural or 
functional markers (Fig. 1) [1, 2]: 
o 
Structural abnormality defined as moderate left ventricular hypertrophy (LVH), 

3 
 
indicated by a left ventricular mass index (LVMI) ≥95 g/m² in women or ≥115 g/m² 
in men 
o 
Functional impairment defined as E/e’ > 15 and/or left ventricular global longitudinal 
strain (LVGLS) > −16% 
 
 
 
Fig. 1. Stages in the development of HF and recommended therapy by stage [1]. 
 
4.2.  Exclusion criteria 
l 
Individuals with type 1 diabetes 
l 
Age <20 years at the time of screening 
l 
HbA1c <7.0% or >9.5% at screening 
l 
FPG >15 mmol/L (270 mg/dL) at screening (Visit 1), confirmed by a repeat test prior to 
randomization 
l 
Use of a glucagon-like peptide-1 (GLP-1) receptor agonist within 12 weeks prior to the 
screening visit 

4 
 
l 
Women of childbearing potential without an effective contraceptive method 
l 
History of gastric surgery, including gastric banding, within 3 years before the screening 
visit 
l 
History of diabetic ketoacidosis or nonketotic hyperosmolar coma prior to screening. 
l 
Mean systolic blood pressure (BP) >180 mmHg or diastolic BP >95 mmHg after three 
separate measurements 
l 
History or current symptoms of HF 
l 
Severe anemia, or severe respiratory, hepatic, neurological, or psychiatric disorders; active 
malignant neoplasms; or any major systemic disease or short life expectancy that would 
hinder protocol implementation or interpretation of study results 
l 
Aspartate aminotransferase (AST) or alanine aminotransferase (ALT) levels more than 
three times the upper limit of normal (ULN) 
l 
Total bilirubin >1.5 times the ULN (except for Gilbert syndrome) 
l 
Use of systemic glucocorticoids (excluding topical, ophthalmic, or inhaled forms) for more 
than 10 consecutive days within 90 days prior to screening 
l 
Participation in another investigational drug trial or use of prohibited therapies within 3 
months prior to screening 
 
5. Major investigation 
5.1. GLS by transcardiac echocardiography 
The standard commercially available cardiac ultrasound machines (Vivid 7 and Vivid E9, 
General Electric Medical Systems, Milwaukee, WI, USA) will be used to perform resting 
echocardiograms. Images will be saved in raw data format for offline analysis to assess left 
ventricular (LV) wall thickness, valvular morphology, chamber volumes, and global 2D strain. 
LV mass will be measured using standard criteria and normalized to body surface area to obtain 
the LVMI [3]. LVH will be determined following the recommendations of the American 
Society of Echocardiography and the European Association of Echocardiography [4]. The 
modified Simpson’s biplane method will be used to measure the LV ejection fraction (LVEF). 
Pulsed wave Doppler recordings of LV inflow will be acquired from the apical four-
chamber view with the sample volume placed between the tips of the mitral leaflets. Peak early 
(E) and late diastolic flow velocities (A), the E/A ratio, and deceleration time of early diastolic 
flow will be measured. Pulsed wave tissue Doppler will be performed to assess peak early 

5 
 
diastolic mitral annular velocity (e’). The ratio of mitral inflow early diastolic velocity to the 
average e' velocity obtained from the septal and lateral sides of the mitral annulus (E/e’) will 
be calculated to estimate LV filling pressure, with a value >15 indicating elevated LV filling 
pressure [5]. 
For global 2D strain analysis, digital loops will be acquired from standard apical four-
chamber, three-chamber, and two-chamber views. The LV endocardial border will be traced at 
the end-systolic frame. The strain curve will be derived from the gray-scale images using 
dedicated software (EchoPAC, GE, Vingmed, Norway). Peak strain will be defined as the peak 
negative value on the strain curve during the cardiac cycle. Peak GLS will be calculated for the 
entire U-shaped LV myocardium as: LVGLS (%) = [(L end-systole − L end-diastole) / L end-
diastole] × 100 [6], where “L” represents the length of the entire LV myocardium, considered 
as one continuous segment. GLS will be averaged across the apical 4-, 3-, and 2-chamber views. 
A recent study demonstrated a strong positive correlation between GLS and ejection 
fraction (EF), particularly in individuals with LV systolic impairment (r=0.95; P<0.001) [7]. 
In contrast, LV ejection had a relatively weaker correlation with LV twist and torsion. Another 
study also showed that semi-automated GLS analysis had a strong correlation with EF, 
regardless of whether it was performed by experienced readers (r=0.98) or less experienced 
readers (r=0.91) (Fig. 2) [8]. The semi-automated GLS measurements exhibited less bias 
between experienced and less experienced readers (−1.0 ± 13%) compared to EF measurements 
(−3.5 ± 6.7%). Furthermore, repeated GLS measurements showed higher intra-class correlation 
(ICC=0.98) compared to EF (ICC=0.89). GLS analysis also takes less time, approximately one 
minute per patient, whereas biplane EF measurements take twice as long. Thus, semi-
automated GLS measurements are faster, less dependent on experience, and more reproducible 
than conventional EF measurements. 
In a recent study involving individuals with advanced chronic kidney disease, GLS was 
found to be a significant predictor of all-cause mortality [hazard ratio (HR), 1.09; 95% 
confidence interval (CI), 1.02–1.16; P<0.05] and cardiovascular (CV) mortality (HR, 1.16; 
95% CI, 1.04–1.30; P<0.05), even after adjusting for clinical factors such as LVMI and EF [9]. 
Notably, GLS had greater predictive power for both all-cause and CV mortality compared to 
EF. Impaired GLS (>−16%) was associated with a 5.6-fold increased risk of CV mortality, 
even in individuals with preserved EF. Collectively, these findings suggest that GLS is a 
valuable measure for reflecting myocardial function. 
 

6 
 
 
 
Fig. 2. Left ventricular global longitudinal strain and volumes. After the endocardial 
boundaries are defined by the user, the software generates global longitudinal strain curves 
throughout the cardiac cycle. These curves quantify myocardial deformation, represented as 
strain values, across the 4-chamber, 3-chamber, and 2-chamber views [8]. 
 
5.2. Body composition analysis using bioelectrical impedance analysis 
Whole body fat mass and fat percentage are measured using bioelectrical impedance analysis 
(BIA), a widely used method for estimating body composition by analyzing the impedance 
generated when a current flows through the body. This noninvasive, simple, and cost-effective 
technique has evolved from earlier single-frequency systems to the more accurate 
multifrequency systems used today. To date, body composition data—including whole-body 
fat mass, fat percentage, and muscle mass—obtained via BIA has been used in over 2,000 
studies, including our own, according to a PubMed search conducted on June 15, 2015 [10, 11]. 

7 
 
Participants are instructed to avoid smoking, alcohol consumption, and strenuous exercise 
for 48 hours prior to measurement. After standing on the device platform, age and gender 
information is entered into the machine. The participant's posture is confirmed, with arms 
slightly apart from the body and feet placed correctly on the platform, before a supervisor 
initiates the assessment. The hands are positioned at a 45-degree angle away from the body. 
The BIA device, such as the X-scan model, uses multiple frequencies (1, 5, 50, 250, 500 kHz, 
and 1 MHz) to assess intracellular and extracellular fluid levels, as well as total body water 
content. 
Abdominal visceral fat area (VFA) is also estimated using three multifrequency BIA 
devices (InBody 720; InBody Co., Seoul, Korea), with participants measured in a fasting state 
on the same day as their blood tests [10]. 
 
5.3. Biomarkers 
Recent studies have identified a new regulatory axis within the renin-angiotensin system (RAS) 
(Fig. 3). In this axis, angiotensin (1-7) is ultimately produced from either angiotensin I or II 
through the catalytic activity of angiotensin-converting enzyme 2 (ACE2). 
 
 
 
 
 
 
 
 
 
 
 
Fig. 3. Renin-angiotensin system. 
 
ACE2 
ACE2 is a monocarboxypeptidase primarily expressed in vascular endothelial cells and renal 
tubular epithelium. The catalytic domain of ACE2 shares 42% identity with that of angio-

8 
 
converting enzyme (ACE); however, unlike ACE, ACE2 activity is not inhibited by ACE 
inhibitors. The membrane-bound ectodomain of ACE2 can be cleaved by the metalloproteinase 
ADAM17, releasing a soluble form of ACE2. Thus, measuring plasma ACE2 reflects the level 
of soluble ACE2. Soluble ACE2 levels and activity in plasma are elevated in patients with 
chronic heart failure, cardiac dysfunction, and myocardial infarction. While ACE2 is believed 
to play a key role in cardiac protection, the exact mechanisms remain unclear. 
 
Angiotensin (1-7) 
Angiotensin (1-7) is primarily produced from angiotensin II by ACE2, with the heart, brain, 
and kidneys serving as key sites of its generation. It exerts broad effects on the cardiovascular 
system, including vasodilation, myocardial protection, antiarrhythmic actions, and 
antihypertensive effects. Additionally, it may inhibit vascular inflammation and smooth muscle 
cell proliferation via the Mas receptor. Angiotensin (1-7) is also believed to have beneficial 
effects on metabolism by reducing insulin resistance 
 
Pro–B-type natriuretic peptide 
Cardiac natriuretic peptides are released by the heart under physiological conditions and play 
a key role in maintaining cardiovascular homeostasis. They induce dilation of afferent 
arterioles and constriction of efferent arterioles in the kidneys, which increases glomerular 
filtration, promoting natriuresis and diuresis. Additionally, these peptides reduce cardiac 
preload by shifting intravascular fluid into the interstitial space. Natriuretic peptides also 
suppress the RAS, inhibiting renin release from the kidneys and aldosterone secretion from the 
adrenal glands, further enhancing natriuresis and reducing extracellular fluid volume. B-type 
natriuretic peptide (BNP) belongs to the natriuretic peptide family, which includes atrial 
natriuretic peptide (ANP) and C-type natriuretic peptide, the latter primarily secreted by the 
vascular endothelium. ANP and BNP are secreted by cardiac myocytes, with BNP 
predominantly released by atrial myocytes in a healthy heart. However, in congestive HF, 
ventricular BNP secretion increases significantly, reflecting greater ventricular stress and 
severe cardiac dysfunction. In patients with HF, BNP levels can rise by up to 107-fold 
compared to healthy individuals. 
 
High-sensitivity C-reactive protein 
 

9 
 
Increased levels of the inflammatory biomarker high-sensitivity C-reactive protein (hsCRP) 
are predictive of cardiovascular events. In a trial involving apparently healthy individuals 
without hyperlipidemia but with elevated hsCRP, the lipid-lowering drug rosuvastatin 
significantly reduced hsCRP levels by 37% and lowered the incidence of major cardiovascular 
events [12]. hsCRP concentrations were measured using enzyme-linked immunosorbent assay 
kits from BD Biosciences Pharmingen (BD Biosciences Pharmingen, Heidelberg, Germany). 
 
6. Study outcomes 
6.1. Primary outcome 
l 
Changes in LVGLS after ertugliflozin treatment in individuals with T2D and pre-HF 
compared to placebo. 
 
6.2. Secondary outcomes 
l 
Changes in LVEF 
l 
Changes in LVMI 
l 
Changes in E/e’ 
l 
Changes in left atrial volume index 
l 
Changes in LV end-diastolic volume 
 
6.3. Prespecified exploratory outcomes 
l 
Changes in body weight, body fat mass, and body fat percentage with ertugliflozin 
l 
Whether ertugliflozin reduces microalbuminuria 
l 
Impact of ertugliflozin on ACE2, angiotensin (1-7), pro-BNP, and hsCRP levels 
l 
Cardiovascular benefits of ertugliflozin, including improvement in diastolic dysfunction 
and activation of the ACE2-angiotensin (1-7) axis 
 
6.4. Safety outcome 
l 
Adverse events related to ertugliflozin treatment in individuals with T2D and pre-HF 
 
 
 

10 
 
7. Treatment 
7.1. Intervention and control 
After randomization, patients will undergo a 24-week double-blind treatment period. A total of 
102 patients aged 20 years or older will be randomly assigned in a 1:1 ratio to one of the 
following two groups: 
l 
Ertugliflozin 5 mg once daily 
l 
Placebo (identical in appearance to ertugliflozin) once daily 
 
7.2. Rescue therapy 
The following criteria will trigger alerts: 1) FPG >270 mg/dL (13.3 mmol/L) at the Week 8 
visit; 2) FPG >240 mg/dL (11.1 mmol/L) at the Week 16 visit. 
Open-label rescue medication(s) to manage hyperglycemia will be administered at the 
investigator’s discretion, following local standards of care and prescribing practices. Any 
approved medication, including oral antidiabetic drugs or insulin, may be used to treat 
hyperglycemia, with the exception of other SGLT2 inhibitors. If glycemic rescue is necessary, 
the investigational product administered during the randomized, double-blind treatment phase 
should be continued, and blinding must be maintained until the end of the study. 
 
8. Sample size calculation 
The primary endpoint of this study is the change in LVGLS from baseline to week 24. The 
hypothesis is that the ertugliflozin group will demonstrate superiority over the placebo group. 
 
l 
Null hypothesis (H₀): P₁ = P₂ ≥ δ 
l 
Alternative hypothesis (H₁): P₁ − P₂ < δ 
 
The following equation will be used for sample size estimation: 
When r = 1, 
1. Type Ⅰ error (α) = 5% (two-sided, default) 
2. Power = 1 − Type Ⅱ error (β) = 80% (default) 
3. Allocation (r) = 1 (default) 
4. Mean in the ertugliflozin group (μ₁) 
5. Mean in the placebo group (μ₂) 

11 
 
6. Standard deviation (SD) in the ertugliflozin group (SD₁) 
7. SD in the placebo group (SD₂) 
8. Dropout rate (d) = 10% (default) 
 
Since no prior interventional studies have evaluated the effect of ertugliflozin on GLS, we 
referenced studies measuring LV volume. An increase in LV volume has been used as a marker 
for assessing the impact of drug therapy on heart failure survival [13]. It has been suggested 
that a 10 mL change in LV volume is clinically significant [14]. This change corresponds to a 
15% change in EF in individuals with pre-HF, whose EF typically ranges from 30% to 50%. 
In heart failure populations, the SD for the mean difference in LV volume has been reported to 
be 7.5 [15]. For comparison, the EMPA-REG OUTCOME trial showed that empagliflozin 
reduced heart failure hospitalization by 35% [16], and the CANVAS program found that 
canagliflozin reduced heart failure hospitalization by 33% [17]. Based on these results, we 
assumed a 15% baseline GLS in both groups and a 13.2% decrease in GLS in the ertugliflozin 
group after treatment, with no change in the placebo group. We assumed a standard deviation 
of 3.5 for both groups, adopting a conservative approach. Considering an 18% dropout rate, 
the minimum required sample size is 100 participants (60 per group with a 1:1 randomization). 
Additionally, a recent study demonstrated that improvements in glycemic control (HbA1c 
reduction from 10.3 ± 2.4% to 8.3 ± 2.0%) over a 12-month period led to a 21% improvement 
in GLS and a 24% improvement in cardiac function, as estimated by septal e’ [18]. 
 
Real calculation 
1. α = 0.05 
2. 1 − β = 0.8 
3. r = 1 
4. μ1 = 17 
5. μ2 = 15 
6. SD₁ = 3.5 
7. SD₂ = 3.5 
8. d = 0.18 (18%) 
 
Number of study participants 
l 
Group 1: 46 

12 
 
l 
Group 2: 46 
l 
Total: 92 
After considering the dropout rate, the total required number of participants is 102. 
 
 
 

13 
 
References 
1. 
Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE, Jr., Drazner MH, Fonarow GC, 
Geraci SA, Horwich T, Januzzi JL et al: 2013 ACCF/AHA guideline for the 
management of heart failure: executive summary: a report of the American 
College of Cardiology Foundation/American Heart Association Task Force on 
practice guidelines. Circulation 2013, 128(16):1810-1852. 
2. 
Kosmala W, Jellis CL, Marwick TH: Exercise limitation associated with 
asymptomatic left ventricular impairment: analogy with stage B heart failure. J 
Am Coll Cardiol 2015, 65(3):257-266. 
3. 
Devereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, Reichek N: 
Echocardiographic assessment of left ventricular hypertrophy: comparison to 
necropsy findings. Am J Cardiol 1986, 57(6):450-458. 
4. 
Lang RM, Bierig M, Devereux RB, Flachskampf FA, Foster E, Pellikka PA, Picard MH, 
Roman MJ, Seward J, Shanewise JS et al: Recommendations for chamber 
quantification: a report from the American Society of Echocardiography's 
Guidelines and Standards Committee and the Chamber Quantification Writing 
Group, developed in conjunction with the European Association of 
Echocardiography, a branch of the European Society of Cardiology. J Am Soc 
Echocardiogr 2005, 18(12):1440-1463. 
5. 
Nagueh SF, Appleton CP, Gillebert TC, Marino PN, Oh JK, Smiseth OA, Waggoner 
AD, Flachskampf FA, Pellikka PA, Evangelista A: Recommendations for the 
evaluation of left ventricular diastolic function by echocardiography. J Am Soc 
Echocardiogr 2009, 22(2):107-133. 
6. 
Reisner SA, Lysyansky P, Agmon Y, Mutlak D, Lessick J, Friedman Z: Global 
longitudinal strain: a novel index of left ventricular systolic function. J Am Soc 
Echocardiogr 2004, 17(6):630-633. 
7. 
Lima MSM, Villarraga HR, Abduch MCD, Lima MF, Cruz C, Sbano JCN, Voos MC, 
Mathias WJ, Tsutsui JM: Global Longitudinal Strain or Left Ventricular Twist and 
Torsion? Which Correlates Best with Ejection Fraction? Arq Bras Cardiol 2017, 
109(1):23-29. 
8. 
Medvedofsky D, Kebed K, Laffin L, Stone J, Addetia K, Lang RM, Mor-Avi V: 
Reproducibility and experience dependence of echocardiographic indices of left 
ventricular function: Side-by-side comparison of global longitudinal strain and 

14 
 
ejection fraction. Echocardiography 2017, 34(3):365-370. 
9. 
Krishnasamy R, Isbel NM, Hawley CM, Pascoe EM, Burrage M, Leano R, Haluska BA, 
Marwick TH, Stanton T: Left Ventricular Global Longitudinal Strain (GLS) Is a 
Superior Predictor of All-Cause and Cardiovascular Mortality When Compared 
to Ejection Fraction in Advanced Chronic Kidney Disease. PLoS One 2015, 
10(5):e0127044. 
10. 
Lee DH, Park KS, Ahn S, Ku EJ, Jung KY, Kim YJ, Kim KM, Moon JH, Choi SH, Park 
KS et al: Comparison of Abdominal Visceral Adipose Tissue Area Measured by 
Computed Tomography with That Estimated by Bioelectrical Impedance Analysis 
Method in Korean Subjects. Nutrients 2015, 7(12):10513-10524. 
11. 
Park KS, Lee DH, Lee J, Kim YJ, Jung KY, Kim KM, Kwak SH, Choi SH, Park KS, 
Jang HC, Lim S: Comparison between two methods of bioelectrical impedance 
analyses for accuracy in measuring abdominal visceral fat area. J Diabetes 
Complications 2016, 30(2):343-349. 
12. 
Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM, Jr., Kastelein JJ, Koenig W, 
Libby P, Lorenzatti AJ, MacFadyen JG et al: Rosuvastatin to prevent vascular events 
in men and women with elevated C-reactive protein. N Engl J Med 2008, 
359(21):2195-2207. 
13. 
Konstam MA, Kramer DG, Patel AR, Maron MS, Udelson JE: Left ventricular 
remodeling in heart failure: current concepts in clinical significance and 
assessment. JACC Cardiovasc Imaging 2011, 4(1):98-108. 
14. 
Grothues F, Smith GC, Moon JC, Bellenger NG, Collins P, Klein HU, Pennell DJ: 
Comparison of interstudy reproducibility of cardiovascular magnetic resonance 
with two-dimensional echocardiography in normal subjects and in patients with 
heart failure or left ventricular hypertrophy. Am J Cardiol 2002, 90(1):29-34. 
15. 
Kramer DG, Trikalinos TA, Kent DM, Antonopoulos GV, Konstam MA, Udelson JE: 
Quantitative evaluation of drug or device effects on ventricular remodeling as 
predictors of therapeutic effects on mortality in patients with heart failure and 
reduced ejection fraction: a meta-analytic approach. J Am Coll Cardiol 2010, 
56(5):392-406. 
16. 
Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, Mattheus M, Devins 
T, Johansen OE, Woerle HJ et al: Empagliflozin, Cardiovascular Outcomes, and 
Mortality in Type 2 Diabetes. N Engl J Med 2015, 373(22):2117-2128. 

15 
 
17. 
Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, Shaw W, Law 
G, Desai M, Matthews DR, Group CPC: Canagliflozin and Cardiovascular and 
Renal Events in Type 2 Diabetes. N Engl J Med 2017, 377(7):644-657. 
18. 
Leung M, Wong VW, Hudson M, Leung DY: Impact of Improved Glycemic Control 
on Cardiac Function in Type 2 Diabetes Mellitus. Circ Cardiovasc Imaging 2016, 
9(3):e003643.