Comparative Cardiovascular and Renal Effectiveness and Safety of Empagliflozin and Other SGLT2i in Patients With Type 2 Diabetes (T2D) With and Without Baseline Kidney Disease in the United States
Conditions: Diabetes Mellitus, Type 2
Sponsor: Boehringer Ingelheim

ABCD
Non-Interventional Study (NIS) Protocol 
 
Document Number:
c39368586-02
BI Study Number:
1245-0228
BI Investigational
Product(s):
Jardiance® (empagliflozin)
Title:
Comparative cardiovascular and renal effectiveness and safety 
of Empagliflozin and other SGLT2i in patients with type 2 
diabetes (T2D) with and without baseline kidney disease in the 
United States
Brief lay title:
Evaluating comparative effectiveness of empagliflozin in 
patients with type 2 diabetes with and without chronic kidney 
disease 
Protocol version 
identifier:
2.0
Date of last version of 
protocol:
10June2022
PASS:
No
EU PAS register 
number:
EUPAS45682
Active substance:
A10BK03 Empagliflozin 
Medicinal product:
Jardiance® 
Product reference:
NA
Research question and 
objectives:
The primary objective of this research study is to determine the 
cardiovascular and renal effectiveness and safety of empagliflozin 
compared to dipeptidyl peptidate-4 inhibitor (DPP4i) in patients 
with T2D in the 
1. Overall cohort,
2. Patients with established kidney disease (DKD cohort), 
and
3. Patients without established kidney disease (non-DKD 
cohort).

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The secondary objective of this research study is to determine 
the cardiovascular and renal effectiveness and safety of any 
sodium glucose co-transporter-2 inhibitors (SGLT2i) compared 
to glucagon-like peptide-1 receptor agonists (GLP1RA) in 
patients with T2D, overall and by DKD status.
Country(-ies) of study:
United States of America
Author:
Marketing 
authorisation holder(s):
Boehringer Ingelheim International GmbH
Date:
26 May 2023
Page 1 of 49
Proprietary confidential information
© 2023 Boehringer Ingelheim Group of companies. All rights reserved.
This document may not - in full or in part - be passed on, reproduced, published or otherwise used without prior written permission

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1.
TABLE OF CONTENTS
TITLE PAGE.................................................................................................................. 1
1.
TABLE OF CONTENTS....................................................................................... 3
2.
LIST OF ABBREVIATIONS................................................................................ 5
3.
RESPONSIBLE PARTIES.................................................................................... 7
4.
ABSTRACT........................................................................................................... 8
5.
AMENDMENTS AND UPDATES..................................................................... 15
6.
MILESTONES..................................................................................................... 17
7.
RATIONALE AND BACKGROUND................................................................ 18
8.
RESEARCH QUESTION AND OBJECTIVES ................................................. 19
9.
RESEARCH METHODS .................................................................................... 20
9.1
STUDY DESIGN............................................................................................ 20
9.2
SETTING........................................................................................................ 20
9.2.1
Study sites ............................................................................................... 20
9.2.2
Study population ..................................................................................... 21
9.2.2.1
Inclusion criteria............................................................................... 21
9.2.2.2
Exclusion criteria ............................................................................. 21
9.2.3
Study visits .............................................................................................. 22
9.2.4
Study discontinuation.............................................................................. 24
9.3
VARIABLES .................................................................................................. 24
9.3.1
Exposures ................................................................................................ 24
9.3.2
Outcomes................................................................................................. 25
9.3.2.1
Primary renal effectiveness outcomes.............................................. 26
9.3.2.2
Secondary outcomes......................................................................... 26
9.3.3
Covariates................................................................................................ 28
9.4
DATA SOURCES........................................................................................... 28
9.5
STUDY SIZE.................................................................................................. 29
9.6
DATA MANAGEMENT................................................................................ 29
9.7
DATA ANALYSIS......................................................................................... 30
9.7.1
Phased Implementation of Analyses ....................................................... 30
9.7.2
Main analysis........................................................................................... 30

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9.7.2.1
Describe the demographic and clinical characteristics of the overall 
cohort, stratified by DKD status and drug comparator....................................... 30
9.7.2.2
Generate propensity score models and overlap weights .................. 31
9.7.2.3
Determine the effect of empagliflozin compared to DPP4i on outcomes
31
9.7.2.4
Determine the effect of SGLT2i compared to GLP1RA on outcomes32
9.8
QUALITY CONTROL................................................................................... 33
9.9
LIMITATIONS OF THE RESEARCH METHODS...................................... 34
9.10
OTHER ASPECTS ......................................................................................... 34
9.10.1
Data quality assurance............................................................................. 34
10.
PROTECTION OF HUMAN SUBJECTS .......................................................... 35
10.1
MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS .................................................................................................. 35
10.2
STUDY APPROVAL, PATIENT INFORMATION, AND INFORMED 
CONSENT ...................................................................................................... 35
10.3
STATEMENT OF CONFIDENTIALITY...................................................... 35
11.
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS
............................................................................................................................. 36
12.
REFERENCES .................................................................................................... 37
12.1
PUBLISHED REFERENCES......................................................................... 37
12.2
UNPUBLISHED REFERENCES................................................................... 39
13.
ANNEXURES ..................................................................................................... 40
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS............................................ 40
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS ............................ 42
ANNEX 3. REVIEWERS AND APPROVAL SIGNATURES................................. 49

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2.
LIST OF ABBREVIATIONS
ACD
All-Cause Death
ADR
Adverse Drug Reaction
AE
Adverse Event
AESI
Adverse Event of Special interest
AKI
Acute Kidney Injury
ASMD
Absolute Standardized Mean Difference
AT
As-Treated
BI
Boehringer Ingelheim
CA
Competent Authority
CCDS
Company Core Data Sheet
CDM
Common Data Model
CI
Confidence Interval
CML
Local Clinical Monitor 
CRA
Clinical Research Associate
CRF
Case Report Form
CTCAE
Common Terminology Criteria for Adverse Events
CTP
Clinical Trial Protocol
CV
Cardiovascular
DKD
Diabetic Kidney Disease
DMRP
Data Management and Review Plan
DPP4i
Dipeptidyl Peptidate-4 inhibitor
eCRF
Electronic Case Report Form
ED
Emergency Department
EHR
Electronic Health Record
ENCePP 
European Network of Centres for Pharmacoepidemiology and 
Pharmacovigilance 
ESRD/ESKD
End Stage Renal (Kidney) Disease
FDA
Food and Drug Administration
GCP
Good Clinical Practice
GEP
Good Epidemiological Practice

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GLP1RA
Glucagon-like Peptide-1 Receptor Agonists
GPP
Good Pharmacoepidemiology Practice
GVP
Good Pharmacovigilance Practices
HF
Heart Failure
HR
Hazard Ratio
IB
Investigator’s Brochure
IEC
Independent Ethics Committee
IQR
Interquartile Range
IRB
Institutional Review Board
ITT
Intent-to-treat
MAH
Marketing Authorization Holder
MedDRA
Medical Dictionary for Regulatory Activities
NIS
Non-Interventional Study
PASS
Post-Authorization Safety Study
PCORnet
Patient Centered Outcomes Research Network
PS
Propensity Score
QC
Quality Control
SAE
Serious Adverse Event
SEAP
Statistical and Epidemiological Analysis Plan
SGLT2i
Sodium glucose co-transporter-2 inhibitors
SOP
Standard Operating Procedure
SSDC
Study Specific Data Characterization
T1D
Type 1 Diabetes Mellitus
T2D
Type 2 Diabetes Mellitus
UTI
Urinary Tract Infection

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4.
ABSTRACT
Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
Title of study:
Comparative cardiovascular and renal effectiveness and safety of 
Empagliflozin and other sodium glucose co-transporter-2 inhibitors in 
patients with type 2 diabetes with and without baseline kidney disease 
in the United States
Rationale and 
background:
While clear renal and cardiovascular (CV) benefits of empagliflozin 
have been demonstrated in randomized clinical trials [P15-09840], the 
effectiveness of this therapy in direct comparison to other anti-
hyperglycemic therapies has not been shown among patients with 
diabetic kidney disease (DKD). Understanding the real-world clinical 
impact of empagliflozin in this high-risk population is critical to 
elucidate this medication’s effect on clinical care and outcomes.
Overall, we aim to use a large, national network of electronic health 
record (EHR) data to determine the following in a real-world 
population:
1) Characteristics of patients with T2D, both with and without DKD, 
who have been initiated on empagliflozin or any sodium glucose co-
transporter-2 inhibitors (SGLT2i) compared to those who have been 
initiated on dipeptidyl peptidate-4 inhibitor (DPP4i) or glucagon-like 
peptide-1 receptor agonists1 (GLP1RA)
2) Renal and CV effectiveness of empagliflozin compared with DPP4i 
and SGLT2i compared with GLP1RA evaluated up to 24 months 
after treatment initiation
3) Safety of empagliflozin compared with DPP4i and any SGLT2i 
compared to GLP1RA evaluated up to 24 months after treatment 
initiation
Research question and 
objectives:
The primary objective of this research study is to determine the 
cardiovascular and renal effectiveness and safety up to 24 months after 
initiation of empagliflozin compared to DPP4i in patients with T2D in 
the 
1.
Overall cohort,
2.
Patients with established kidney disease (DKD cohort) at 
baseline, and
3.
Patients without established kidney disease at baseline (non-

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Proprietary confidential information © 2023 Boehringer Ingelheim International GmbH or one or more of its affiliated companies
Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
DKD cohort).
Study design:
This will be a non-interventional study (NIS) using existing data from 
20+ US health systems that have mapped their EHR data to the 
PCORnet Common Data Model [R21-4494]. The study period will be 
from 1 Jan 2014 through 31 December 2021, which includes data after 
the start of the COVID-19 pandemic. There will be an assessment of 
COVID-era data for quality purposes and a sensitivity analysis 
excluding data from March 2020 (the assumed beginning of COVID in 
the US) to the end of study period will be performed. 
The primary aim of the study will include patients with T2D who 
initiate use of empagliflozin or DPP4i without prior use of either drug 
[class]. The analyses of all outcomes will compare patients with T2D 
initiating empagliflozin to patients with T2D initiating DPP4i.
The secondary aim of the study will be to examine cardiovascular and 
renal effectiveness and safety associated with initiation of any SGLT2i
compared to GLP1RA in patients with T2D who initiate treatment 
without prior use of either drug class.
Population:
The analysis will include adults (≥18 years) with T2D with or without 
kidney disease in the US. To study real-world treatment patterns, the 
study population will include a broad spectrum of patients initiating
empagliflozin or any SGLT2i, DPP4i or GLP1RA. The following 
inclusion and exclusion criteria will be used for each two-arm 
comparison: 
Inclusion criteria:
-
Patients ≥18 years old,
-
Having a diagnosis of T2D within 12 months prior to the index 
date based on ICD-9 and -10 codes and other available data,
-
Record of 1+ prescription for empagliflozin, any SGLT2i, any 
DPP4 inhibitor, or any GLP1RA use between 1 January 2015
and 31 December 2020, and
-
No record of any prescription for the drugs being compared 

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Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
during the 12 months preceding the index date, i.e.,
o
For the primary comparison of initiation of 
empagliflozin versus DPP4 inhibitors, patients will not 
have any prescription for empagliflozin/any SGLT2i or 
DPP4 inhibitors during the preceding 12 months.
o
For the comparison of initiation of SGLT2i versus 
GLP1RA, patients will not have any prescription for 
SGLT2i or GLP1RA during the preceding 12 months.
Exclusion criteria:
-
Aged <18 years on the first prescription date of the qualifying 
prescription,
-
Pre-existing diagnosis of Type 1 diabetes (T1D) during the 12 
months before the index date,
-
Having a disqualifying diagnosis during the 12 months before 
the index date, defined as having at least one of the following: 
estimated glomerular filtration rate (eGFR) <30, dialysis, 
polycystic kidney disease or a kidney transplant,
-
<12 months of available data before the index date, and/or no 
complete history of drug prescriptions/or other records of drug 
use during this period, defined as not having at least 1 
ambulatory visit and at least 1 medication prescription during the 
preceding 12 months, and 
-
Missing or ambiguous data on serum creatinine in the preceding 
12 months.
Variables:
Exposure variables will include:
!
Initiation of empagliflozin, GLP1RA, DPP4 inhibitors or any 
SGLT2i for the treatment of T2D
Outcomes (evaluated through 24 months after index date):
Primary effectiveness outcomes:
!
Composite of a 40% decline in eGFR, incident ESRD, or all-cause 
death (ACD)

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Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
Secondary effectiveness outcomes:
!
Individual renal events: 40% decline in eGFR, incident ESRD, 
dialysis, and kidney transplant
!
Hospitalizations for cardiovascular events: heart failure (HF), 
HF+ACD, myocardial infarction+stroke+coronary 
revascularization+ACD, myocardial infarction+stroke+ACD
!
ACD
Secondary safety outcomes:
!
Diabetic ketoacidosis
!
Severe hypoglycaemia
!
Urinary tract cancer
!
Acute kidney injury (AKI) that requires dialysis
!
Genital mycotic infection
!
Severe urinary tract infections
Covariates:
Several baseline patient characteristics will be captured in the 12
months prior to the index date. Covariates that will be included as 
covariates in the propensity scores (PS) model include (not are not 
limited to):
!
Demographics (age, sex, race/ethnicity, BMI, quarter and year of 
incident prescription, smoking status)
!
Comorbidities: history of heart failure, history of CV events (MI, 
stroke, PCI, CABG, PAD), hypertension
!
Prior/concomitant use of other glucose lowering agents
!
Prior/concomitant use of other medications e.g., cardiovascular 
agents (ACE/ARB, beta blocker, ARNi, statin) and diuretics
!
Relevant lab test results, e.g., eGFR, HbA1c, HDL-c, etc.
  Note:  See Section 9.3.3 for complete list of covariates
Data sources:
This study will utilize high-quality renal function laboratory data 
available in medical electronic health records from approximately 20 

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Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
health systems in the US that have mapped their data to the PCORnet 
Common Data Model (CDM). Sites meeting PCORnet data curation 
quality checks will be eligible to participate in this study. Sites will be 
approached for participation in this study based on an initial feasibility 
assessment to determine the extent and completeness of key data 
elements (renal laboratory data, prescription data, relevant medical 
diagnoses, and data from both inpatient and outpatient encounters).
Death data will be ascertained from site records and augmented with de-
identified encrypted linkage to external sources, which includes 
reported deaths from the government and commercial obituaries using 
Datavant Software.
Study size:
A sample size of N=7,600 per group with median follow-up duration of 
18 months will provide 80% power to detect a hazard ratio of 0.80, 
assuming an incidence rate of 30 per 1,000 patient years for the primary 
composite renal outcome in the reference cohort.    
Data analysis:
The index date in this study is defined as the date of the first recorded 
order for a qualifying prescription as a new user. Patients are required to 
have at least 1 ambulatory visit and at least 1 medication prescription in 
the 12 months prior to initiation of empagliflozin or a comparator drug 
(the look-back period). The look-back period includes the index date. 
The main analyses of this study will utilize a modified As-Treated (AT) 
approach and an Intention-to-Treat (ITT) approach will be used as a 
sensitivity analysis for the primary and secondary comparisons of the 
primary outcome.
Follow-up starts from the day after the index date until the first 
qualifying event has been met:
!
First occurrence of outcome of interest
!
Death
!
2 years following the index prescription
!
End of query specific study period (December 31, 2021)
!
Empagliflozin user starts a DPP4i or other type of SGLT2i, or if a 
DPP4i user starts any SGLT2i
o
SGLT2i user starts a GLP1RA, or a GLP1RA user starts 
any SGLT2i

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Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
!
No observed prescriptions for the index drug within 1 year (+30 
days) from the last observed prescription 
The primary analysis will be performed using overlap weighting to 
balance covariates across the two treatment arms (empagliflozin vs
DPP4i) and Cox proportional hazards modelling to determine the effect 
of drug on outcomes. To create the overlap weights, the following will 
be performed:
For each two-arm study comparison and within the DKD and non-DKD 
subgroups separately, propensity score models will be built using a 
logistic LASSO model with the covariates of interest and all subgroup
by covariate pairwise interactions. The outcome of interest is treatment 
group, with empagliflozin [or any SGT2i] as the treatment of interest 
and DPP4i [or GLP1RA] as the reference group. The 
variables/interactions that are remaining in the LASSO model are refit 
to a standard logistic regression and the resulting predicted probability 
for each patient is considered the PS. For patients on the reference 
treatment, the overlap weight is the same as the PS. For patients on the 
treatment of interest, the overlap weight is 1-PS. No trimming is 
required due to the PS weights being bounded between 0 and 1. 
Distributions of covariates in the DKD and non- DKD groups and 
further within subgroups of interest will be assessed using standardized 
mean differences. Absolute standardized mean differences will be 
visually depicted using the CONNECT-S plot.
For each outcome, incidence rates (number of events per 1000 PY of 
follow-up), hazard ratios, and corresponding 95% confidence intervals
(CI) will be presented. Hazard ratios and CI will be calculated using 
weighted Cox proportional hazards models. For the AT analysis, if an 
empagliflozin or DPP4i user initiates a GLP1RA during the follow-up
period, this will be adjusted for in the comparison of empagliflozin and 
DPP4i (and similarly for users initiating a DPP4i).
Analyses will be performed overall and within DKD subgroups. 
A sensitivity analysis will be performed using propensity score 

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Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Jardiance®
Name of active ingredient:
A10BK03 Empagliflozin
Protocol date:
Study
number:
Version/Revision:
Version/Revision 
date:
26 May 2023
1245-0228
2.0
26 May 2023
matching in place of overlap weighting. 
Another sensitivity analysis will be performed excluding data available 
from March 2020 to the end of the study period to reduce the impact of 
the pandemic. 
A sensitivity analysis for the primary efficacy comparison will be 
performed where eGFR decline requires >1 measurement during 
follow-up (instead of >2).
Given this is a retrospective study utilizing EHR data from multiple 
sites, the protocol-specified analyses may need to be modified based on 
overall data collection completeness (data latency) and final cohort 
sample sizes. 
Milestones:
-
Final protocol and SEAP: Q2 2022
-
ENCEPP registration: After finalization of the study protocol (Q2
2022)
-
Contracts executed with sites: Q1 2022
-
Data collection via distributed query: Q2 2022
-
Final report: Q4 2023
-
Manuscript submission: Q4 2023

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5.
AMENDMENTS AND UPDATES
Number
Date
Section of the 
study protocol
Amendment or 
update
Reason
1
26 May 
2023
Abstract
8.0 Research 
questions and 
objectives
9.1 Study design
9.2.2.2 
Flowchart
9.3.1 Exposures
Removal of analyses 
involving 
comparison of 
empagliflozin vs 
GLP1RA. 
Phase 1 analyses 
indicated 
differences in 
treatment exposure 
between patients 
prescribed 
empagliflozin 
compared to those 
prescribed 
GLP1RAs (i.e., 
greater proportion 
of patients 
prescribed 4+ 
prescriptions 
observed for 
GLP1RA over 
follow up)
Timelines/milestones 
extended
Update protocol to 
reflect study 
progress at time of 
amendment
EU PASS Register 
Number added
Number not 
available at time of 
initial protocol 
approval
9.3.2.2 
Outcomes
Added study 
outcome
The composite 
outcome of MI + 
stroke+all-cause 
death+ 
cardiovascular 
revascularization 
was previously in 
the protocol but the 
composite 
MI+stroke +all-
cause death was 
added 

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Number
Date
Section of the 
study protocol
Amendment or 
update
Reason
9.7.3.0 
Sensitivity 
analysis
Addition of acute 
HHF codes as a 
sensitivity analysis
The initial broader 
codelist for HHF 
will be performed 
but a sensitivity 
analysis only 
including HHF that 
indicate acute HF 
will be examined.

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6.
MILESTONES
Milestone
Planned Date
IRB/IEC approval
June 2021
Start of data collection
May 2022
End of data collection
July 2022
<Registration in the EU
PAS register>
June 2022
Final results ready
Q4 2023
Final report of study results:
Q4 2023

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7.
RATIONALE AND BACKGROUND
The global prevalence of diabetes has increased nearly 4-fold in the last forty years and this 
increase is projected to continue [R21-4492]. Diabetic kidney disease (DKD) affects 30-40% 
of persons with diabetes and is the leading cause of end-stage renal disease (ESRD) in the 
Unites States [P18-00615, R19-1661].] The development of DKD substantially increases the 
risk of mortality for persons with diabetes [R13-0685].] Empagliflozin and other sodium-
glucose cotransporter 2 inhibitors (SGLT2i) have emerged as the first promising advance in 
the care of DKD for nearly two decades. While kidney and cardiovascular outcomes trials 
have demonstrated clear cardiorenal benefit for empagliflozin and SGLT2i above standard 
care and renin-angiotensin-aldosterone axis blockade [P15-09840, P16-06807, R19-1356, 
R21-1080],] no definitive study has compared the effectiveness of empagliflozin to other 
anti-hyperglyemic therapies. Since some of these therapies have putative cardiorenal benefits 
and risks [R18-1139, R17-1732, R21-4493], a direct comparison of empagliflozin and 
SGLT2i to these therapies is imperative. 
In addition, the EMPRISE US study [P21-10532] used diagnostic coding from claims data to 
identify incident cases of end stage renal disease (ESRD) as the main renal outcomes and 
assessed the comparative effectiveness of empagliflozin vs DPP4 inhibitors. The current
study builds upon the EMPRISE US study by also including key aspects of laboratory data 
that allow for assessment of eGFR-based renal outcomes and analyses of CKD cohorts 
defined by eGFR levels. This is a relevant adaptation to the EMPRISE US study 
methodology in that use of eGFR assessments of renal function are a more sensitive approach 
for categorizing CKD stages and monitoring changes in renal function over time. If feasible, 
this study will also include comparisons of risk for study outcomes between empagliflozin or 
SGLT2i compared to both DPP4 inhibitors and GLP1RAs.  GLP1RA was not included in the 
EMPRISE studies as a comparison group.  

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8.
RESEARCH QUESTION AND OBJECTIVES
The primary purpose of this research study is to determine the cardiovascular and renal 
effectiveness and safety of empagliflozin compared to DPP4i in patients with T2D in the 
!
Overall cohort,
!
Patients with established kidney disease (DKD cohort), and
!
Patients without established kidney disease (non-DKD cohort).
The secondary purpose of this research study is to determine the cardiovascular and renal 
effectiveness and safety of any SGLT2i compared to GLP1RA

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9.
RESEARCH METHODS
9.1
STUDY DESIGN
This will be a non-interventional comparative effectiveness and safety study, using existing 
(secondary) data from up to 20 US health systems that have mapped their electronic health 
record data to the PCORnet Common Data Model (CDM). The study period will be 1 January 
2014 through 31 December 2021, which includes data during the COVID-19 pandemic. 
There will be an assessment of COVID-era data for quality purposes, and we will perform a 
sensitivity analysis excluding all data available from March 2020 to the end of the study 
period. 
The primary objective of the study will include patients with T2D who initiate use of 
empagliflozin or DPP4i without prior use of either drug [class]. The primary analysis will 
compare patients with T2D initiating empagliflozin to patients with T2D initiating DPP4i.
The secondary objective of the study will include an additional cohort of patients: those with 
T2D who initiate use of any SGLT2i or GLP1RA without prior use of either drug class. 
Propensity score weighting (overlap weighting [R20-1964, R21-4495] will be used to balance 
covariates between two treatment groups in each comparison (empagliflozin vs DPP4i; 
SGLT2i vs GLP1RA). With overlap weighting, the resulting reweighted sample targets the 
subpopulation of patients with the most overlap in covariates across the two treatment groups. 
Patients in this subpopulation have substantial probability to be assigned to either treatment 
of interest, and therefore represent patients for whom there is clinical equipoise for treatment 
assignment. Propensity score models will be developed, and the reweighted populations will 
be assessed to ensure cross-treatment group covariate balance within both the DKD and non-
DKD subgroups, as well as for the overall cohorts using methods of Yang et al [R21-4497]. 
Additional details about propensity score modeling and reweighting are provided in the 
section on Data Analysis.
Study feasibility will be evaluated after data collection has occurred. If the final sample size 
does not meet the required sample size for 80% power, the planned sensitivity and subgroup 
analyses will be removed from the final study report. The primary analyses will still be 
assessed but in an exploratory capacity.  
9.2
SETTING
9.2.1
Study sites
This study will utilize high-quality renal function laboratory data available in medical 
electronic health records from approximately 20 health systems in the US that have mapped 
their data to the PCORnet Common Data Model (CDM). Sites meeting PCORnet data 
curation quality checks will be eligible to participate in this study.  

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9.2.2
Study population
The analysis will include adults (≥18 years) with type 2 diabetes with or without kidney 
disease in the US. To study real-world treatment patterns, the study population will include a 
broad spectrum of new users of empagliflozin, SGLT2i, DPP4i or GLP1RA. The following 
inclusion and exclusion criteria will be used for each two-arm comparison: 
9.2.2.1
Inclusion criteria
Inclusion criteria:
-
Patients ≥18 years old,
-
Having a diagnosis of type 2 diabetes in 12 months before the index date (defined as 
the date of initiation of empagliflozin or GLP1RA or DPP4i, based on the cohort 
evaluated), based on ICD-9 and -10 codes and other available data (see SEAP for 
details),
-
Record of prescription for empagliflozin, any SGLT2i, any DPP4 inhibitor, or any 
GLP1RA use between 1 January 2015 and 31 December 2020, and
-
No record of any prescription for the drugs being compared during the 12 months + 
30-day grace preceding the index date period, i.e.,
o
For the primary comparison of initiation of empagliflozin versus DPP4i, 
patients will not have any prescription for empagliflozin/any SGLT2i or 
DPP4i during the preceding 12 months + 30-day grace period.
o
For the comparison of initiation of SGLT2i versus GLP1RA, patients will not 
have any prescription for SGLT2i or GLP1RA during the preceding 12 
months + 30-day grace period.
9.2.2.2
Exclusion criteria
Exclusion criteria:
-
Aged <18 years on the first prescription date of the qualifying prescription,
-
Pre-existing diagnosis of T1DM during the 12 months before the index date,
-
Having a disqualifying diagnosis during the 12 months before the index date, defined 
as having at least one of the following: eGFR<30, dialysis, polycystic kidney disease 
or a kidney transplant,
-
<12 months of available data before the index date, and/or no complete history of 
drug dispensations/other records of drug use during this period, defined as not having 
at least 1 ambulatory visit and at least 1 medication prescription during the preceding 
12 months, and 
-
Missing or ambiguous data on serum creatinine in the 12 months prior to the index 
date or sex.

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9.2.4
Study discontinuation
Boehringer Ingelheim reserves the right to discontinue the study overall or at a particular 
study site at any time for the following reasons:
1. Failure to meet expected enrollment goals overall or at a particular study site
2. Emergence of any methodological, effectiveness, or safety information that could 
significantly affect continuation of the study, or any other relevant administrative 
reasons.
3. Violation of Good Pharmacoepidemiology Practice (GPP), the study protocol, or the 
contract by a study site, investigator or research collaborator, disturbing the 
appropriate conduct of the study
The investigator/the study site/research collaborator will be reimbursed for reasonable 
expenses incurred in case of study/site termination (except in case of the third reason).
9.3
VARIABLES
9.3.1
Exposures
Primary exposure (see Statistical and Epidemiological Analysis Plan for applicable drug 
codes): 
!
Main comparison:
o
Incident prescription order of empagliflozin [ATC codes: A10BK03, 
A10BD20] without prior use of any SGLT2i or DPP4 inhibitors
o
Incident prescription order of any DPP4 inhibitor without prior use of any 
DPP4 inhibitor or any SGLT2i
!
Secondary comparison:
o
Incident prescription order of any SGLT2i without prior use of SGLT2i or 
GLP1RA
o
Incident prescription order of any GLP1RA without prior use of any GLP1RA 
or SGLT2i
A modified As-Treated (AT) approach will be used for all analyses. Patients will be included 
in their incident prescription cohort with censoring occurring for the following reasons:
!
Occurrence of outcome of interest
!
Empagliflozin user has new prescription for a different SGLT2i during follow-up
!
Empagliflozin [SGLT2i] user has new prescription for the comparator drug of interest 
during follow-up
!
DPP4i or GLP1RA user has new prescription for any SGLT2i during follow-up
!
No additional prescription for the incident drug has been written in the 1 year (+30 
days) since the last observed prescription
!
2 years following index prescription
!
End of study period

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This modified approach will be used due to inconsistencies in the available prescribing data
(e.g., number of fills, number of pills) and discontinuation dates across PCORnet healthcare 
sites and the fact that claims/fill data are not available in PCORnet to supplement the written 
orders. We will assume a patient is on their initial prescription unless the criteria above have 
been met. 
To better understand potential limitations of this modified AT approach, a feasibility 
assessment will be performed once the initial data queries are performed to examine the 
extent of more detailed prescribing information (e.g., number of fills, number of pills, 
discontinuation dates) across participating healthcare sites.  If feasibility is determined by the 
investigative team, sensitivity analyses will be performed including sites with more complete 
prescribing information examining all primary and secondary outcomes (See section 9.7.2).
The intention-to-treat (ITT) approach will be used as a sensitivity analysis for the primary 
and secondary comparisons of the primary outcome. In this ITT analysis, follow-up will not 
be censored when a patient switches to, or adds, treatment with a different agent.
Primary subgroup of interest: diabetic kidney disease (DKD)
!
DKD will be defined using diagnosis codes and laboratory values based on records at 
the index encounter and from other health system encounters up to 12 months prior to 
index prescription.  Analyses will be performed overall and within subgroups of DKD 
(DKD and no DKD at baseline). 
9.3.2
Outcomes
Any outcome requiring at least 2 measurements meeting the event definition over a specified 
timeframe will have a date of event set to the date of the first measurement. 

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9.3.2.1
Primary renal effectiveness outcomes
Table 2
Primary outcome included in this study
Outcome
Definition
Composite outcome including
40% decline in eGFR
Incident end-stage renal disease 
(ESRD)
All-cause death
40% decline in eGFR: at least 2 measurements*
during follow-up of at least a 40% decline relative to 
baseline separated by ≥ 28 days [R21-4243]. 
ESKD definition: at least 1 kidney transplant or 
ESKD diagnosis/procedure1 or at least 2 dialysis 
diagnoses/procedures1 separated by ≥ 28 days or 
eGFR<15 on 2 measurements separated by ≥ 28 days
*The second eGFR measurement is required to be 
within 2 years from index, at which time, all patients 
will be censored (See Section 
9.3.2.2
Secondary outcomes
Table 3
Secondary outcomes included in this study
Outcomes
Definition1
Secondary Renal Effectiveness Outcomes
Secondary outcome 1: 40% decline in 
eGFR
Same as that used for the primary 
composite outcome
Secondary outcome 2: Incident end-stage 
kidney disease (ESKD)
As for ESRD definition from primary 
composite outcome
Secondary outcome 3: Dialysis
Incident dialysis, given dialysis in the 12 
months preceding index date is a 
disqualifying diagnosis/procedure
Secondary outcome 4: Kidney transplant
Any procedure1 associated with healthcare 
encounters, including hospitalizations and 
specialist outpatient and primary care 
encounters
Secondary CV Effectiveness Outcomes
Secondary outcome 5: Composite outcome 
including
Hospitalization for heart failure
All-cause death
Any diagnosis1 of heart failure associated 
with hospital admission, including inpatient 
and ED to inpatient encounters.
From death records provided by sites, 
supplemented with linkage using Datavant 
Software.

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Outcomes
Definition1
Secondary outcome 6: Hospitalization for 
heart failure
Any diagnosis1 associated with hospital 
admission, including inpatient and
emergency department (ED) to inpatient 
encounters
Secondary outcome 7: All-cause death
From death records provided by sites, 
supplemented with linkage using Datavant 
Software.
Secondary outcome 8: Composite outcome 
including 
MI2
Stroke2
All-cause death
Coronary revascularization procedure
For MI and stroke, any inpatient diagnosis2
associated with healthcare encounters, 
including inpatient and ED to inpatient
For all-cause death, as for secondary
outcome 7
Secondary outcome 9: Composite outcome 
including 
MI2
Stroke2
All-cause death
For MI and stroke, any inpatient diagnosis2
associated with healthcare encounters, 
including inpatient and ED to inpatient
For all-cause death, as for secondary
outcome 7
Secondary safety outcomes
Secondary outcome 10: Diabetic 
ketoacidosis
Any diagnosis1 associated with healthcare 
encounters in the inpatient setting
Secondary outcome 11: Severe 
hypoglycemia
Any diagnosis1 associated with healthcare 
encounters in the inpatient or ED setting
Secondary outcome 12: Urinary tract cancer
Two or more diagnoses1 associated with 
healthcare encounters within 2 months 
Secondary outcome 13: Severe Urinary 
Tract Infections (UTI)
Any diagnosis1 associated with healthcare 
encounters in the inpatient or ED setting 
for:
Pyelonephritis (ICD-10 codes in Annex 
Table 5-6)
Urosepsis. Combination of diagnosis code 
for UTI and a diagnosis code for sepsis 
within 1 week (ICD-10 codes for sepsis in 
Annex Table 5-6, ICD-10 codes for UTI in 
Annex Table 5-8).
In order to rule out nosocomial infection, at 
least one of the following criteria will have 

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Outcomes
Definition1
to be present within 7 days prior to the 
hospital admission:
Prescription for an antimicrobial agent
Outpatient visit with a recorded diagnosis 
code for UTI or pyelonephritis 
Outpatient visit with a recorded diagnosis 
code for UTI or pyelonephritis
Secondary outcome 14: Acute kidney injury 
that requires dialysis
Any diagnosis1 associated with inpatient 
healthcare encounters for AKI plus at least 
one inpatient encounter indicating dialysis 
within 28 days of the AKI encounter
Two or more dialysis encounters separated 
by 28 days or more will be excluded from 
this definition
Secondary outcome 15: Genital Mycotic 
infection
Any diagnosis associated with healthcare 
encounters, including hospitalizations and 
outpatient encounters, or prescription for 
fluconazole
1 Detailed variable definitions for the outcomes will be defined based on ICD diagnosis and procedure codes and CPT 
codes; 
2 As heart failure, MI and stroke are defined from diagnosis without mortality data, the outcomes include both fatal and non-
fatal events.
9.3.3
Covariates
The overall list of covariates being examined in this investigation is provided in the study 
SEAP.  The SEAP provides an overview of the variables that will either be included in the 
propensity score modeling for patient matching or presented in descriptive analyses for the 
baseline variables but will not be included in PS modeling.
9.4
DATA SOURCES
This study will utilize high-quality renal function laboratory data available in medical 
electronic health records from approximately 20 health systems in the US that have mapped 
their data to the PCORnet CDM. Sites meeting PCORnet data curation quality checks will be 
eligible to participate in this study.  Sites will be approached for participation in this study 
based on an initial feasibility assessment to determine the extent and completeness of key 
data elements (renal laboratory data, prescription data, relevant medical diagnoses, and data 
from both inpatient and outpatient encounters). Death data will be ascertained from site 
records and augmented with de-identified encrypted linkage to external sources, which 
includes reported deaths from the government and commercial obituaries using Datavant 
Software.

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misclassification through appropriate eligibility criteria (e.g., restricting to patients with 
evidence of interaction within the health system).  For time-to-event analyses, follow-up will 
be censored early if patient has lost contact with the health system (defined as 18 months 
after last encounter with the health system).
9.7
DATA ANALYSIS
Below is an overview of the statistical analyses planned for this project and the approach to 
implementation of the analyses.  
9.7.1
Phased Implementation of Analyses 
A phased approach to implementation of data analyses will be used to allow examination of 
key aspects of the patient populations by treatment group and the prescribing practices by 
treatment type (i.e., empagliflozin, any SGLT2i, DPP4i and (if feasible) GLP1RA).  A first 
phase of the analyses will focus on descriptive evaluation of differences in demographic and 
clinical patient characteristics, number and timing of prescriptions across treatment groups, 
and summary of outcome event rates aggregated across treatment arms. The main rationale 
for this phased analytic approach is to examine the potential for exposure misclassification 
due to the limited medication exposure data available in PCORnet (e.g., no pharmacy claims 
data). Secondary goals of the initial phase will be to assess the degree to which patient 
characteristics have been well balanced after propensity score weighting, and to confirm that 
the study will have adequate statistical power based on observed sample size and aggregate 
event rates for key outcomes. Results from this first analytic phase will be examined and 
discussed by members of the study team (BI and 
) prior to implementation of 
comparative outcome analysis to provide an opportunity for modification of the study 
protocol (if needed) and/or study discontinuation if determined appropriate.  Additional 
details for the phased analytic approach, along with codelists and table shells, are provided in 
the SEAP.
9.7.2
Main analysis
9.7.2.1
Describe the demographic and clinical characteristics of the overall cohort, 
stratified by DKD status and drug comparator 
Analysis: Baseline characteristics will be presented separately for each comparison cohort 
identified in sections above, resulting in one set of tables for each 2-arm comparison. 
Characteristics will include demographics, medical history, lab values, and concomitant 
medications. Continuous variables will be summarized as mean (standard deviation), median 
[25th percentile, 75th percentile], 5th and 95th percentiles, and minimum, maximum. 
Categorical variables will be presented as frequencies (%), as will any continuous variable 
that is further categorized. 
Characteristics will be presented in the unweighted cohorts. Additionally, characteristics will 
be stratified by DKD status and drug comparators. The degree of imbalance in variables 

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between comparator arms will be quantified with absolute standardized mean differences (see 
also Objective 2). 
9.7.2.2
Generate propensity score models and overlap weights 
Analysis: We will use post-LASSO overlap weighting to create the weights for analysis 
within the DKD and no DKD groups separately. For each two-arm study, propensity score 
models will be built using a logistic LASSO model with the covariates of interest and all 
subgroup (see section below) by covariate pairwise interactions. The outcome of interest is 
treatment group, with empagliflozin [or any SGLT2i] as the treatment group of interest and 
DPP4i [or GLP1RA] as the reference treatment. In the post-LASSO approach, the 
variables/interactions that are remaining in the LASSO model are refit to a standard logistic 
regression to get the final propensity score estimates and weights (effects/probabilities from 
the LASSO model would have faults due to shrinkage of the coefficient estimates) and the 
overlap weights. The predicted probabilities from the refit logistic regression are considered 
the propensity scores. For patients on the reference treatment, the overlap weight is the same 
as the PS. For patients on the treatment of interest, the overlap weight is 1-PS. No trimming is 
required due to the PS weights being bounded between 0 and 1.
For each patient, the overlap weight is the predicted propensity that the patient received the 
treatment opposite from what they were initiated on. For example, for the comparison of 
empagliflozin versus DPP4i initiation, a patient who was initiated on empagliflozin will 
receive a weight equal to (1-ps), where ‘ps’ is the estimated propensity score for 
empagliflozin initiation, and a patient who was initiated on DPP4i is weighted by ‘ps’. 
Baseline characteristics will be presented in the reweighted populations. Distributions of 
covariates in the DKD and no DKD groups and further within subgroups of interest will be 
assessed using standardized mean differences. Absolute standardized mean differences will 
be visually depicted using the CONNECT-S plot. Absolute standardized mean differences 
should be below 0.10 across covariates and subgroups but those that are less than 0.25 might 
be acceptable. 
9.7.2.3
Determine the effect of empagliflozin compared to DPP4i on outcomes 
Analysis: The effect of empagliflozin compared to DPP4i on outcomes will be assessed using 
Cox proportional hazards models in a 2-arm comparison. The analysis will include all 
patients with a valid overlap weight and will be done for overall and within DKD subgroups. 
The main analysis will assess outcomes while patients remain on initial treatment. 
Follow-up will start the day after the index date (date of initiation of empagliflozin or DPP4i) 
and will continue until the first occurrence of the outcome of interest, or end of study date 
(date of death, date of study end, 2 years after index date). For the main AT analysis, follow 
up will be censored early if an empagliflozin user starts a DPP4i or other type of SGLT2i, or 
if a DPP4i user starts any SGLT2i. For the AT analysis, if an empagliflozin or DPP4i user
initiates a GLP1RA, this will be adjusted for in the model using a time-dependent indicator 

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variable. Additionally, follow-up will be censored early if there is no indication of a new 
prescription in the year (+30 days) following the last observed prescription. 
Incidence rates will be computed as the number of first events per 100 patient years of 
follow-up. Analyses of time to first event will be performed using Cox proportional hazards 
models. Outcomes where death is a competing risk will be analyzed using cause-specific 
proportional hazards models, achieved by censoring follow-up at the time of death. All 
analyses will be adjusted for covariates (variables) that continue to be unbalanced after 
reweighting, with any additional covariates that might be of medical interest identified by the 
clinicians. Hazard ratios comparing empagliflozin to DPP4i with 95% confidence intervals 
and the adjusted two-sided p-values for superiority testing will be presented for all outcomes. 
Kaplan-Meier curves will be created for each outcome in the overall and DKD subgroups 
using the reweighted population. Kaplan-Meier curves will also be generated to summarize 
the cumulative incidence of treatment switching by comparator arm.   
9.7.2.4
Determine the effect of SGLT2i compared to GLP1RA on outcomes
Analysis: Repeat objective 3 with the secondary comparison cohort of initiators of any 
SGLT2i or GLP1RA. In this analysis, follow up will be censored early if a SGLT2i user 
starts a GLP1RA, or if a GLP1RA user starts any SGLT2i. If a SGLT2i or GLP1RA user 
initiates a DPP4 inhibitor, this will be adjusted for in the model.

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9.8
QUALITY CONTROL
The quality control, review, and monitoring plan are summarized below. Greater details are 
documented in the study DMRP.
Validation or quality control (QC) refers to establishing by objective evidence that 
requirements of programming tasks have been implemented correctly and completely. To 
ensure these requirements are met, internal and beta testing is performed for every query 
according to applicable standard operating procedures (SOP). Data quality checks will 
include evaluating variable distributions to identify extreme outliers, which will be handled 
with input from the 
clinical PI. Key variables will be evaluated for unusual patterns of 
missingness or distributions over time and by site. 
A Study Specific Data Characterization (SSDC) query will also be deployed to the selected 
sites to confirm data availability, completeness, conformance to the CDM specifications and 
study feasibility prior to the final production query. The SSDC will provide descriptive 
statistics of the data that will allow for an early evaluation of variable distributions. These 
results can often provide insights for local institutions to refine their data, and possibly 
refresh prior to the final query.
Additionally, as part of general QC standards, SAS log files will be saved after each 
production run and inspected for errors and warnings after each run by the program author.  
Log files will be free from ERROR messages, and any WARNINGS or problematic NOTEs, 
such as those concerning uninitialized variables or multi-record merging, etc., should be 
investigated and, if allowed to remain, should be reviewed with the lead statistician, with 
input from the statistical mentor if needed.
The statistical mentor will review new statistical results before they are released to the 
internal team, or in parallel (if timelines necessitate), and will review programming 
specifications and/or code as requested by the lead statistician, or as needed based on an 
assessment of risk. The 
clinical PI will review new statistical results before they are 
released to the sponsor.

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9.9
LIMITATIONS OF THE RESEARCH METHODS
Limitations of the study include:
-
Limitations inherent to all EHR-based studies, including potential for missing data 
(i.e., data that was generated through a different health system) or inaccurate data 
based on billing codes
-
The data will represent 20 large US health systems but may not be representative of or 
generalizable to the entire US population
-
Only the presence of a prescription will be used to identify drug exposure since due to 
the nature of US EHR data, which includes the unavailability of more detailed 
treatment exposure data is not available in PCORnet (i.e., no data are available for 
number of pills, or numbers of refills, days supply, or discontinuation orders).
However, to account for the maximal days supply provided in the US, patients).
Patients will be censored at 12 months following index prescription (with a 30-day 
grace period), which allows for the maximal amount of time a single prescription in 
the US is provided if no subsequent prescriptions are observed.  In EMPRISE US
[P21-10532], approximately 40% of patients were censored due to treatment 
discontinuation and the mean follow-up time on treatment was approximately 6 
months in both exposure groups.  Therefore, patients in However, the current study 
may be followed beyond time of medication exposure. ability to estimate drug 
exposure using more accurate approaches commonly implemented in real-world 
studies using claims data (e.g., calculation of days supply) will not be possible. This 
limitation could result in higher than actual number of person years of follow-up time 
beyond actual drug exposure, which could lead to attenuation of the estimated risk 
differences between treatment groups. 
-
With the advent of COVID, less laboratory and encounter data may have been 
collected, though we do not anticipate that this would differ by medication type
-
Despite adjusting for numerous factors, there may be unmeasured confounders that 
impact the estimated differences in risk across treatment groups in this analysis
-
eGFR data may not have been obtained as a part of routine clinical care, or the 
laboratory data may be missing, which is a potential limitation in all EHR analyses. 
9.10
OTHER ASPECTS
9.10.1
Data quality assurance
A quality assurance audit/inspection of this study may be conducted by the sponsor or 
sponsor’s designees or by Institutional Review Board (IRBs) / Independent Ethics Committee 
(IECs) or by regulatory authorities. The quality assurance auditor will have access to all 
medical records, the investigator’s study-related files and correspondence, and the informed 
consent documentation of this study.

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10.
PROTECTION OF HUMAN SUBJECTS
The study will be carried out in compliance with the protocol, the principles laid down in the 
Declaration of Helsinki, Guidelines for Good Pharmacoepidemiology Practice (GPP), and the 
relevant BI Standard Operating Procedures (SOPs). Standard medical care (prophylactic, 
diagnostic and therapeutic procedures) remains the responsibility of the treating physician of 
the patient.
The investigator should inform the sponsor immediately of any urgent safety measures taken 
to protect the study subjects against any immediate hazard, and also of any serious breaches 
of the protocol.
10.1
MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS
The study design involves only the analysis of retrospective data that was collected from the 
patient records in an aggregate manner. However, if during the study conduct, 
 
incidentally uncovers an adverse event (AE) associated with the use of Empagliflozin or any 
BI product, that will be reported according to local regulatory requirements for spontaneous 
AE reporting.
10.2
STUDY APPROVAL, PATIENT INFORMATION, AND INFORMED 
CONSENT
This NIS will be initiated only after all required legal documentation has been reviewed and 
approved by the respective Institutional Review Board (IRB)/Independent Ethics Committee 
(IEC) and Competent Authority (CA) according to national and international regulations. The 
same applies for the implementation of changes introduced by amendments.
10.3
STATEMENT OF CONFIDENTIALITY
Individual patient medical information obtained as a result of this study is considered 
confidential and disclosure to third parties is prohibited with the exceptions noted below. 
Patient confidentiality will be ensured by using patient identification code numbers.
Treatment data may be given to the patient’s personal physician or to other appropriate 
medical personnel responsible for the patient’s welfare. Data generated as a result of the 
study need to be available for inspection on request by the participating physicians, the 
sponsor’s representatives, by the IRB/IEC and the regulatory authorities.

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11.
PLANS FOR DISSEMINATING AND COMMUNICATING 
STUDY RESULTS
We will plan to submit both an abstract to a major CV scientific congress, as well as a 
manuscript to a leading CV peer-reviewed journal. We will also disseminate results to the 
public using methods endorsed by our stakeholder advisory group.
The rights of the investigator and of the sponsor regarding publication of the results of this 
study are described in the investigator contract. As a general rule, no study results should be 
published prior to finalization of the Study Report.

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12.
REFERENCES
12.1
PUBLISHED REFERENCES
Reference 
BI Document 
Number
Afkarian M, Sachs MC, Kestenbaum B, Hirsch IB, Tuttle KR, 
Himmelfarb J, de Boer IH. Kidney disease and increased mortality risk 
in type 2 diabetes. J Am Soc Nephrol, 2013. (PMID: 23362314)
R13-0685
Alicic RZ, Rooney MT, Tuttle KR. Diabetic Kidney Disease: 
Challenges, Progress, and Possibilities. Clin J Am Soc Nephrol, 2017. 
(PMID: 28522654)
P18-00615
Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, 
Ohlrogge AW, Malanda B. IDF Diabetes Atlas: Global estimates of 
diabetes prevalence for 2017 and projections for 2045. Diabetes Res 
Clin Pract, 2018 (PMID: 29496507)
R21-4492
Fleurence RL, Curtis LH, Califf RM, Platt R, Selby JV, Brown JS. 
Launching PCORnet, a national patient-centered clinical research 
network. J Am Med Inform Assoc, 2014. (PMID: 24821743)
R21-4494
Heerspink HJL, Stefánsson BV, Correa-Rotter R, Chertow GM, Greene 
T, Hou FF, Mann JFE, McMurray JJV, Lindberg M, Rossing P, 
Sjöström CD, Toto RD, Langkilde AM, Wheeler DC; DAPA-CKD 
Trial Committees and Investigators. Dapagliflozin in Patients with 
Chronic Kidney Disease. N Engl J Med, (PMID: 32970396)
R21-1080
Levin A, Agarwal R, Herrington WG, Heerspink HL, Mann JFE, 
Shahinfar S, Tuttle KR, Donner JA, Jha V, Nangaku M, de Zeeuw D, 
Jardine MJ, Mahaffey KW, Thompson AM, Beaucage M, Chong K, 
Roberts GV, Sunwold D, Vorster H, Warren M, Damster S, Malik C, 
Perkovic V; participant authors of the International Society of 
Nephrology’s 1st International Consensus Meeting on Defining Kidney 
Failure in Clinical Trials. International consensus definitions of clinical 
trial outcomes for kidney failure: 2020. Kidney Int., 2020. (PMID: 
32998816.)
R21-4243
Li F, Morgan KL, and Zaslavsky AM. Balancing covariates via 
propensity score weighting. J Am Statistical Assoc, 2018.
R20-1964
Mann JFE, Ørsted DD, Brown-Frandsen K, Marso SP, Poulter NR, 
Rasmussen S, Tornøe K, Zinman B, Buse JB; LEADER Steering 
Committee and Investigators. Liraglutide and Renal Outcomes in Type 
2 Diabetes. N Engl J Med, 2017. (PMID: 28854085)
R21-4493

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Reference 
BI Document 
Number
Marso SP, Daniels GH, Brown-Frandsen K, Kristensen P, Mann JF, 
Nauck MA, Nissen SE, Pocock S, Poulter NR, Ravn LS, Steinberg 
WM, Stockner M, Zinman B, Bergenstal RM, Buse JB; LEADER 
Steering Committee; LEADER Trial Investigators. Liraglutide and 
Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med, 2016. 
PMID (27295427)
R17-1732
Packer M. Worsening Heart Failure During the Use of DPP-4 
Inhibitors: Pathophysiological Mechanisms, Clinical Risks, and 
Potential Influence of Concomitant Antidiabetic Medications. JACC 
Heart Fail, 2018. (PMID: 29525332)
R18-1139
Patorno E, Pawar A, Wexler DJ, Glynn RJ, Bessette LG, Paik JM, 
Najafzadeh M, Brodovicz KG, Déruaz-Luyet A, Schneeweiss S. 
Effectiveness and safety of empagliflozin in routine care patients: 
Results from the EMPagliflozin compaRative effectIveness and SafEty 
(EMPRISE) study. Diabetes Obes Metab, 2022. (PMID: 34729891)
P21-10532
Perkovic V, Jardine MJ, Neal B, Bompoint S, Heerspink HJL, Charytan 
DM, Edwards R, Agarwal R, Bakris G, Bull S, Cannon CP, Capuano G, 
Chu PL, de Zeeuw D, Greene T, Levin A, Pollock C, Wheeler DC, 
Yavin Y, Zhang H, Zinman B, Meininger G, Brenner BM, Mahaffey 
KW; CREDENCE Trial Investigators. Canagliflozin and Renal 
Outcomes in Type 2 Diabetes and Nephropathy. N Engl J Med, 2019. 
(PMID: 30990260)
R19-1356
Thomas LE, Li F, Pencina MJ. 2020. Overlap weighting: a propensity 
score method that mimics attributes of a randomized clinical trial. 
JAMA, 2020. (PMID: 32369102)
R21-4495
Tohidi M, Hasheminia M, Mohebi R, et al. Incidence of chronic kidney 
disease and its risk factors, results of over 10 year follow up in an 
Iranian cohort. PLoSOne 201;7(9):e45304. (PMID: 23028919)
R21-4496
USRDS: United States Renal Data System Annual Data Report: 
Epidemiology of Kidney Disease in the United States, Bethesda, MD, 
National Institute of Diabetes and Digestive and Kidney Diseases, 
2015.
R19-1661
Wanner C, Inzucchi SE, Lachin JM, Fitchett D, von Eynatten M, 
Mattheus M, Johansen OE, Woerle HJ, Broedl UC, Zinman B; EMPA-
REG OUTCOME Investigators. Empagliflozin and Progression of 
Kidney Disease in Type 2 Diabetes. N Engl J Med, 2016. (PMID: 
27299675)
P16-06807
Yang S, Lorenzi E, Papadogeorgou G, Wojdyla DM, Li F, Thomas LE. 
Propensity score weighting for causal subgroup analysis. Stat Med. 
R21-4497

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Reference 
BI Document 
Number
2021. (PMID: 33982316)
Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, 
Mattheus M, Devins T, Johansen OE, Woerle HJ, Broedl UC, Inzucchi 
SE; EMPA-REG OUTCOME Investigators. Empagliflozin, 
Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J 
Med, 2015. (PMID: 26378978) 
P15-09840
12.2
UNPUBLISHED REFERENCES
Not applicable

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13.
ANNEXURES
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS
Number
Document 
reference 
number
Description
Date
Title
1
c39368586-01
Study Protocol (V 1.0)
30 June 
2022
Comparative 
cardiovascular and 
renal effectiveness and 
safety of 
Empagliflozin and 
other SGLT2i in 
patients with type 2 
diabetes (T2D) with 
and without baseline 
kidney disease in the 
United States
2
c39712001-01
Statistical and 
Epidemiological 
Analysis Plan (V 1.0)
8 July 
2022
Statistical and 
Epidemiological 
Analysis Plan (SEAP) 
for Non-Interventional 
Study (NIS) to 
compare
cardiovascular and 
renal effectiveness and 
safety of 
Empagliflozin and 
other SGLT2i in 
patients with type 2 
diabetes (T2D) with 
and without baseline 
kidney disease in the 
United States –
Version 1.0

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Number
Document 
reference 
number
Description
Date
Title
3
c39712001-02
Statistical and 
Epidemiological 
Analysis Plan (V 2.0)
TBD
Statistical and 
Epidemiological 
Analysis Plan (SEAP) 
for Non-Interventional 
Study (NIS) to 
compare
cardiovascular and 
renal effectiveness and 
safety of 
Empagliflozin and 
other SGLT2i in 
patients with type 2 
diabetes (T2D) with 
and without baseline 
kidney disease in the 
United States –
Version 2.0
4
NA
Data Management and 
Review Plan
18 July 
2022
Comparative 
cardiovascular and 
renal effectiveness and 
safety of 
Empagliflozin and 
other SGLT2i in 
patients with type 2 
diabetes (T2D) with 
and without baseline 
kidney disease in the 
United States: Data 
Management and 
Review Plan
5
c39712001-02
Study codelist (included 
with SEAP)
15June20
23
1245.0228 Empa DKD 
Codelist Master with 
Sources 15June2023

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ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS
ENCePP Checklist for Study Protocols (Revision 4)
Adopted by the ENCePP Steering Group on 15/10/2018
The European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP)
welcomes innovative designs and new methods of research. This Checklist has been developed by 
ENCePP to stimulate consideration of important principles when designing and writing a 
pharmacoepidemiological or pharmacovigilance study protocol. The Checklist is intended to promote 
the quality of such studies, not their uniformity. The user is also referred to the ENCePP Guide on 
Methodological Standards in Pharmacoepidemiology, which reviews and gives direct electronic 
access to guidance for research in pharmacoepidemiology and pharmacovigilance.
For each question of the Checklist, the investigator should indicate whether or not it has been 
addressed in the study protocol. If the answer is “Yes”, the section number of the protocol where 
this issue has been discussed should be specified. It is possible that some questions do not apply to 
a particular study (for example, in the case of an innovative study design). In this case, the answer 
‘N/A’ (Not Applicable) can be checked and the “Comments” field included for each section should be 
used to explain why. The “Comments” field can also be used to elaborate on a “No” answer. 
This Checklist should be included as an Annex by marketing authorisation holders when submitting 
the protocol of a non-interventional post-authorisation safety study (PASS) to a regulatory authority 
(see the Guidance on the format and content of the protocol of non-interventional post-authorisation 
safety studies). The Checklist is a supporting document and does not replace the format of the 
protocol for PASS presented in the Guidance and Module VIII of the Good pharmacovigilance 
practices (GVP).
Section 1: Milestones
Yes
No
N/A
Section
Number
1.1
Does the protocol specify timelines for 
1.1.1 Start of data collection1
6
1.1.2 End of data collection2
6
1.1.3 Progress report(s)
NA
1.1.4 Interim report(s)
NA
1.1.5 Registration in the EU PAS Register®
6
1.1.6 Final report of study results.
6
Comments:
Section 2: Research question
Yes
No
N/
A
Section
Number
2.1
Does the formulation of the research question 
and objectives clearly explain: 
                                                
1 Date from which information on the first study is first recorded in the study dataset or, in the case of secondary use of data, the date from 
which data extraction starts.
2 Date from which the analytical dataset is completely available.

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Section 2: Research question
Yes
No
N/
A
Section
Number
2.1.1 Why the study is conducted? (e.g. to 
address an important public health concern, a risk 
identified in the risk management plan, an emerging 
safety issue)
7
2.1.2 The objective(s) of the study?
8
2.1.3 The target population? (i.e. population or 
subgroup to whom the study results are intended to be 
generalised)
9.2.2
2.1.4 Which hypothesis(-es) is (are) to be 
tested?
NA
2.1.5 If applicable, that there is no a priori
hypothesis?
NA
Comments:
Section 3: Study design
Yes
No
N/
A
Section 
Number
3.1
Is the study design described? (e.g. cohort, case-
control, cross-sectional, other design) 
9.1
3.2
Does the protocol specify whether the study is 
based on primary, secondary or combined data 
collection?
9.1
3.3
Does the protocol specify measures of
occurrence? (e.g., rate, risk, prevalence)
9.7
3.4
Does the protocol specify measure(s) of 
association? (e.g. risk, odds ratio, excess risk, rate 
ratio, hazard ratio, risk/rate difference, number needed to 
harm (NNH))
9.7
3.5
Does the protocol describe the approach for the 
collection and reporting of adverse 
events/adverse reactions? (e.g. adverse events that 
will not be collected in case of primary data collection)
10.1
Comments:
Section 4: Source and study populations
Yes
No
N/
A
Section 
Number
4.1
Is the source population described?
9.2.2
4.2
Is the planned study population defined in 
terms of:
4.2.1 Study time period
9.2.3
4.2.2 Age and sex
9.2.2
4.2.3 Country of origin
9.2.1

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Section 4: Source and study populations
Yes
No
N/
A
Section 
Number
4.2.4 Disease/indication
9.2.2
4.2.5 Duration of follow-up
9.2.3
4.3
Does the protocol define how the study 
population will be sampled from the source 
population? (e.g. event or inclusion/exclusion criteria)
9.2.2
Comments:
Section 5: Exposure definition and 
measurement
Yes
No
N/
A
Section
Number
5.1
Does the protocol describe how the study 
exposure is defined and measured?
(e.g. operational details for defining and categorising 
exposure, measurement of dose and duration of drug 
exposure)
9.3.1
5.2
Does the protocol address the validity of the 
exposure measurement? (e.g. precision, accuracy, 
use of validation sub-study)
--
5.3
Is exposure categorised according to time 
windows?
9.2.3
5.4
Is intensity of exposure addressed? 
(e.g., dose, duration)
9.3.1
5.5
Is exposure categorised based on biological 
mechanism of action and taking into account 
the pharmacokinetics and pharmacodynamics 
of the drug?
NA
5.6
Is (are) (an) appropriate comparator(s) 
identified?
9.3.1
Comments:
Section 6: Outcome definition and 
measurement
Yes
No
N/
A
Section 
Number
6.1
Does the protocol specify the primary and 
secondary (if applicable) outcome(s) to be 
investigated?
9.3.2.1-2
6.2
Does the protocol describe how the outcomes
are defined and measured? 
9.3.2.1-2
6.3
Does the protocol address the validity of 
outcome measurement? (e.g. precision, accuracy, 
sensitivity, specificity, positive predictive value, use of 
validation sub-study)
--

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Section 6: Outcome definition and 
measurement
Yes
No
N/
A
Section 
Number
6.4
Does the protocol describe specific outcomes 
relevant for Health Technology Assessment? 
(e.g. HRQoL, QALYs, DALYS, health care services 
utilisation, burden of disease or treatment, compliance, 
disease management)
NA
Comments:
Section 7: Bias
Yes
No
N/
A
Section
Number
7.1
Does the protocol address ways to measure
confounding? (e.g. confounding by indication)
9.7.1
7.2
Does the protocol address selection bias? (e.g. 
healthy user/adherer bias)
9.2.2
7.3
Does the protocol address information bias?
(e.g. misclassification of exposure and outcomes, time-
related bias)
--
Comments:
Section 8: Effect measure modification
Yes
No
N/A
Section
Number
8.1
Does the protocol address effect modifiers?
(e.g. collection of data on known effect modifiers, sub-
group analyses, anticipated direction of effect) 
Comments:
Section 9: Data sources
Yes
No
N/A
Section 
Number
9.1
Does the protocol describe the data source(s) 
used in the study for the ascertainment of:
9.1.1 Exposure? (e.g. pharmacy dispensing, general 
practice prescribing, claims data, self-report, face-to-
face interview)
9.4, SEAP
9.1.2 Outcomes? (e.g. clinical records, laboratory 
markers or values, claims data, self-report, patient 
interview including scales and questionnaires, vital 
statistics)
9.4, SEAP
9.1.3 Covariates and other characteristics?
9.4, SEAP
9.2
Does the protocol describe the information 
available from the data source(s) on:

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Section 9: Data sources
Yes
No
N/A
Section 
Number
9.2.1 Exposure? (e.g. date of dispensing, drug 
quantity, dose, number of days of supply prescription, 
daily dosage, prescriber)
SEAP
9.2.2 Outcomes? (e.g. date of occurrence, multiple 
event, severity measures related to event)
9.3.3, SEAP
9.2.3 Covariates and other characteristics?
(e.g. age, sex, clinical and drug use history, co-
morbidity, co-medications, lifestyle)
9.3.3, SEAP
9.3
Is a coding system described for: 
9.3.1 Exposure? (e.g. WHO Drug Dictionary, 
Anatomical Therapeutic Chemical (ATC) Classification 
System)
9.3.1, SEAP
9.3.2 Outcomes? (e.g. International Classification of 
Diseases (ICD), Medical Dictionary for Regulatory 
Activities (MedDRA))
9.3.2.1-2, 
SEAP
9.3.3 Covariates and other characteristics?
9.4
Is a linkage method between data sources 
described? (e.g. based on a unique identifier or other)
9.4, SEAP
Comments:
Section 10: Analysis plan
Yes
No
N/
A
Section
Number
10.1 Are the statistical methods and the reason for 
their choice described? 
9.7.1
10.2 Is study size and/or statistical precision 
estimated?
9.5
10.3 Are descriptive analyses included?
9.7
10.4 Are stratified analyses included?
9.7.2
10.5 Does the plan describe methods for analytic 
control of confounding?
9.8
10.6 Does the plan describe methods for analytic 
control of outcome misclassification?
--
10.7 Does the plan describe methods for handling 
missing data?
9.6
10.8 Are relevant sensitivity analyses described?
9.7.2
Comments:

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Section 11: Data management and quality 
control
Yes
No
N/
A
Section
Number
11.1 Does the protocol provide information on data 
storage? (e.g. software and IT environment, database 
maintenance and anti-fraud protection, archiving)
9.6
11.2 Are methods of quality assurance described?
9.8, 9.10
11.3 Is there a system in place for independent 
review of study results? 
--
Comments:
Section 12: Limitations
Yes
No
N/
A
Section
Number
12.1 Does the protocol discuss the impact on the 
study results of:
12.1.1 Selection bias?
SEAP
12.1.2 Information bias?
12.1.3 Residual/unmeasured confounding?
(e.g. anticipated direction and magnitude of such biases, 
validation sub-study, use of validation and external data, 
analytical methods).
12.2 Does the protocol discuss study feasibility?
(e.g. study size, anticipated exposure uptake, duration of 
follow-up in a cohort study, patient recruitment, precision 
of the estimates)
9.1, 
9.2.1,
9.5
Comments:
Section 13: Ethical/data protection issues
Yes
No
N/
A
Section
Number
13.1 Have requirements of Ethics Committee/ 
Institutional Review Board been described?
10
13.2 Has any outcome of an ethical review 
procedure been addressed?
NA
13.3 Have data protection requirements been 
described?
9.6
Comments:
Section 14: Amendments and deviations
Yes
No
N/
A
Section
Number
14.1 Does the protocol include a section to 
document amendments and deviations? 
5

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Comments:
Section 15: Plans for communication of study 
results
Yes
No
N/
A
Section
Number
15.1 Are plans described for communicating study 
results (e.g. to regulatory authorities)?
NA
15.2 Are plans described for disseminating study 
results externally, including publication?
11
Comments:
Name of the main author of the 
protocol:
Date: 
3/May/2022
Main Author Signature:
____________________________________

 
 
 
APPROVAL / SIGNATURE PAGE 
Document Number: 
 
Technical Version Number:
Document Name: 
                                                                                                                 
 
Title: 
                                                                                                                   
Signatures (obtained electronically) 
Meaning of Signature  
Signed by 
Date Signed 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Document Number: 
Technical Version Number:
(Continued) Signatures (obtained electronically) 
Meaning of Signature  
Signed by 
Date Signed 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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