Cardiovascular Outcomes, and Mortality in Danish Patients With Type 2 Diabetes Who Initiate Empagliflozin Versus Glucagon-Like Peptide-1 Receptor Agonists (GLP1-RA): A Danish Nationwide Comparative Effectiveness Study [EMPLACEtm]
Conditions: Diabetes Mellitus, Type 2
Sponsor: Boehringer Ingelheim

ABCD
001-MCS-90-124_RD-01 (4.0)
 
Protocol for non-interventional studies based on existing data
 
Document Number:
c28125444-03
BI Study Number:
1245-0194
BI Investigational
Product(s):
Empagliflozin (Jardiance®)
Empagliflozin + Linagliptin (Glyxambi®)
Empagliflozin + Metformin (Synjardy®)
Title:
Cardiovascular outcomes, and mortality in Danish patients 
with type 2 diabetes who initiate empagliflozin versus
Glucagon-Like Peptide-1 Receptor Agonists (GLP1-RA): A 
Danish nationwide comparative effectiveness study
[EMPLACETM]
Brief Lay Title:
A Study Using Medical Records of Danish People with Type 2 
Diabetes Comparing Empagliflozin and Glucagon-Like Peptide-
1 Receptor Agonists (GLP1-RA) in the Occurrence of Serious 
Cardiovascular Outcomes
Protocol version 
identifier:
3.0
Date of last version of 
protocol:
08 November 2021
PASS:
No
EU PAS register 
number:
EUPAS29985
Active substance:
A10BX12 Empagliflozin
A10BK03 Empagliflozin
A10BD19 Empagliflozin + Linagliptin
A10BD20 Empagliflozin + Metformin
GLP1-RAs:
A10BJ01, A10BX04 (Exenatide)
A10BJ02, A10BX07 (Liraglutide)
A10BJ03, A10BX10 (Lixisenatide)
A10BJ05, A10BX14 (Dulaglutide)
A10BJ06 (Semaglutide)
A10AE56 (Insulin glargin + Liraglutide)
A10AE54 (Insulin glargin + Lixisenatid)

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companies
001-MCS-90-124_RD-01 (4.0)
Medicinal product:
Jardiance
Glyxambi
Synjardy
  Bydureon
Victoza
  Lyxumia
  Trulicity
  Ozempic
  Rybelsus
Xultophy
  Suliqua
Product reference:
Empagliflozin (Jardiance®): EMEA/H/C/002677
Empagliflozin + Linagliptin (Glyxambi®): EMEA/H/C/003833
Empagliflozin + Metformin (Synjardy®): EMEA/H/C/003770
  Exenatide (Bydureon®): EMEA/H/C/002020
Liraglutide (Victoza®): EMEA/H/C/001026
  Lixenatide (Lyxumia®): EMEA/H/C/002445
  Dulaglutide (Trulicity®): EMEA/H/C/002825
  Semaglutide (Ozempic®, Rybelsus®): EMEA/H/C/004174,   
  EMEA/H/C/004953
Insulin glargin + Liraglutide (Xultophy®): EMEA/H/C/002647
  Insulin glargin + Lixenatide (Suliqua®): EMEA/H/C/004243
Procedure number:
Not applicable
Joint PASS:
No
Research question and 
objectives:
To compare, among patients with type 2 diabetes in Denmark, 
clinical outcomes among new users (initiators) of empagliflozin 
versus GLP1-RA.
Country(-ies) of study:
Denmark
Authors:
On behalf of the 
Marketing authorisation 
holder(s):

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companies
001-MCS-90-124_RD-01 (4.0)
MAH contact person:
Date:
08 November 2021
Page 1 of 48
Proprietary confidential information
© 2021 Boehringer Ingelheim International GmbH or one or more of its affiliated 
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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Protocol for non-interventional studies based on existing data
BI Study Number 1245-0194
c28125444-03
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companies
001-MCS-90-124_RD-01 (4.0)
1.
TABLE OF CONTENTS
TITLE PAGE......................................................................................................... 1
1.
TABLE OF CONTENTS............................................................................. 4
2.
LIST OF ABBREVIATIONS...................................................................... 5
3.
RESPONSIBLE PARTIES.......................................................................... 6
4.
ABSTRACT................................................................................................. 7
5.
AMENDMENTS AND UPDATES........................................................... 11
6.
MILESTONES........................................................................................... 15
7.
RATIONALE AND BACKGROUND...................................................... 16
8.
RESEARCH QUESTION AND OBJECTIVES........................................ 17
9.
RESEARCH METHODS .......................................................................... 18
9.1
STUDY DESIGN................................................................................ 18
9.2
SETTING ............................................................................................ 18
9.2.1
Study population..................................................................... 18
9.2.2
Study period............................................................................ 19
9.2.3
Index prescription definition................................................... 19
9.2.4
Index date................................................................................ 19
9.2.5
Baseline and lookback period................................................. 19
9.2.6
Inclusion criteria ..................................................................... 20
9.2.7
Exclusion criteria.................................................................... 20
9.2.8
Follow-up of subjects ............................................................. 21
9.3
VARIABLES ...................................................................................... 21
9.3.1
Exposures................................................................................ 21
9.3.2
Study outcomes....................................................................... 22
9.3.3
Covariates ............................................................................... 25
9.4
DATA SOURCES............................................................................... 29
9.5
STUDY SIZE ...................................................................................... 30
9.6
DATA MANAGEMENT.................................................................... 30
9.7
DATA ANALYSIS............................................................................. 30
9.8
QUALITY CONTROL ....................................................................... 32
9.9
LIMITATIONS OF THE RESEARCH METHODS.......................... 32
10.
PROTECTION OF HUMAN SUBJECTS ................................................ 34
11.
MANAGEMENT AND REPORTING OF ADVERSE 
EVENTS/ADVERSE REACTIONS ......................................................... 35
12.
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY 
RESULTS .................................................................................................. 36
13.
REFERENCES........................................................................................... 37
13.1
PUBLISHED REFERENCES............................................................. 37
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS..................................... 40
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS..................... 41
ANNEX 3. ADDITIONAL INFORMATION .................................................... 48

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2.
LIST OF ABBREVIATIONS
AE
Adverse Event
AUC
Area under the Curve
CI
Confidence Interval
CML
Local Clinical Monitor 
CRA
Clinical Research Associate
CRF
Case Report Form
CTCAE
Common Terminology Criteria for Adverse Events
CTMF
Clinical Trial Master File
CTP
Clinical Trial Protocol
CTR
Clinical Trial Report
DMC
Data Monitoring Committee
eCRF
Electronic Case Report Form
EDC
Electronic Data Capture
EudraCT
European Clinical Trials Database
FAS
Full Analysis Set
GCP
Good Clinical Practice
HCRU
Health Care Resource Use
IB
Investigator’s Brochure
IEC
Independent Ethics Committee
IRB
Institutional Review Board
ISF
Investigator Site File
i.v.
intravenous
IVRS
Interactive Voice Response System
IWRS
Interactive Web-based Response System
LABKA 
The clinical laboratory information system (LABKA) research 
database at 
MedDRA
Medical Dictionary for Drug Regulatory Activities
MST
Medical Subteam
OPU
Operative Unit
p.o.
per os (oral)
PCC
Protocol Challenge Committee
q.d.
quaque die (once a day)
SAE
Serious Adverse Event
s.c.
subcutaneous
SPC
Summary of Product Characteristics
TCM
Trial Clinical Monitor
TDMAP
Trial Data Management and Analysis Plan
t.i.d.
ter in die (3 times a day)
TMM
Team Member Medicine
TMW
Trial Medical Writer
TSAP
Trial Statistical Analysis Plan

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Protocol for non-interventional studies based on existing data
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companies
001-MCS-90-124_RD-01 (4.0)
4.
ABSTRACT
Name of company:
Boehringer Ingelheim
Name of finished medicinal 
product:
Empagliflozin:
A10BX12, A10BK03, A10BD19,
A10BD20 
GLP1-RAs:
A10BJ01, A10BX04, A10BJ02, 
A10BX07, A10BJ03, A10BX10,
A10BJ05, A10BX14, A10BJ06,
A10AE56, A10AE54 
Name of active ingredient:
See above
Protocol date:
Study 
number:
Version/Revision:
Version/Revision date:
15JUL2018
1245-0194
3.0
08NOV2021
Title of study:
Cardiovascular outcomes, and mortality in Danish patients with type 2 
diabetes who initiate empagliflozin versus Glucagon-Like Peptide-1 
Receptor Agonists (GLP1-RA): A Danish nationwide comparative 
effectiveness study [EMPLACETM]
Rationale and 
background:
Utilization of the glucose-lowering drugs Glucagon-Like Peptide 1 Receptor 
Agonists (GLP1-RA) and Sodium-glucose Cotransporter-2 (SGLT2) 
Inhibitors has increased substantially in people with type 2 diabetes (T2D) 
worldwide. Trials have shown that the GLP1-RA liraglutide and the SGLT2 
inhibitor empagliflozin caused (13% and 14%, respectively) reductions in 
major adverse cardiac events among T2D patients with high cardiovascular 
risk, with similar reductions in HbA1c of 0.4% and 0.3%. Little is known 
about how these therapies compare regarding clinical outcomes in routine 
clinical care. In Denmark, nationwide population-based databases holding 
individual-level patient data enable comparative effectiveness studies among 
non-selected patients with T2D.
Research question 
and objectives:
Our primary objective is to compare clinical outcomes (cardiovascular 
outcomes, and mortality) among empagliflozin initiators and GLP1-RA 
initiators in Denmark
Study design:
Non-interventional cohort study using existing data. The study will use a 
new user design and compare new users of empagliflozin with new users of 
GLP1-RA.
Population:
The study population will include all eligible patients with T2D initiating 
treatment with empagliflozin or with GLP1-RA in 2015-2020.

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companies
001-MCS-90-124_RD-01 (4.0)
Name of company:
Boehringer Ingelheim
Name of finished medicinal 
product:
Empagliflozin:
A10BX12, A10BK03, A10BD19,
A10BD20 
GLP1-RAs:
A10BJ01, A10BX04, A10BJ02, 
A10BX07, A10BJ03, A10BX10,
A10BJ05, A10BX14, A10BJ06,
A10AE56, A10AE54 
Name of active ingredient:
See above
Protocol date:
Study 
number:
Version/Revision:
Version/Revision date:
15JUL2018
1245-0194
3.0
08NOV2021
Variables:
Exposure: Patients will be included on the index date of their first 
prescription for empagliflozin or GLP1-RA, respectively (either as 
monotherapy or fixed-dose combination with another drug), with or without 
treatment with other GLDs. Patients with previous use of any SGLT2i or 
GLP-1RA at any time before treatment initiation will be excluded. We will 
also exclude patients prescribed liraglutide with the brand-name Saxenda® 
(liraglutide 3.0 mg daily, approved as a treatment for obesity in 2015). 
Outcomes: The primary outcome in our study will be a composite of 
hospitalization due to stroke, myocardial infarction, unstable angina, 
coronary revascularization, hospitalized heart failure (HHF), or all-cause 
death (expanded MACE). Secondary outcomes will be inpatient hospital 
admission with a diagnosis of HF and/or initiation of community 
prescription drug therapy with loop diuretics; inpatient hospital 
admission with a diagnosis of HF and/or all-cause death; composite of 
all-cause hospitalization or death; all-cause hospitalization; all-cause 
death, and hospitalization for HF.
Hospitalization will be defined as any inpatient hospital admission at any 
Danish hospital, independent of admissions being through emergency room 
contact, by ambulance, self-referral, or via referral from GP, outpatient 
clinic, or other health care provider.
In further analyses, we will examine total health care resource use associated 
with empagliflozin or GLP1-RA, including total inpatient days, length-of-stay 
of patients with admissions, total hospital specialist outpatient clinic services 
provided, total cost of hospital care, total general practitioner services 
provided in primary care and their costs, total drug prescription use and 
pharmacy costs, and total medical costs.
Confounders: Age, gender, year of inclusion, diabetes duration, number of 
diabetes drugs used, metformin use, insulin use, diagnoses of retinopathy, 
neuropathy, or nephropathy, estimated glomerular filtration rate (eGFR), 

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Name of company:
Boehringer Ingelheim
Name of finished medicinal 
product:
Empagliflozin:
A10BX12, A10BK03, A10BD19,
A10BD20 
GLP1-RAs:
A10BJ01, A10BX04, A10BJ02, 
A10BX07, A10BJ03, A10BX10,
A10BJ05, A10BX14, A10BJ06,
A10AE56, A10AE54 
Name of active ingredient:
See above
Protocol date:
Study 
number:
Version/Revision:
Version/Revision date:
15JUL2018
1245-0194
3.0
08NOV2021
history of ischemic heart disease, cerebrovascular disease, peripheral 
vascular disease, heart failure (further divided by duration and 
primary/secondary diagnosis) ), rheumatological disease, dementia, 
osteoporosis, medical obesity, chronic obstructive pulmonary disease, 
cancer, use of angiotensin-converting-enzyme inhibitors (ACE-I) or 
angiotensin II receptor blockers (ARBs), other antihypertensives, statins, 
antiplatelet drugs, social and frailty markers, marital status, prescriptions for 
mental disorders, alcoholism, and number of prior hospital admission days
and other prior HCRU.
Data sources:
Danish population-based linked registries: The Civil Registration System, 
The Danish National Patient Register, The National Database of Reimbursed 
Prescriptions, The LABKA Database
Study size:
Source population: Approx. 0.5 mill. patients with drug-treated type 2 
diabetes in Denmark, during the period 1994-2020. The study size will be 
driven by the uptake of empagliflozin following its approval and launch in 
Denmark, with rapid increase after 2015. In 2016 there were 13,362 users of 
SGLT2 inhibitors in Denmark, including approximately 6,000 users of 
empagliflozin. In 2016, there were 24,273 users of GLP-1 receptor agonists, 
including 23,420 users of GLP1-RA

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5.
AMENDMENTS AND UPDATES

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Number
Date
Section of 
study 
protocol
Amendment 
or update
Reason
1
22 October 
2020
Milestone
Update
Interim report and 
amendment 
specifications
2
22 October 
2020
Rationale 
and 
background
Amendment
GLP1-RA class 
analysis specified 
incl rationale for 
liraglutide in the 
first 2 interim 
reports.
3
22 October 
2020
Research 
and 
objectives
Amendment
GLP1-RA class 
analysis specified
4
22 October 
2020
Study 
design
Update
Amendment
Outcome 
clarification
Stratifiers listed
GLP1-RA class 
analysis specified
5
22 October 
2020
Study 
population
Update
Amendment
Population 
description 
clarified
GLP1-RA class 
analysis specified
6
22 October 
2020
Study period
Update
Clarified to 
include data 
capture from 
entire contracting 
period (end 2020. 
expected to be 
available end 
2021)
7
22 October 
2020
Lookback
Update
Clarified 
description of 
lookback period

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Number
Date
Section of 
study 
protocol
Amendment 
or update
Reason
8
22 October 
2020
Inclusion/
Exclusion
Amendment
GLP1-RA class 
analysis specified
Define analysis 
restrictions related 
to +/- previous 
events
9
22 October 
2020
Follow up
update
Grace period and 
treatment duration 
description 
clarified
10
22 October 
2020
Outcome
Update
Cardiovascular
event definitions 
updated
11
22 October 
2020
Covariates
Update
Updated list of 
covariates
12
22 October 
2020
Data Source
Update
Clarified 
description of data
sources incl lab 
data
13
22 October 
2020
Study size
Update
Included 
information on 
most recent T2D 
and new user 
proportions and 
estimated 2020 
pers exposure/pers 
yrs.
14
22 October 
2020
Data 
analysis
Update
IIT and OT, PS 
and multivariate 
model as well as 
IPWT description 
clarified.
Strata list updated 
15
22 October 
2020
Abstract 
pages
Update
Updated according 
to the relevant 
section 
updates/amendme
nts

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Number
Date
Section of 
study 
protocol
Amendment 
or update
Reason
16
08
November
2021
Amendment
Amended HCRU 
endpoint 
definitions
17
08
November 
2021
Milestones
Update
Update of 
milestone 
achievements and 
expected dates
18
08
November 
2021
Responsible 
parties 
Update
New members of 
team
19
08
November 
2021
Study 
Outcomes
Amendment
Study outcome on 
main analysis is 
still the same. 
HCRU analysis 
added and will be 
described in SAP
20
08
November 
2021
Follow up
Update
Grace period
changed to 30 
days

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6.
MILESTONES
Milestone
Planned Date
Protocol version 1.0
15 July 2018
Start of data collection
01 January 2015
End of data collection
December 2021
Interim report 1
April 2019 (EASD abstract) / August 2019 (EASD 
Poster)
Protocol version 2.0
22 October 2020
Interim report 2
Manuscript May 2021
Protocol version 3.0
08 November 2021
Interim report 3
December 2021
Registration in the EU 
PAS register
04 June 2019
(http://www.encepp.eu/encepp/viewResource.htm?id
=37726)
Final report of study 
results:
Q4 2021 including HCRU

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7.
RATIONALE AND BACKGROUND
Utilization of the newer type 2 diabetes (T2D) medications GLP1 RA and SGLT2 inhibitors 
in Denmark has increased substantially, after clinical trials have provided evidence that these 
drugs reduce cardiovascular disease (CVD) risk beyond their glucose-lowering effect. For 
example, in the LEADER and EMPA-REG OUTCOME trials (6,7), the GLP1 RA liraglutide 
and the SGLT2 inhibitor empagliflozin caused (13% and 14%, respectively) reductions in 
major adverse cardiac events (MACE; i.e., CVD death, myocardial infarction, or stroke) 
among T2D patients, with reductions in HbA1c of 0.4% and 0.3%, respectively. Since GLP1 
RA and SGLT2 inhibitors furthermore both are associated with weight loss and low risk of 
hypoglycemia, they have become a popular choice for second-line therapy, in particular as 
add-on therapy to metformin. In Denmark, liraglutide has been the overwhelmingly used 
GLP1 RA since 2010 (8), while use of exenatide has remained low; use of lixisenatide and 
dulaglutide is still low as of 2016 (9). The initial 2 interim analyses of this study were 
restricted to comparison of empagliflozin versus liraglutide as this active medical compound 
was the single most frequently used GLP-1-RA in DK between 2015-2018. For the final 
analysis (between 2015-2020) the GLP1RA class will be used as the comparator to include
new GLP1-RA products in the evaluation of the GLP1-RA class. Regarding SGLT2 
inhibitors in Denmark, dapagliflozin has been the clearly most used SGLT2 inhibitor up to 
2015 (10), whereas from 2016 onwards the use of empagliflozin has increased substantially 
(use of canagliflozin has generally been low) (9). 
Little is known about the differences in patient characteristics between users of GLP1-RA 
versus users of empagliflozin, and how these therapies compare regarding clinical outcomes 
in routine clinical care. In Denmark, nationwide population-based databases holding 
individual-level patient data enable drug utilization studies and comparative effectiveness 
studies in clinical practice among non-selected patients with T2D (10,11). In an ongoing 
collaboration between Boehringer Ingelheim and the 
 in 
, we investigate patient characteristics at the time of empagliflozin initiation, and 
compare the characteristics with those of initiators of other frequently used newer glucose-
lowering drugs, namely: SGLT2 inhibitors other than empagliflozin, GLP-1 RA, and DPP-4 
inhibitors. Our preliminary results suggest that initiators of empagliflozin and GLP-1 RA in 
Denmark are very similar regarding demographic and clinical variables and baseline 
glycemic control. We now propose to conduct a cohort study of cardiovascular outcomes and 
mortality in Danish patients with T2D who initiate empagliflozin versus GLP1-RA.

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9.
RESEARCH METHODS
9.1
STUDY DESIGN
Non-interventional cohort study using existing data.
We will use two alternative analytic approaches in our study: an on-treatment (OT) exposure 
definition, and an intention-to-treat (ITT) exposure definition. For the OT analyses, treatment 
duration will be based on the estimated number of days covered by each filled prescription, 
calculated as the number of packages * the numerical volume of a package. A grace period of 
30 days will be added. In the OT analysis, participants are censored from further follow-up at 
either treatment cessation, initiation of an alternative drug in the study drug class (for 
example, dapagliflozin among empagliflozin users), and initiation of a drug from the 
comparator study drug class (for example, liraglutide or another GLP-1RA among 
empagliflozin users). Addition of other GLD classes are allowed.
For the ITT analyses, participants are defined as exposed from the start of treatment 
throughout follow-up, analogous to an ITT design in a clinical trial. 
In both analyses, participants will be followed from the date of initiation of empagliflozin or 
GLP1-RA treatment until outcome event, date of death, emigration, or end of study at 
December 31, 2020 or last data availability (or, in the OT analyses, also until treatment 
cessation or drug changes as explained above). In the analyses of the composite outcomes, 
patients are censored at the first occurrence of any outcome-defining event. For individual 
outcomes, patients are censored at the first occurrence of the outcome analyzed, independent 
of other outcomes. We will construct adjusted cumulative incidence curves for the different 
outcomes, taking competing risk of death into account when examining non-fatal outcomes. 
We will use Cox proportional hazards regression with time since treatment initiation as the 
underlying timescale to compute adjusted hazard ratios (aHRs) with 95% CIs. We will repeat 
all outcome analyses among empagliflozin vs. GLP1-RA initiators stratified by different 
baseline characteristics, i.e. by applying propensity score balancing of potential confounders 
across the two treatment groups within strata of sex, age (=65 years), presence or absence of 
cardiovascular disease at baseline (ischemic heart disease, HF, cerebrovascular disease, or 
peripheral vascular disease), current insulin use, current metformin use, and calendar periods 
before and after publication of the EMPA-REG OUTCOME and LEADER CVOTs (current 
analysis Jan 2015 – June 2016, July 2016 – Dec 2018).
9.2
SETTING
9.2.1
Study population
The source population for our study consists of individuals with T2D, who are defined in our 
study as individuals who live in Denmark and have ever used oral antihyperglycemic drugs or 
insulin (ATC-codes A10A, A10B) between 1994-2020, defined as one or more prescriptions 
for: metformin, sulfonylureas, thiazolidinediones, DPP-4 inhibitors, GLP-1 receptor agonists, 
SGLT2 inhibitors, insulin, alfa-glucosidase inhibitors, other oral antihyperglycemic drugs, or 
combination products, according to the Anatomical Therapeutic Chemical (ATC) 

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classification system (12). Diabetic patients who under the age of 30 used insulin as mono-
therapy and never used oral antihyperglycemic medications will be excluded as likely T1D 
patients (2,13). Within this source population, we will identify our study population of adult 
type 2 diabetes patients initiating empagliflozin or GLP1-RA between 2015-2020.
The use of hospital ICD codes recorded in the Danish National Patient Register to identify 
patients with diabetes excluding gestational diabetes can only identify diabetes patients who 
required hospital treatment and treatment by hospital-based specialist doctors. Uncomplicated 
type 2 diabetes is usually treated by general practitioners (i.e., ~80% of type 2 diabetes 
patients are followed mainly in primary care), and thus not completely registered in hospital 
registries (14). The sensitivity of the Danish National Patient Register in identifying patients 
with known diabetes through diabetes diagnosis codes has been estimated at 64% (as most 
people with diabetes have hospital contact at some point of time), while the PPV of a diabetes 
diagnosis in the same Register is 97% (15). In comparison, the sensitivity of the Danish 
National Prescription Registry in identifying patients with diabetes through one or more 
glucose-lowering drug prescriptions has been estimated at 72% (as not all diabetes is drug 
treated), while the PPV of one glucose-lowering drug prescription for presence of diabetes is 
95% (15). In the case of the present study all patients redeeming a prescription for the drugs 
examined will be registered with the Danish National Prescription Registry (16). 
Empagliflozin and GLP1-RA are prescribed/started as initial drug both by general 
practitioners (GPs) and specialist physicians in Denmark, and most of the follow-up 
prescriptions (for chronic treatment) will be issued by GPs or primary care physicians. All 
these prescriptions, no matter which physician prescribed them, are dispensed and registered 
on the individual level at essentially monopolized community pharmacies in Denmark, and 
therefore, new user data for the drugs is complete on the national level.
9.2.2
Study period
The planned study period is 1 January 2015 to 31 December 2020. Empagliflozin was 
launched in Denmark August 2014. 
9.2.3
Index prescription definition
The index prescription will be the first prescription for the study medication of interest that 
fulfils the definition of new user during the study period. Index prescriptions/dispensings of 
the study drugs include the single study drugs or fixed-dose combinations of the study drugs 
with other glucose-lowering drugs.
9.2.4
Index date
The index date will be defined as the date on which each identified new user receives the 
index prescription for empagliflozin or GLP1-RA.
9.2.5
Baseline and lookback period
To characterize the empagliflozin and GLP1-RA cohorts at the time of study drug initiation, 
all information available during the lookback (pre-index) time period will be collected. The 
lookback time period is defined as the time period ending on the index date. All cohort 

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members are required to have at least 12 months of data history before the index date 
(baseline period), the lookback period will therefore include at least 365 days during which 
covariates can be evaluated. For most cohort members, more data on covariates is available 
beyond 365 days. Thus, the look-back period for co-medication will be 365 days and up to 15 
years for chronic co-diagnoses.
9.2.6
Inclusion criteria
All patients will be required to meet all of the following criteria:
•
Be aged 18 or more years at the index date (date of initiation of empagliflozin or 
GLP1-RA).
•
Have at least 12 months of residency in Denmark prior to the index date. 
•
Have T2D ever before the index date (defined in detail under study population)
The empagliflozin-exposed population must also meet the following criteria:
•
Have at least one prescription for empagliflozin or fixed-dose combination of 
empagliflozin with another drug, with or without treatment with another glucose-lowering 
drug.
•
Have no prescription/dispensing of SGLT2 inhibitors (including empagliflozin) alone 
or in fixed-dose combination prior to the index date.
•
Have no prescription/dispensing of a GLP-1 RA alone or in fixed-dose combination 
prior to the index date.
The population exposed to GLP1-RA must meet the following criteria:
•
Have at least one prescription for GLP1-RA or a fixed-dose combination of GLP1-RA 
with another drug, with or without treatment with another glucose-lowering drug.
•
Have no prescription/dispensing of a GLP-1 receptor agonist alone or in fixed-dose 
combination prior to the index date.
•
Have no prescription/dispensing of SGLT2 inhibitors (including empagliflozin) alone 
or in fixed-dose combination prior to the index date.
9.2.7
Exclusion criteria
Patients with type 1 diabetes T1D before the index date will not be included in the study. 
In general, analysis will include patients with previous outcome events, and adjustment for 
the history of these events will be carried out in the regression models rather than excluding 
them (e.g. assess outcome rates of myocardial infarction in empagliflozin and GLP1-RA 
initiators while adjusting for previous history of myocardial infarction, unstable angina, or 
coronary revascularization) to asses first event after SGLT2 or GLP1-RA initiation. 
However, an analysis of a composite of first incident HHF or first initiation of loop diuretic 
therapy will be restricted to patients with no previous HHF or loop-diuretic use. 

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9.2.8
Follow-up of subjects
Follow-up will start the day after the index date, which will be the date of the first 
prescription for empagliflozin or GLP1-RA including the index date.
For the analysis of each outcome, follow-up time in a given cohort in a given exposure 
category for each patient will end at whichever of the following dates occurs first:
•
The date of the outcome event; acute hospital admission with heart failure (or 
initiation of loop diuretics), stroke, myocardial infarction, unstable angina, or coronary 
revascularization, or all-cause acute hospital admission
•
The date of death.
•
The date of study end.
•
The emigration date out of Denmark.
For the OT analyses, treatment duration will be based on the estimated number of days 
covered by each filled prescription, calculated as the number of packages * the numerical 
volume of a package. A grace period of 30 days will be added. In the OT analysis, 
participants are censored from further follow-up at either treatment cessation, initiation of an 
alternative drug in the study drug class (for example, dapagliflozin among empagliflozin 
users), and initiation of a drug from the comparator study drug class (for example, liraglutide 
or another GLP-1RA among empagliflozin users).
For the ITT analyses, participants are defined as exposed from the start of treatment 
throughout follow-up, analogous to an ITT design in a clinical trial. 
Follow-up will not be censored if glucose-lowering drugs other than the index drugs are 
prescribed in addition to empagliflozin or GLP1-RA after the index date. 
9.3
VARIABLES
9.3.1
Exposures
For this study, eligible patients will be identified from prescription/dispensing for the study 
medications of interest listed in the Danish prescription registries:
A10BX12 (Empagliflozin (Jardiance®))
A10BK03 (Empagliflozin (Jardiance®))
A10BD19 (Empagliflozin + Linagliptin (Glyxambi®))
A10BD20 (Empagliflozin + Metformin (Synjardy®))

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GLP1-RAs:
A10BJ01, A10BX04 (Exenatide (Bydureon®)
A10BJ02, A10BX07 (Liraglutide (Victoza®)
A10BJ03, A10BX10 (Lixisenatide (Lyxumia®)
A10BJ05, A10BX14 (Dulaglutide (Trulicity®)
A10BJ06 (Semaglutide (Ozempic® Rybelsus®)
A10AE56 (Insulin degludec + Liraglutide (Xultophy®)
A10AE54 (Insulin glargin + Lixisenatid (Suliqua®)
9.3.2
Study outcomes
The primary outcomes of interest for this study are the time from “index date” until (first) 
event of cardiovascular outcomes and mortality. 
Primary study outcome: 
!
“Expanded MACE”: All-cause death, acute admission with non-fatal (within 30 
days) stroke, acute admission with non-fatal (within 30 days) MI, admission with 
unstable angina, coronary revascularization, or acute admission with non-fatal HF
Secondary outcomes of interest:
!
Inpatient hospital admission with a diagnosis of HF and/or initiation of 
community prescription drug therapy with loop diuretics
!
Inpatient hospital admission with a diagnosis of HF and/or all-cause death
!
Composite of all-cause hospitalization or death
!
All cause hospitalization
!
All-cause death
!
Hospitalization for HF
For the above study outcomes, “inpatient hospital admission” in the Danish registries covers 
all types of hospital entry that lead to inpatient admission, for example; admission via 
emergency room entrance, admission by ambulance, self-referral, and referral from 
GP/primary health care provider. Major cardiovascular outcomes such as myocardial 
infarction or acute heart failure almost always lead to inpatient admission in the Danish 
health care system and these discharge diagnoses have documented high validity. The 
validity of diagnoses of apparently major cardiovascular events that do not lead to subsequent 
inpatient admission (for example, myocardial infarction coded during emergency room 
contact without admitting the patient to hospital) have considerably lower validity.

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Variable
Database
Codes
revascularization, hospital 
admission for HF
I200 OR nonfatal 
stroke: I61, I63, I64,
OR admission for 
HF:
I500, I501, I502, 
I503, I508, I509, 
I110, I130, I132, 
I420, I426, I427, 
I428, I429, 
OR  procedure code 
CABG:
KFNA-KFNE, 
KFNH20
OR Procedure code 
PCI:
KFNG, KFNF
OR All-cause death
ICD-10 codes for secondary outcomes
Variable
Database
Codes
Notes
All-cause inpatient hospital 
admission or emergency room 
visit
DNPR
Various 
diagnoses and 
procedures 
from all  acute 
hospital 
contacts
Hospital admission with HF
DNPR
Admission for 
HF:
I500, I501, 
I502, I503, 
I508, I509, 
I110, I130, 
I132, I420, 
I426, I427, 
I428, I429
All-cause inpatient hospital 
admission or all-cause death
DNPR, CPR
Various 
diagnoses and 
procedures 
from all  
inpatient 
hospital 
admissions

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Variable
Database
Codes
OR All-cause 
death
All-cause death
CPR
All-cause death
9.3.3
Covariates
For all patients with a first initiation of empagliflozin or GLP1-RA, we will ascertain data on 
a range of variables potentially associated with the outcomes of interest, including the 
following: 
Included in current analysis as potential confounders: Age, gender, year of inclusion, diabetes 
duration, number of diabetes drugs used, metformin use, insulin use, diagnoses of 
retinopathy, neuropathy, or nephropathy, estimated glomerular filtration rate (eGFR), history 
of ischemic heart disease, cerebrovascular disease, peripheral vascular disease, heart failure 
(further divided by duration and primary/secondary diagnosis), medical obesity, chronic 
obstructive pulmonary disease, cancer, use of angiotensin converting-enzyme inhibitors 
(ACE-I) or angiotensin II receptor blockers (ARBs), other antihypertensives, statins, 
antiplatelet drugs, social and frailty markers, marital status, prescriptions for mental 
disorders, alcoholism, and number of prior hospital admission days.
Table 2
Codes for other covariates: comorbidities and diabetes complications
Variable
Database
Codes
Notes
Ischemic heart 
disease 
DNPR
I20-I25, T822A, T823, KFNA, 
KFNB, KFNC, KFND, KFNE, 
KFNF, KFNG, KFNH, KFNW, 
KFLF
Ischemic heart disease 
diagnosis incl angina or 
coronary OP
Cerebrovascul
ar disease
DNPR
G45, I61, I63-I66, I672, I678-
I679, I691, I693-I698, G45, 
KAAL10, KAAL11
Atherosclerotic 
cerebrovascular disease 
incl 
thrombolysis/thrombecto
my, TCI, intracerebral 
hemorrhage
Peripheral 
vascular 
disease 
DNPR
I702, I742-I745, I739A, I739B, 
I739C, E105, E115, E125, E135, 
E145, KPBE+F+H+N+P+Q, 
KPBW, KPGH10, 
KPDE+F+H+N+P+Q, 
KPDW99, KPDW20, 
KPEE+F+H+N+P+Q+W, 
KPFE+H+N+P+Q+W, 
KPGH20+21+22+23+30+31+40
Atherosclerotic 
peripheral vascular 
disease incl vascular OP 
or amputation

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Variable
Database
Codes
Notes
+99, KPDU74+82+83+84, 
KPEU74+82+83+84, 
KPFU74+82+83+84, KNBQ, 
KNCQ, KNDQ, KNEQ, KNFQ,
KNGQ, KNHQ
Neuropathy
E104, E114, E144, G590, G632, 
G598, G603, G628, G629, 
G632, G638, G990
Retinopathy
DNPR
Diagnosis 
codes
+
procedure 
codes
E103, E113, E143, H340, H341, 
H342, H280, H334, H450, 
H360, H540, H541, H544, H25, 
H268, H269, H430, H431, 
H438C, H439, H334A, H330, 
H335, H470
KCKC10, KCKC15, KCKD65
Nephropathy
DNPR
Diagnosis 
codes
+
E102, E112, DE142, I120, 
N083, N06, N17, N18, N19, 
R809
BJFD2
  Creatinine 
(eGFR) 
LABKA
NPU18016, NPU01807, 
NPU04998, NPU17559, 
ASS00354, ASS00355, 
ASS00356 or analysis codes: 
110266, 111016, 1311235, 
1411235, 1511235, 1511236, 
1511237, 1610154, 1610296, 
1611807, 1710552, 1710301, 
1711807, 1811807, 1817156, 
1817428, 18016, 1155, 38927, 
4998, 716, 1807, 5224, 38926, 
38928 
Chronic 
pulmonary 
disease
DNPR
J40-J48, J60-J68, J684, J701, 
J703, DJ961, J982, J983
Cancer
DNPR
C00-C99
Medical 
obesity
DNPR
E65-E68
Alcoholism
DNPR
G312, G621, G721, I426, K292, 
K860, K70, R780, T51, Z714, 
Z721

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Variable
Database
Codes
Notes
Mental 
disorders
prescriptio
ns
N05A, N05BA, N05CD, 
N05CF, N06A
Antiplatelet 
drugs
prescriptio
ns
B01AC06, N02BA01, 
B01AC30, B01AC07, 
B01AC22, B01AC04, 
B01AC24, B01AC25
Statins
prescriptio
ns
C10AA, C10BA, C10BX, 
A10BH51
Any 
antihypertensi
ve drugs
prescriptio
ns
C02, C03A, C03B, C03X, C07, 
C08, C09
ACE 
inhibitors
prescriptio
ns
C09A, C09B
ARB
prescriptio
ns
C09C, C09D
Marital status
CRS
Current marital status (if 
no current status in CPR, 
last value carried 
forward)
Exhaustive list for lab value data sources and codes can be requested from the corresponding  author.
Table 3
Codes for all antihyperglycemic (glucose-lowering) drugs of interest
Diabetes drugs
ATC codes in database
Empagliflozin
A10BX12, A10BK03, A10BD19, A10BD20
Liraglutide
A10BX07, A10BJ02, A10AE56
SGLT2-inhibitor
A10BX09, A10BX11, A10BX12, A10BK, A10BD15, A10BD16, 
A10BD21, A10BD20, A10BD19, A10BD23, A10BD24, A10BD25
GLP1 receptor 
agonists
A10BX04, A10BX07, A10BX10, A10BX13, A10BX14, A10BJ, 
A10AE54, A10AE56
DPP4 inhibitors
A10BH, A10BD07, A10BD12, A10BD08, A10BD09, A10BD10, 
A10BD11, A10BD13, A10BD18, A10BD19, A10BD21, A10BD22, 
A10BD24, A10BD25
biguanides
A10BA, A10BD01, A10BD02, A10BD03, A10BD05, A10BD07, 
A10BD08, A10BD10, A10BD11, A10BD13, A10BD14, A10BD15, 
A10BD16, A10BD17, A10BD18, A10BD20, A10BD22, A10BD23, 
A10BD25
sulfonylureas
A10BB, A10BD04, A10BD02, A10BD06, A10BD01, A10BC01

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Diabetes drugs
ATC codes in database
glitazones
A10BG, A10BD03, A10BD04, A10BD05, A10BD06, A10BD09, 
A10BD12
alfa-glucosidase 
inhibitors
A10BF, A10BD17
Insulin and 
analogues
A10A
meglitinides
A10BX02, A10BX03, A10BX08, A10BD14

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9.4
DATA SOURCES
The Danish health care system provides universal coverage to all Danish residents (5.7 million 
inhabitants. Health care coverage includes visits to general practitioners and specialists, 
hospital admissions, and outpatient visits. The costs of medicines are partially covered by the 
Danish health system. 
The centralized Civil Registration System in Denmark allows for personal identification of 
each person in the entire Danish population and for the possibility of linkage to all Danish 
registers containing civil registration numbers, such as the registers mentioned below.
Data collected in these registers are available for research purposes after following a standard 
application procedure to the relevant data board. The process requires collaboration with a local 
university or investigator affiliated with a research institute to access the data; Danish Data 
Protection Agency approval to handle data; data release by the Danish National Data Board; 
and, for accessing medical charts, approval of a Patient Safety Board. All applications have to 
be submitted in Danish.
Denmark’s primary health care sector, which includes GPs, specialists, and dentists, generates 
about 96% of the prescription sales, most of which are reimbursable and are dispensed by 
community pharmacies. Each dispensing record contains information on the patient, drug, and 
prescriber. Dispensing records retain the patient’s universal personal identifier, allowing for 
individual-level linkage to all Danish registers and medical databases.
The study will draw on the following Danish population-based registries:
The Civil Registration System: Holds records of central personal registry (CPR)-number, 
address, marital status, emigration and immigration status, and date of death (if any) of the 
entire population of Denmark since 1968. This system can be used to link all Danish registries 
containing CPR-numbers (1).
The Danish National Patient Register: The Danish National Patient Register (DNPR) includes 
information of all hospitalized patients since 1977 and on outpatient hospital contacts since 
1995. The register contains information about the date of admission, discharge, diagnosis codes 
and surgical procedures. From 1977 to 1993 diagnosis codes were coded with reference to the 
ICD-8 classification and from 1994 onwards they have been coded according to ICD-10 (2). 
The National Database of Reimbursed Prescriptions: Contains complete information on all 
prescriptions dispensed at community pharmacies in the Danish regions since 1994. Records 
information about the drug user including civil registration number, age, gender, residence, 
ATC (Anatomical Therapeutic Chemical) code of the drug, package size, and date of 
dispensing (3).
The National Laboratory Database: Data from samples which involve laboratory analysis (e.g. 
blood samples) are compiled in this database. Danish regions were affiliated with the database 
from 2013. In addition, historical data from some regions have been incorporated.
Data on e.g. creatinine can be extracted from this registry (5).

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The National Health Insurance Service Registry: Contains data on all reimbursed primary care 
encounters and services, such as contacts and services by general practitioners (GP), privately 
practicing specialist physicians, psychologists, physiotherapists, dentists, podiatrists, etc.
The Danish Diagnosis-Related Group (DRG) and Danish Ambulatory Grouping System 
(DAGS): contains costs for all hospital contacts and procedures recorded in The Danish 
National Patient Register (see above); updated until 2018. 
9.5
STUDY SIZE
In general, the study size will be driven by the uptake of empagliflozin following approval and 
launch of empagliflozin for the treatment of T2D to improve glycaemic control in adults in 
Denmark in 2014. In 2019, according to www.medstat.dk there were 23,350 users of 
empagliflozin in Denmark, 
In 2019, there were 41,715 users of GLP-1 receptor agonists in Denmark (9). This may yield 
an estimated at least 50,000 GLP-1 RA users during 2014-2020 for comparison making 
statistical power a minor concern when including 2020 data in the final analysis. 
We thus estimate that at least 40,000 person-years of empagliflozin exposure and 60,000 
person-years of liraglutide exposure can be included in our study up to the end of 2020.
9.6
DATA MANAGEMENT
The 
 at 
 is a large academic 
department, with more than 15 years’ experience conducting data management and 
epidemiologic research based on Danish registry data. This includes several successfully 
fulfilled calls from the EMA, specifically on utilization and safety of antidiabetic agents 
using Danish registry data. The department has a cadre of 25 statisticians at Master or PhD 
level, one of whom will be assigned to this project for its duration.
Standard security processes at 
 will be in place to ensure the safety of all 
systems and data. Every effort will be made to ensure that data are kept secure so that they 
cannot be accessed by anyone except select study staff.
All conversion of the original data to analysis variables will be performed using SAS 
software version 9.4 (SAS Institute, Inc., Cary, North Carolina).
9.7
DATA ANALYSIS
We will provide two approaches in our study across the two exposure groups: an on-treatment 
(OT) exposure definition, and an intention-to-treat (ITT) exposure definition (see 
section 9.1 for details).
Decisions to start a specific glucose-lowering drug are influenced by demographic, medical, 
and clinical factors, and those same factors might be associated with the outcomes of interest. 
For balanced comparison of the two treatment groups, we plan to conduct propensity score 
(PS) balancing of potential confounders (see section 9.3, covariates) across the two treatment 
groups. Covariate balance will be assessed by checking standardized differences (SD) between 
the groups; a covariate being considered well balanced if the SD is below 0.1.

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The propensity score is the predicted probability of being assigned to a particular treatment 
conditional on a set of observed covariates. Because a propensity score model predicts not the 
probability of experiencing the (relatively rare) outcome but the probability of the (frequent) 
exposure i.e. being treated with empagliflozin or GLP1-RA in this study, more of our potential 
confounding covariates may be used in the model than in a conventional multivariable 
regression model. As recently discussed (Kahlert et al: Control of confounding in the analysis 
phase. Clin Epidemiol 2017), in the majority of studies that have used both multivariable 
analysis and propensity score methods, there were no important differences in the results. 
Propensity score methods may be more robust in situations with rare outcomes and common 
exposures than traditional multivariable analysis, as expected in our proposed study. However, 
just as with multivariable analysis, propensity score methods do not protect against unknown, 
unmeasured and residual confounding when comparing GLP1-RA and empagliflozin initiators.
Moreover, propensity score methods may not in some settings estimate treatment effects in the 
entire population of real-world treated individuals but in a trimmed subset of the data, limiting 
sample size and in some cases hampering the feasibility and interpretability of the results 
obtained by the propensity score method. Therefore, our approach will be to examine and learn 
about the data available in our dataset, apply stratified analyses and investigate available 
confounders and sample size, and then seek to apply the methods. 
Given that 1) We aim to measure the average treatment effect at the population level; 2) We 
wanted to avoid excluding patients, to reduce the risk of a non-representative sample; and 3) 
The number of patients in our two treatment groups will likely differ little, the Inverse 
Probability Treatment Weighting approach (IPTW) may be a feasible approach
Cumulative incidence function curves adjusted for competing risk will be constructed to depict 
the cumulative incidence over time of each of the outcomes under study, comparing 
empagliflozin and GLP1-RA initiators. 
We will use Cox regression analyses to compute crude and adjusted hazard ratios (HRs) with 
95% CIs to examine the association between empagliflozin versus GLP1-RA initiation and 
study outcomes. For each of the primary outcomes (primary objective) and secondary outcomes 
(secondary objective) of interest, estimation of adjusted use HRs with 95% CIs will be 
considered the main analysis of interest. 
The selection of variables to be included in the Cox regression model will be based on evidence 
from previous literature, covariate data availability, examination of exposure group differences 
in the distribution of each covariate, and the association of covariates with the outcomes of 
interest. The current list of potential confounders for the Cox regression model is included in 
section 9.3. The variable list may be subject to changes in which case these will be included in 
an amendment process and will be reflected in the SAP.
Stratified analyses
A number of stratified analyses will be performed to assess effect measure modification and 
possible residual confounding.

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approach (i.e., carrying forward the initial exposure status and disregarding changes in 
treatment status over time) is not affected by informative censoring bias in the same way, but 
may on the other hand be biased through exposure misclassification that increases with 
longer follow-up periods and is open to potential differential loss to follow-up (27). We will 
therefore consider results from both analyses carefully in evaluating the clinical effects of 
empagliflozin and GLP1-RA, in light of the strengths and limitations inherent in each 
approach.

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10.
PROTECTION OF HUMAN SUBJECTS
According to Danish law, individual informed consent, or permission from ethical committee, 
is not required for observational registry-based studies without patient contact. The project 
has been approved by the Danish Data Protection Agency (Record number 2014-54-0922 
KEA-2015-4).

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11.
MANAGEMENT AND REPORTING OF ADVERSE 
EVENTS/ADVERSE REACTIONS
Not applicable based on secondary use of data without any potential that any employee of BI 
or agent working on behalf of BI access individually identifiable patient data.

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12.
PLANS FOR DISSEMINATING AND COMMUNICATING 
STUDY RESULTS
The 
 reserves the right to submit the results from any of 
the study analyses for publication and commits that at least the final results will be published. 
Any publications will follow guidelines, including those for authorship, established by the 
International Committee of Medical Journal Editors. When reporting results of this study, the 
appropriate STROBE (Strengthening the Reporting of Observational Studies in 
Epidemiology) checklist will be followed.

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13.
REFERENCES
13.1
PUBLISHED REFERENCES
1. 
Pedersen CB. The Danish Civil Registration System. Scand J Public Health [Internet]. 
2011;39(7_suppl):22–5. Available from: 
http://journals.sagepub.com/doi/10.1177/1403494810387965
2. 
Leegaard A, Riis A, Kornum JB, Prahl JB, Thomsen V, Sørensen HT, et al. Diabetes, 
glycemic control, and risk of tuberculosis: A population-based case-control study. Diabetes 
Care. 2011;34(12):2530–5. 
3. 
Johannesdottir SA, Horváth-Puhó E, Ehrenstein V, Schmidt M, Pedersen L, Sørensen HT. 
Existing data sources for clinical epidemiology: The Danish National database of reimbursed 
prescriptions. Clin Epidemiol. 2012;4(1):303–13. 
4. 
Ehrenstein V, Antonsen S, Pedersen L. Existing data sources for clinical epidemiology: 
Aarhus University Prescription Database. Clin Epidemiol. 2010;2(1):273–9. 
5. 
Anon. 2020. Documentation of The National Laboratory Database. 
https://sundhedsdatastyrelsen.dk/da/registre-og-services/om-de-nationale-
sundhedsregistre/doedsaarsager-og-biologisk-materiale/laboratoriedatabasen. In Danish
6. 
Marso SP, Daniels GH, Brown-Frandsen K, Kristensen P, Mann JFE, Nauck MA, et al. 
Liraglutide and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med [Internet]. 
2016;375(4):311–22. Available from: http://www.nejm.org/doi/10.1056/NEJMoa1603827
7. 
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; 373: 2117-28.
8. 
Pottegård A, Bjerregaard BK, Larsen MD, Larsen KS, Hallas J, Knop FK, et al. Use of 
exenatide and liraglutide in Denmark: A drug utilization study. Eur J Clin Pharmacol. 
2014;70(2):205–14. 
9. 
Sundhedsdatastyrelsen. “Medstat.dk.” 
10. 
Birkeland KI, Jørgensen ME, Carstensen B, Persson F, Gulseth HL, Thuresson M, et al. 
Cardiovascular mortality and morbidity in patients with type 2 diabetes following initiation of 
sodium-glucose co-transporter-2 inhibitors versus other glucose-lowering drugs (CVD-REAL 
Nordic): a multinational observational analysis. Lancet Diabetes Endocrinol. 2017;5(9):709–
17. 
11. 
Thomsen RW, Baggesen LM, Søgaard M, Pedersen L, Nørrelund H, Buhl ES, et al. Early 
glycaemic control in metformin users receiving their first add-on therapy: a population-based 
study of 4,734 people with type 2 diabetes. Diabetologia. 2015;58(10):2247–53. 
12. 
Mor A, Dekkers OM, Nielsen JS, Beck-Nielsen H, Sørensen HT, Thomsen RW. Impact of 
Glycemic Control on Risk of Infections in Patients with Type 2 Diabetes: A Population-Based 
Cohort Study. Am J Epidemiol. 2017;186(2):227–36. 

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13. 
Horsdal HT, Johnsen SP, Søndergaard F, Rungby J. Type of preadmission glucose-lowering 
treatment and prognosis among patients hospitalised with myocardial infarction: A 
nationwide follow-up study. Diabetologia. 2008;51(4):567–74. 
14. 
M.a S, S.A.J.a S, J.L.b S, V.a E, L.a P, H.T.a S. The Danish National patient registry: A 
review of content, data quality, and research potential. Clin Epidemiol [Internet]. 2015;7:449–
90. Available from: http://www.scopus.com/inward/record.url?eid=2-s2.0-
84947945481&partnerID=40&md5=b3064ef56eb42aeaddf3d6d3f466c733
15. 
Kristensen JK, B DT, Carstensen B, Marianne S-J, Green A. Validering af metoder til 
identifikation af erkendt diabetes på basis af administrative sundhedsregistre. Ugeskr læger. 
2007;(April):1687–92. 
16. 
Pottegård A, Schmidt SAJ, Wallach-Kildemoes H, Sørensen HT, Hallas J, Schmidt M. Data 
resource profile: The Danish national prescription registry. Int J Epidemiol. 2017;46(3):798–
798f. 
17. 
Christensen DH, Rungby J, Thomsen RW. Nationwide trends in glucose-lowering drug use, 
Denmark, 1999-2014. Clin Epidemiol. 2016;8:381–7. 
18. 
Thomsen RW, Nicolaisen SK, Hasvold P, Sanchez RG, Pedersen L, Adelborg K, et al. 
Elevated potassium levels in patients with chronic kidney disease: occurrence, risk factors and 
clinical outcomes—a Danish population-based cohort study. Nephrol Dial Transplant 
[Internet]. 2017;1(April):1–10. Available from: http://academic.oup.com/ndt/advance-
article/doi/10.1093/ndt/gfx312/4644812
19. 
Carstensen B, Kristensen JK, Ottosen P, Register ND. The Danish National Diabetes 
Register: trends in incidence, prevalence and mortality. 2008;2187–96. 
20. 
Rydén L, Grant PJ, Anker SD, Berne C, Cosentino F, Danchin N, et al. ESC guidelines on 
diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. 
Eur Heart J. 2013;34(39):3035–87. 
21. 
Gribsholt SB, Pedersen L, Dekkers O, Thomsen W. Body Mass Index of 92 , 027 patients 
acutely admitted to general hospitals in Denmark : Associated clinical characteristics and 30-
day mortality. PLoS One. 2018;1–16. 
22. 
Svensson E, Baggesen LM, Johnsen SP, Pedersen L, Nørrelund H, Buhl ES, et al. Early 
Glycemic Control and Magnitude of HbA 1c Reduction Predict Cardiovascular Events and 
Mortality: Population-Based Cohort Study of 24,752 Metformin Initiators. Diabetes Care 
[Internet]. 2017;40(June):dc162271. Available from: 
http://care.diabetesjournals.org/lookup/doi/10.2337/dc16-2271
23. 
Thomsen RW, L.M. B, E S, L. P, Nørrelund H, E.S.Buhl, et al. Early glycaemic control 
among patients with type 2 diabetes and initial glucose-lowering treatment: a 13-year
population-based cohort study. Diabetes, Obes Metab. 2015;771–80. 
24. 
Thomsen RW, Nicolaisen SK, Hasvold P, Sanchez RG, Pedersen L, Adelborg K, et al. 
Elevated potassium levels in patients with chronic kidney disease: occurrence, risk factors and 
clinical outcomes—a Danish population-based cohort study. Nephrol Dial Transplant 

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companies
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[Internet]. 2017;1(January):1–10. Available from: http://academic.oup.com/ndt/advance-
article/doi/10.1093/ndt/gfx312/4644812
25. 
Svensson E, Nielsen RB, Hasvold P, Aarskog P, Thomsen RW. Statin prescription patterns, 
adherence, and attainment of cholesterol treatment goals in routine clinical care: A Danish 
population-based study. Clin Epidemiol. 2015;7:213–23. 
26. 
Suissa S. Lower Risk of Death With SGLT2 Inhibitors in Observational Studies: Real or 
Bias? Diabetes Care [Internet]. 2018;41(1):6–10. Available from: 
http://care.diabetesjournals.org/lookup/doi/10.2337/dc17-1223
27. 
Patorno E, Patrick AR, Garry EM, Schneeweiss S, Gillet VG, Bartels DB, et al. Observational 
studies of the association between glucose-lowering medications and cardiovascular 
outcomes: addressing methodological limitations. Diabetologia. 2014;57(11):2237–50. 
28. 
Mor A, Petersen I, SØrensen HT, Thomsen RW. Metformin and other glucose-lowering drug 
initiation and rates of community-based antibiotic use and hospital-treated infections in 
patients with type 2 diabetes: A Danish nationwide population-based cohort study. BMJ 
Open. 2016;6(8). 
29. 
Christiansen C, Johansen M, Christensen S, O’Brien JM, Tønnesen E, Sørensen H. 
Preadmission metformin use and mortality among intensive care patients with diabetes: a 
cohort study. Crit Care [Internet]. 2013;17(5):R192. Available from: 
http://ccforum.biomedcentral.com/articles/10.1186/cc12886

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ANNEX 1. LIST OF STAND-ALONE DOCUMENTS
None

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Study reference number:
http://website.encepp.eu/encepp/viewResource.htm?id=37726
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 Study progress report(s)
1.1.4 Interim progress report(s)
6
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: 
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)
9.2.1
2.1.4 Which hypothesis(-es) is (are) to be tested?
2.1.5 If applicable, that there is no a priori hypothesis?
Comments:
__________________________
1 Date from wh ch informat on on the first study is first recorded in the study data set or, in the case of secondary use of data, the date from wh ch 
data extract on starts
2 Date from which the analytical data set is completely available

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Section 3: Study design
Yes
No
N/A
Section 
Number
3.1
Is the study design described? (e.g. cohort, case-
control, cross-sectional, new or alternative 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. incidence rate, absolute risk)
9.1
3.4
Does the protocol specify measure(s) of association? 
(e.g. relative risk, odds ratio, excess risk, incidence 
rate ratio, hazard ratio, number needed to harm (NNH) 
per year)
9.1
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)
11
Comments:
Section 4: Source and study populations
Yes
No
N/A
Section 
Number
4.1
Is the source population described?
9.2.1
4.2
Is the planned study population defined in terms of:
4.2.1 Study time period?
9.2.2
4.2.2 Age and sex?
9.2.1
4.2.3 Country of origin?
9.2.1
4.2.4 Disease/indication?
9.2.1
4.2.5 Duration of follow-up?
9.2.8
4.3
Does the protocol define how the study population 
will be sampled from the source population? 
(e.g. event or inclusion/exclusion criteria)
9.2.6, 9.2.7
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)
9.3.1

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Section 5: Exposure definition and measurement
Yes
No
N/A
Section 
Number
5.3
Is exposure classified according to time windows? 
(e.g. current user, former user, non-use)
9.3.1
5.4
Is exposure classified based on biological mechanism 
of action and taking into account the pharmacokinetics 
and pharmacodynamics of the drug?
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
6.2
Does the protocol describe how the outcomes are 
defined and measured? 
9.3.2
6.3
Does the protocol address the validity of outcome 
measurement? (e.g. precision, accuracy, sensitivity, 
specificity, positive predictive value, prospective or 
retrospective ascertainment, use of validation sub-
study)
9.3.2
6.4
Does the protocol describe specific endpoints relevant 
for Health Technology Assessment? (e.g. HRQoL, 
QALYs, DALYS, health care services utilisation, 
burden of disease, disease management)
Comments:
Section 7: Bias
Yes
No
N/A
Section 
Number
7.1
Does the protocol describe how confounding will be 
addressed in the study?
9.9
7.1.1. Does the protocol address confounding by 
indication if applicable?
9.9
7.2
Does the protocol address:
7.2.1. Selection biases (e.g. healthy user bias)
9.9
7.2.2. Information biases (e.g. misclassification of 
exposure and endpoints, time-related bias)
9.9
7.3
Does the protocol address the validity of the study 
covariates?
9.3.3
Comments:

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Section 8: Effect modification
Yes
No
N/A
Section 
Number
8.1
Does the protocol address effect modifiers? 
(e.g. collection of data on known effect modifiers, 
subgroup analyses, anticipated direction of effect) 
9.9
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
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
9.1.3 Covariates?
9.4
9.2
Does the protocol describe the information available 
from the data source(s) on:
9.2.1 Exposure? (e.g. date of dispensing, drug 
quantity, dose, number of days of supply 
prescription, daily dosage, prescriber)
9.4
9.2.2 Outcomes? (e.g. date of occurrence, multiple 
event, severity measures related to event)
9.4
9.2.3 Covariates? (e.g. age, sex, clinical and drug use 
history, comorbidity, comedications, lifestyle)
9.4
9.3
Is a coding system described for: 
9.3.1 Exposure? (e.g. WHO Drug Dictionary, 
Anatomical Therapeutic Chemical (ATC) 
Classification System)
9.4
9.3.2 Outcomes? (e.g. International Classification of 
Diseases (ICD)-10, Medical Dictionary for 
Regulatory Activities (MedDRA))
9.4
9.3.3 Covariates?
9.4
9.4
Is a linkage method between data sources described? 
(e.g. based on a unique identifier or other) 
9.4
Comments:

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Section 10: Analysis plan
Yes
No
N/A
Section 
Number
10.1
Is the choice of statistical techniques described? 
9.7
10.2
Are descriptive analyses included?
10.3
Are stratified analyses included?
9.7
10.4
Does the plan describe methods for adjusting for 
confounding?
9.7, 9.9
10.5
Does the plan describe methods for handling missing 
data?
10.6
Is sample size and/or statistical power estimated?
9.5
Comments:
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)
9.8
11.2
Are methods of quality assurance described?
9.8
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?
9.9
12.1.2 Information bias?
9.9
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)
9.9
12.2
Does the protocol discuss study feasibility? (e.g. study 
size, anticipated exposure, duration of follow-up in a 
cohort study, patient recruitment)
Comments:

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Section 13: Ethical 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?
13.3
Have data protection requirements been described?
10
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
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)? 
12
15.2
Are plans described for disseminating study results 
externally, including publication?
12
Comments:
Name of the main author of the protocol:
Date: 
22 Oct 2020
Signature: 

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ANNEX 3. ADDITIONAL INFORMATION
Not applicable