Post-authorisation Safety Study in Patients With Type 2 Diabetes Mellitus to Assess the Risk of Acute Liver Injury, Acute Kidney Injury and Chronic Kidney Disease, Severe Complications of Urinary Tract Infection, Genital Infections, and Diabetic Ketoacidosis Among Patients Treated With Empagliflozin Compared to Patients Treated With DPP-4 Inhibitors
Conditions: Diabetes Mellitus, Type 2
Sponsor: Boehringer Ingelheim

ABCD
Protocol for observational studies based on existing data
TITLE PAGE
Document Number:
c03270726-08
BI Study Number:
1245.96
BI Investigational
Product(s):
Jardiance® (empagliflozin)
Synjardy® (empagliflozin/metformin)
Title:
Post-authorisation safety study in patients with type 2 diabetes mellitus to 
assess the risk of acute liver injury, acute kidney injury and chronic 
kidney disease, severe complications of urinary tract infection, genital 
infections, and diabetic ketoacidosis among patients treated with 
empagliflozin compared to patients treated with DPP-4 inhibitors
Brief lay title:
Post-authorisation safety study in patients with type 2 diabetes to assess 
the risk of liver injury, kidney injury, urinary tract and genital infections, 
and diabetic ketoacidosis in patients treated with empagliflozin, 
compared to DPP-4 inhibitors
Protocol version 
identifier:
8.0
Date of last version of 
protocol:
13 Jun 2019 (version 7.0)
PASS:
Yes
EU PAS Register 
number:
ENCEPP/SDPP/13413; 
http://www.encepp.eu/encepp/viewResource.htm?id=13414
Active substance:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Medicinal product:
Jardiance
Synjardy
Product reference:
EMEA/H/C/002677
EMEA/H/C/003770
Procedure number:
EMEA/H/C/002677/MEA
EMEA/H/C/003770/MEA
Joint PASS:
No

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Research question and 
objectives:
To estimate, among patients with type 2 diabetes mellitus (T2D), the risk 
of acute liver injury (ALI), the risk of acute kidney injury (AKI) and 
chronic kidney disease (CKD), the risk of severe complications of urinary 
tract infection (UTI), the risk of genital infections (GI), and the risk of 
diabetic ketoacidosis (DKA) among patients treated with empagliflozin 
compared with patients treated with dipeptidyl peptidase-4 (DPP-4) 
inhibitors
Country(-ies) of study:
United Kingdom, Denmark, United States
Authors:
and 
Marketing authorisation 
holder(s):
MAH contact person:
EU-QPPV:
Signature of EU-QPPV:
The signature of the EU-QPPV is provided electronically
Date:
19 July 2021 (version 8.0)
Page 1 of 148
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© 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 observational studies based on existing data
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c03270726-08
Proprietary confidential information © 2021 Boehringer Ingelheim International GmbH or one or more of its affiliated companies
1.
TABLE OF CONTENTS
TITLE PAGE.............................................................................................................................1
1.
TABLE OF CONTENTS...................................................................................................3
2.
LIST OF ABBREVIATIONS............................................................................................7
3.
RESPONSIBLE PARTIES..............................................................................................10
4.
ABSTRACT.....................................................................................................................11
5.
AMENDMENTS AND UPDATES.................................................................................18
6.
MILESTONES.................................................................................................................26
7.
RATIONALE AND BACKGROUND............................................................................27
7.1
DATA ON THE OUTCOMES OF INTEREST IN EMPAGLIFLOZIN 
CLINICAL TRIALS AND SAFETY STUDIES.................................................................29
7.2
EPIDEMIOLOGY OF ACUTE LIVER INJURY ........................................30
7.2.1
Epidemiology of acute liver injury in general population.............................30
7.2.2
Epidemiology of acute liver injury in the diabetes population .....................31
7.3
EPIDEMIOLOGY OF ACUTE KIDNEY INJURY.....................................32
7.3.1
Epidemiology of acute kidney injury in general population.........................32
7.3.2
Epidemiology of acute kidney injury in the diabetes population..................32
7.4
EPIDEMIOLOGY OF CHRONIC KIDNEY DISEASE..............................33
7.5
EPIDEMIOLOGY OF SEVERE COMPLICATIONS OF URINARY 
TRACT INFECTION ..........................................................................................................33
7.5.1
Epidemiology of severe UTI in general population......................................34
7.5.2
Epidemiology of severe UTI in the diabetes population...............................34
7.5.3
Epidemiology of sepsis in general population and in diabetes patients........35
7.6
EPIDEMIOLOGY OF GENITAL INFECTIONS........................................35
7.7
EPIDEMIOLOGY OF DIABETIC KETOACIDOSIS.................................37
7.8
EPIDEMIOLOGY OF DIABETES AND ANTIDIABETIC TREATMENT 
PATTERNS .......................................................................................................................38
8.
RESEARCH QUESTION AND OBJECTIVES .............................................................40
9.
RESEARCH METHODS ................................................................................................41
9.1
STUDY DESIGN..........................................................................................41
9.2
SETTING ......................................................................................................42
9.2.1
Study population............................................................................................42
9.2.2
Study period ..................................................................................................43
9.2.3
New user definition .......................................................................................43

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9.2.4
Index prescription definition .........................................................................43
9.2.5
Index date ......................................................................................................43
9.2.6
Baseline and lookback period........................................................................43
9.2.7
Inclusion criteria............................................................................................44
9.2.8
Exclusion criteria...........................................................................................45
9.2.8.1
Exclusion criteria by outcome of interest ....................................................45
9.2.9
Follow-up of subjects....................................................................................46
9.3
VARIABLES.................................................................................................47
9.3.1
Exposures ......................................................................................................47
9.3.1.1
Exposure and time at risk.............................................................................48
9.3.2
Study outcomes .............................................................................................51
9.3.2.1
ALI: Hospitalisation, emergency department (ED) visit, or specialist visit 
for ALI in patients with no predisposing conditions, primary outcome......................51
9.3.2.2
ALI: Hospitalisation, ED visit, or specialist visit for ALI in patients with or 
without predisposing conditions, secondary outcome .................................................53
9.3.2.3
Hospitalisation, ED visit, or specialist visit for AKI, primary outcome......53
9.3.2.4
Chronic kidney disease (inpatient and outpatient), secondary outcome......55
9.3.2.5
Severe complications of UTI (inpatient and outpatient pyelonephritis and 
urosepsis), primary outcome........................................................................................56
9.3.2.6
Genital infections (inpatient and outpatient), primary outcome..................58
9.3.2.7
Severe genital infections: secondary outcome.............................................61
9.3.2.8
Hospitalisation or ED visit for DKA: primary outcome..............................61
9.3.2.9
Case validation process................................................................................63
9.3.3
Covariates......................................................................................................63
9.3.3.1
Description of cases of elevated liver enzymes ...........................................64
9.4
DATA SOURCES.........................................................................................65
9.4.1
Clinical Practice Research Datalink (CPRD)–UK........................................65
9.4.2
The Danish Population Registries.................................................................68
9.4.3
HIRD, US......................................................................................................70
9.5
STUDY SIZE ................................................................................................73
9.6
DATA MANAGEMENT..............................................................................76
9.7
DATA ANALYSIS .......................................................................................76
9.7.1
Propensity score approach.............................................................................76
9.7.2
Primary and secondary objectives: estimate adjusted incidence rate ratios and 
compare adjusted incidence rates for each of the study outcomes ..................................78

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9.7.2.1
Main analysis ...............................................................................................78
9.7.2.2
Secondary outcome analyses .......................................................................79
9.7.3
Duration, dose, and recent use effects analysis.............................................79
9.7.4
Interim reports to monitor accrual of empagliflozin users and the event rates 
of acute liver injury and acute kidney injury ...................................................................80
9.7.5
Imputation of missing values ........................................................................80
9.7.6
Sensitivity analyses .......................................................................................81
9.8
QUALITY CONTROL .................................................................................82
9.9
LIMITATIONS OF THE RESEARCH METHODS....................................83
9.9.1
Confounding..................................................................................................83
9.9.2
Other biases...................................................................................................84
9.9.3
Strengths and limitations concerning each study database ...........................85
9.9.3.1
CPRD, UK ...................................................................................................85
9.9.3.2
Danish Population Registries.......................................................................86
9.9.3.3
HIRD, US.....................................................................................................87
9.9.4
Limitations due to the new-user design definition........................................87
9.9.5
Limitation due to study size ..........................................................................88
9.9.6
Generalisability .............................................................................................88
10.
PROTECTION OF HUMAN SUBJECTS ..................................................................89
10.1
RTI INTERNATIONAL...............................................................................89
10.2
CPRD.............................................................................................................89
10.3
THE DANISH POPULATION REGISTRIES .............................................90
10.4
HIRD .............................................................................................................90
10.5
OTHER GOOD RESEARCH PRACTICE...................................................91
11.
MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS...........................................................................................................................91
12.
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS .92
13.
REFERENCES ............................................................................................................93
13.1
PUBLISHED REFERENCES.......................................................................93
13.2
UNPUBLISHED REFERENCES...............................................................109
ANNEX 1.
LIST OF STAND-ALONE DOCUMENTS ...............................................110
ANNEX 2.
ENCEPP CHECKLIST FOR STUDY PROTOCOLS................................111
ANNEX 3.
CODES TO BE USED FOR EXCLUSION CRITERIA............................118

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ANNEX 4.
CODES TO DEFINE STUDY OUTCOMES.............................................122
ANNEX 5.
COVARIATES TO BE CONSIDERED FOR INCLUSION IN THE 
PROPENSITY SCORE MODEL, BY OUTCOME..............................................................141
ANNEX 6.
OVERVIEW OF CHARACTERISTICS OF THE DATA SOURCES......147

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2.
LIST OF ABBREVIATIONS
ADQI
Acute Dialysis Quality Initiative
AKI
Acute Kidney Injury
ALI
Acute Liver Injury
ALP
Alkaline Phosphatase
ALT
Alanine Aminotransferase
AST
Aspartate Transaminase
ATC
Anatomical Therapeutic Chemical
BI
Boehringer Ingelheim International GmbH
BMI
Body Mass Index
CI
Confidence Interval
CKD
Chronic Kidney Disease
CKD-EPI 
CKD Epidemiology Collaboration
CPR
Central Personal Registration (number), Denmark
CPRD
Clinical Practice Research Datalink
CPRD Aurum
Database of De-Identified Coded Primary Care Records for Use in Public 
Health Research (of the CPRD) 
CPRD GOLD
General Practitioner Online Database (of the CPRD)
CPT
Current Procedural Terminology (codes)
DKA
Diabetic Ketoacidosis
DPP-4 
Dipeptidyl Peptidase-4
ED
Emergency Department
eGFR
Estimated Glomerular Filtration Rate
EMA
European Medicines Agency
ENCePP
European Network of Centres for Pharmacoepidemiology and 
Pharmacovigilance
FDA
United States Food and Drug Administration
GI
Genital Infection
GLDs
Glucose-Lowering Drugs
GLP-1
Glucagon-Like Peptide-1
GP
General Practitioner

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HCPCS
Healthcare Common Procedure Coding System
HES
Hospital Episode Statistics
ICD-10
International Statistical Classification of Diseases and Related Health 
Problems, 10th Revision
ICD-9
International Classification of Diseases, 9th Revision
ICD-9-CM
International Classification of Diseases, 9th Revision, Clinical Modification
IRB
Institutional Review Board
IRR
Incidence Rate Ratio
ISAC
Independent Scientific Advisory Committee
MedDRA
Medical Dictionary for Drug Regulatory Activities
OQA
Office of Quality Assurance (RTI Health Solutions)
PaCO2
Partial Pressure of Carbon Dioxide
PASS
Post-Authorisation Safety Study
PPV
Positive Predictive Value
RR
Relative Risk
RTI-HS
RTI Health Solutions
SGLT2
Sodium-Glucose Cotransporter 2
SIRS
Systemic Inflammatory Response Syndrome
STD
Sexually Transmitted Disease
STROBE
Strengthening the Reporting of Observational Studies in Epidemiology
T1D
Type 1 Diabetes Mellitus
T2D
Type 2 Diabetes Mellitus
THIN
The Health Improvement Network
UK
United Kingdom
UKPDS
UK Prospective Diabetes Study
ULN
Upper Limit of the Normal Range
US
United States

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UTI
Urinary Tract Infection

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3.
RESPONSIBLE PARTIES
The responsible parties, study investigators, and protocol authors are as follows:

RTI Health Solutions (RTI-HS): coauthors of the protocol, study investigators
responsible for the study in the Clinical Practice Research Datalink (CPRD) database
in the United Kingdom (UK), and study coordinator



through September 2020



coauthors of the protocol and study investigators in the Danish Population Registries





through December 2019

, through December 2019

, through December 2019

 in the United States (US): coauthor of the protocol and study
investigators in the 
 Integrated Research DatabaseSM (HIRD)

, through November 2019

through October 2020



Boehringer Ingelheim International GmbH (BI): coauthors of the protocol and
sponsors of the study

of Global Epidemiology Team
Metabolism, through April 2020

Product
 Team
Metabolism

, Team
Metabolism
The study investigators share responsibility with BI for the design of the study. The 
investigators are responsible for conducting the study in a manner that meets regulatory 
standards, conducting analyses, and preparing scientific reports. The study shall be conducted 
as described in the approved protocol. The authors will not develop or implement any 
deviation or change to the protocol without prior review by BI.
The financial sponsor of this study is BI. The sponsor is responsible to assure study progress. 
BI is also responsible for communicating with the European Medicines Agency (EMA) about
the study protocol, the progress of the study, and study results.

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4.
ABSTRACT
Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
Title of study:
Post-authorisation safety study in patients with type 2 diabetes mellitus to 
assess the risk of acute liver injury, acute kidney injury and chronic kidney 
disease, severe complications of urinary tract infection, genital infections, and 
diabetic ketoacidosis among patients treated with empagliflozin compared to 
patients treated with DPP-4 inhibitors
Rationale and 
background:
As part of the risk management plan, Boehringer Ingelheim International 
GmbH (BI) has committed to perform a post-authorisation safety study 
(PASS) to evaluate the liver and renal safety of empagliflozin. The study will 
also evaluate the risks of severe complications of urinary tract infection (UTI)
and genital infections (GI).
Diabetic ketoacidosis (DKA) was included in the protocol amendment 
(version 4.0) as an additional safety topic in line with BI’s commitment within 
the Article 20 referral, started by the European Medicines Agency (EMA) in 
June 2015.
Two data sources and an extension of the study period to meet the required 
sample size to fulfil the study objectives were added in protocol amendment 
(version 5.0). This protocol also proposed refinements to the study design to 
ensure that the analysis will be adequate to address the different data sources 
and the complexity of a multinational database study. Among these 
refinements was a streamlining of the comparisons to a single comparator 
group. Version 6.0 clarified some of the changes proposed in version 5.0, to 
keep severe GI as a secondary endpoint and to report the number of patients 
with elevated liver enzymes. Version, 7.0, further clarifies some aspects of the 
data analysis. The current version, 8.0, adjusts the study milestones that have
been affected by the COVID-19 pandemic, leading to a delay in the reception
of data for the full study period in Denmark and in the start of validation
activities in the UK CPRD.
Research 
question and 
objectives:
To estimate, among patients with type 2 diabetes mellitus (T2D), the risk of 
acute liver injury (ALI), the risk of acute kidney injury (AKI) and chronic
kidney disease (CKD), the risk of severe complications of UTI, the risk of GI, 
and the risk of DKA among patients treated with empagliflozin compared with 
patients treated with dipeptidyl peptidase-4 (DPP-4) inhibitors.

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Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
Study design:
This will be a non-interventional cohort study using existing data (records 
from routine medical care). The study will use a new-user design and compare 
new users of empagliflozin with new users of DPP-4 inhibitors. Propensity 
scores based on information before or at the index date will be used to account 
for potential confounding. The index date will be defined as the date on which 
each identified new user receives the index prescription for empagliflozin or a 
DPP-4 inhibitor.
Population:
The study population will include all eligible patients with T2D initiating 
treatment with empagliflozin or with a DPP-4 inhibitor. Eligible patients will 
be included if they are aged 18 or more years and have at least 12 months of 
continuous registration in the data source. The data sources included in the 
study will be the Clinical Practice Research Datalink (CPRD) in the United 
Kingdom (UK). For the evaluation of the rarest outcomes, the Danish 
and the 
 Integrated Research 
DatabaseSM (HIRD) in the United States (US) will be added.
Each member of the empagliflozin-exposed population must have at
least one prescription/dispensing for empagliflozin, with or without 
other glucose-lowering drugs (GLDs), and no prior 
prescription/dispensing of empagliflozin, other SGLT2 inhibitors, or 
DPP-4 inhibitors during the 12 months before or at the index date.
Each member of the population exposed to a DPP-4 inhibitor must have
at least one prescription/dispensing for a DPP-4 inhibitor, with or 
without other GLDs, and no prior prescription/dispensing of a DPP-4
inhibitor, empagliflozin, or other SGLT2 inhibitor during the 
12 months before or at the index date.
New users of the study drugs would usually be (1) switching from 
monotherapy with another GLD to monotherapy with a study drug, (2)
switching from dual or triple therapy with another GLD to dual or triple 
therapy with a study drug and other GLDs, (3) adding a study drug to therapy 
with one or two other GLDs to become patients on dual or triple therapy or (4) 
naive to GLD treatment and start the study drugs as first-line therapy.
Treatment complexity will be considered in the analysis. Prior or current use 
of insulin is allowed, and an additional stratified analysis by insulin use is 
planned.
Only patients with T2D will be included in the study. Patients with type 1

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BI Study Number 1245.96
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Proprietary confidential information © 2021 Boehringer Ingelheim International GmbH or one or more of its affiliated companies
Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
diabetes (T1D) will be excluded. Algorithms to identify T2D and T1D will be 
adapted to the type and availability of data in each data source. Different 
exclusion criteria will be applied according to each of the outcomes of interest
(e.g., patients with CKD will be excluded from the analysis of AKI), which 
will result in different cohorts (see Section 9.2.8.1).
Follow-up will start the day after the index date and, for each specified 
outcome, will continue until the occurrence of the study outcome, end of study 
data, the date during follow-up that specific exclusion criteria are met, the end 
date of the first continuous treatment of the index drug (empagliflozin or 
DPP-4 inhibitor) plus a defined grace period (30 days after the end of the last 
prescription’s days’ supply in main analyses), or the date on which a new 
treatment episode starts with the other index drugs or other SGLT2 inhibitors.
Variables:
Primary outcomes:

Hospitalisation, emergency department (ED) visit, or specialist visit for
ALI in patients without predisposing conditions

Hospitalisation, ED visit, or specialist visit for AKI

Hospitalisation or ED visit due to DKA

Severe complications of UTI (inpatient and outpatient)—only in the
CPRD

Genital infections (inpatient and outpatient)—only in the CPRD
Secondary outcomes:

Hospitalisation, ED visit, or specialist visit for ALI in patients with and
without predisposing conditions

Chronic kidney disease (inpatient and outpatient)—only in the CPRD

Severe GI—only in the CPRD
A sensitivity analysis will be performed by adding outpatient primary care 
cases of ALI and AKI to the ALI and AKI primary outcomes. This analysis 
will be performed only in the CPRD and HIRD, where primary care data are
available.
Validation of identified cases will be implemented for all outcomes in the 
three data sources. In addition, a random sample of 100 additional 
outpatient/primary cases of ALI and AKI will also be validated in the CPRD
and HIRD. If the number of cases identified for any of the outcomes is 100 or 

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Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
fewer, all cases will be validated for those outcomes. Otherwise, a random 
sample of cases will be selected. The number of selected cases for validation 
will be based on the proportion of patients that can be validated in each 
database, and the target is to validate 100 cases.
Cases identified in the CPRD and Hospital Episode Statistics (HES) will be 
validated through questionnaires sent to general practitioners (GPs). Cases 
identified in the Danish Population Registries and in the HIRD will be 
validated through medical record data abstraction and/or laboratory test 
results.
Exposures (index drugs):

Empagliflozin (and fixed-dose combinations with metformin)

DPP-4 inhibitors: sitagliptin, saxagliptin, linagliptin, vildagliptin,
alogliptin (and fixed-dose combinations of these drugs with metformin)
Fixed-dose combinations of SGLT2 inhibitors with DPP-4 inhibitors will not 
be included in the study.
Current use of the index drugs will be defined from the date of prescription of 
empagliflozin or DPP-4 inhibitor to the end of supply for that prescription 
plus a period of 30 days. Recent use will be defined from the end of current 
use (30 days after end of supply) through 90 days later (which is 120 days 
after end of supply). End of day’s supply will be estimated according to 
prescription instructions in the CPRD or based on available information on the 
duration of dispensings (e.g., number of packages bought, strength, and 
number of pills) in Denmark and the HIRD.
Data sources:
The data sources included in the study will be the CPRD in the UK, and for 
the evaluation of the rarest outcomes, also the Danish Population Registries in 
Denmark and the HIRD in the US.
The CPRD contains diagnostic and prescribing information recorded by GPs
as part of their routine clinical practice in the UK. The database currently 
contains data for over 16.7 million patients in the CPRD GOLD database and 
22.7 million patients in the CPRD Aurum database, representative of the UK 
population in terms of age and sex, with research-quality data from 790 UK 
practices in CPRD GOLD and 873 practices in CPRD Aurum; 2.6 million of 
these patients in CPRD GOLD and 7.3 million patients in CPRD Aurum are 
active. Detailed information on prescriptions written by the GPs, including 

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Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
prescribed dose and duration, is routinely recorded in the database. Additional 
diagnostic and treatment information can be found in letters from specialists,
hospitals, and other sources. Linkage to the HES and cause-of-death 
information is currently available for approximately 54% of patients in CPRD 
GOLD and 93% of patients in CPRD Aurum [R19-1734].
The Danish Population Registries. The Danish health care system provides
universal coverage to all Danish residents (5.7 million inhabitants). The 
proposed registries are the Danish National Patient Register, which includes 
data on all hospital admissions since 1 January 1977 and on specialist 
outpatient hospital clinic and ED visits since 1995, and the National Health 
Services Prescription Database, which encompasses the reimbursement 
records of all reimbursed drugs sold in community pharmacies and hospital-
based outpatient pharmacies in Denmark since 2004. The national health
registries can be linked to all other national databases through the unique Civil
Personal Registration Number. No primary care diagnosis data are available
for research purposes, but the new nationwide Register of Laboratory Results 
for Research (LAB_F) tracks all laboratory test results from both primary and 
secondary care.
The HIRD contains geographically diverse longitudinal medical and 
pharmacy claims data from approximately 40 million health plan members 
across the US. Member enrolment, medical care (professional and facility 
claims), outpatient prescription drug use, outpatient laboratory test result data 
(available for 30% of the patients), and health care utilisation may be tracked 
for health plan members in the database dating back to January 2006. For 
approximately 50% of members, data in the HIRD can be linked to inpatient 
and outpatient medical records (source records for validation) and to national 
vital records (date and cause of death).
Study size:
The study size is driven by the uptake of empagliflozin after marketing
approval in the UK, Denmark, and US. With a comparator: empagliflozin ratio 
of 10:1 and a power of 80%, the study size required to detect an incidence rate 
ratio (IRR) of 3 (for the comparison of empagliflozin to comparator) is
between 18,000 and 30,000 person-years of empagliflozin use (among new 
users) for ALI, approximately 8,000 person-years for DKA, and 1,400 to 
3,200 person-years of empagliflozin use for AKI. For all other outcomes, the 
number of empagliflozin new-user person-years required to detect an IRR of 3 

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Proprietary confidential information © 2021 Boehringer Ingelheim International GmbH or one or more of its affiliated companies
Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
would be less than 1,400.
The number of empagliflozin new users and crude incidence rates of the 
events of interest have been assessed annually starting June 2016. Based on 
data from the second (2017) and third (2018) interim reports, the number of 
expected empagliflozin users by the end of the study period in the UK was 
projected to be insufficient to answer the scientific questions of interest for the 
outcomes of ALI, AKI, and DKA. The addition of data sources from Denmark 
and the US for these outcomes and the extension of the study period from 3 to 
5 years after launch for all the outcomes should allow the target number of 
users to accrue. 
Data analysis:
The following estimates and comparisons will be generated:
Crude and adjusted incidence rates of each of the outcomes among
empagliflozin new users and DPP-4 inhibitor new users. Incidence 
rates will be reported as point estimates (in cases per 1,000 person-
years) and 95% confidence intervals (CIs).
Summary IRRs, after adjusting for propensity score deciles, among
empagliflozin new users vs. DPP-4 inhibitor new users.
The adjusted IRRs for each of the primary outcomes will be the main effect 
estimates of interest. Adjusted incidence rates and IRRs will be calculated 
using analytic techniques involving stratification by categories of propensity 
scores. An additional analysis will further stratify the IRRs by categories of 
insulin use at the index date. Sensitivity analyses will be performed to 
evaluate the potential for other sources of bias and confounding.
Meta-analytic methods will be used to combine the IRRs obtained from the 
main analysis performed by all the data sources. 
Milestones:
The start of data collection (data extraction) is planned to occur between 
September 2019 and December 2019, depending on the time lag in each data 
source. Annual progress reports, including monitoring of users in each data
source, and project status were sent to EMA in June 2019 and June 2020. The
end of data collection was planned to occur between July 2020 and October
2020, once validation was finalised and all data were available to perform the 
planned analysis. However, validation could not be performed in time due to
the COVID-19 pandemic. There were delays in receiving the final datasets in
Denmark, and the start of data validation activities were also delayed in the

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Protocol for observational studies based on existing data
BI Study Number 1245.96
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Proprietary confidential information © 2021 Boehringer Ingelheim International GmbH or one or more of its affiliated companies
Name of company:
Boehringer Ingelheim International 
GmbH
Name of finished medicinal product:
Jardiance
Synjardy
Name of active ingredient:
A10BK03 Empagliflozin
A10BD20 Empagliflozin/metformin
Protocol date:
Study number:
Version/Revision:
13 Jun 2019
1245.96
8.0
Version/Revision date: 
19 July 2021
UK. Therefore, the end of data collection will occur between July 2020 and
March 2022 and the final report will be produced after completion of
validation activities and analysis in all three data sources included in this
study and is expected to be finalized by December 2022.

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5.
AMENDMENTS AND UPDATES
Protocol version 5.0 was to ensure enough new users of empagliflozin meet the study 
objectives by adding additional data sources to evaluate the rarest outcomes and extending
the study period for all outcomes. Considering the complexity of study with two comparator 
groups and multiple outcomes, and the inclusion of multiple databases, the study will be 
streamlined to focus on the core study objectives and facilitate the interpretation of the 
results. The exploratory analysis of one of the comparator groups (i.e., other SGLT2 
inhibitors) was deleted. The definition of the rarest outcomes has also been modified to have 
primary outcomes that are evaluable in all three data sources in a consistent manner. Finally, 
given the low number of cases for some of the outcomes, the plan for secondary and 
sensitivity analyses has been revised to avoid issues with sparse data. Protocol version 6.0 
clarified some of the changes proposed in version 5.0, to keep severe GI as a secondary 
endpoint, and to report the number of patients with elevated liver enzymes. Protocol version 
7.0 further clarifies aspects of the data analysis. In Protocol version 8.0, the study milestone
for the final report is updated to account for delayed validation activities due to the COVID-
19 pandemic.
Version number
Protocol date
Comment
1.0
05 Feb 2015
Draft protocol v1: submitted to PRAC for review
2.0
23 Jun 2015
Draft protocol v2: submitted to PRAC for review
3.0
21 Oct 2015
PRAC approved protocol
4.0
10 Jun 2016
PRAC approved protocol amendment no 1
5.0
17 May 2018
Draft protocol amendment no 2 (v1): submitted to PRAC 
for review
6.0
03 Dec 2018
Draft protocol amendment no 2 (v2): submitted to PRAC 
for review
7.0
03 Jun 2019
Draft protocol amendment no 2 (v3): submitted to PRAC 
for review
8.0
12 July 2021
Draft protocol amendment no 3: submitted to PRAC for
review
A detailed overview of changes implemented since the PRAC approved protocol (version
3.0) is presented below.

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
8.0
12 July
2021
Section 3
Updated responsible
parties
To reflect changes of responsible
parties
8.0
12 July
2021
Section 4
Updated abstract
To reflect changes in the protocol
milestones that have been delayed
due to the COVID-19 pandemic.
8.0
12 July
2021
Section 6
Updated milestones,
with a final report in 
December 2022
Completion of the final study report
is delayed due to the COVID-19
pandemic.
7.0
03 Jun 
2019
Section 4
Updated abstract
To reflect changes in the protocol
7.0
03 Jun
2019
Section 9.3
Updated list of DPP-
4 inhibitors 
As per PRAC request
7.0
03 Jun 
2019
Section 
9.3.2.1, 
9.3.2.3, 
and 9.3.2.8
Clarified that no ED 
visit information is 
available in HES; ED 
visits will be 
identified from the 
CPRD primary care 
records
As per PRAC request, to clarify in
which outcomes ED visits will be
used, and to describe ED visits 
ascertainment in CPRD
7.0
03 Jun 
2019
Section 
9.4.1 and 
9.5
Confirmed the use of 
CPRD Aurum and 
updated information 
about CPRD GOLD 
and CPRD Aurum 
databases, and on 
monitoring of users 
in CPRD Aurum
To increase study size in the UK. 
To describe the number of users 
expected to increase the study size 
in the UK, based on the monitoring 
of users of empagliflozin as of 
April 2019
7.0
03 Jun 
2019
Section 
9.7.5
Added information 
on the mechanism of 
missing not at 
random 
To clarify that for variables that are 
missing not at random, the 
missingness itself, by definition, is 
an unmeasured confounder. 
Sensitivity analyses evaluating the 
potential influence of unmeasured 
confounders have already been 
included.
7.0
03 Jun 
2019
Section 
9.7.6
Added information 
on sensitivity 
analyses
To document fully in one place all 
of the sensitivity analyses to be 
performed. Furthermore, an 
additional sensitivity analysis is 
described.
7.0
03 Jun 
2019
Section 
9.9.3.3
To clarify that the 
proportion of patients 
aged 65 years or 
As per PRAC request

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
older will be 
described for all data 
sources
7.0
03 Jun 
2019
Annex 4, 
Table 12, 
and Table 
14
Codes related to male 
complications of 
genital infections
have been moved 
from Table 12 to 
Table 14
To correct prior typographical error
6.0
03 Dec 
2018
Section 4
Update abstract
To reflect changes in the protocol
6.0
03 Dec 
2018
Section 8
Updated study 
objectives
To formulate a study objective for 
each primary and secondary 
outcome and retain severe genital 
infection as a secondary outcome
6.0
03 Dec 
2018
Section 
9.2.1
Updated text to 
provide further 
details
To further clarify case 
ascertainment and identification of 
T2D in each data source
6.0
03 Dec 
2018
Section
9.2.6
Clarified lookback 
period
To clarify that lookback period will 
be the same for most of the 
variables within each database, 
except for a small number of 
specific covariables
6.0
03 Dec 
2018
Section
9.2.7
Updated wording of 
inclusion criteria
To clarify the inclusion criteria, per 
PRAC request
6.0
03 Dec 
2018
Section 
9.3.1
Updated list of DPP-
4 inhibitors products
To include medications approved 
since previous versions of the 
protocol
6.0
03 Dec 
2018
Section 
9.3.2
Updated outcomes
definition
To include ED visits in addition to 
those outcomes that require 
hospitalisation
6.0
03 Dec 
2018
Section 
9.3.2
Updated validation 
of ALI cases
To describe cases of ALI that have 
ALT and/or AST ≥3 × ULN but 
< 5 ULN and therefore did not fulfil 
the Aithal et al. (2011)[R14-1933] 
criteria
6.0
03 Dec 
2018
Section
9.3.2
Reintroduced the 
genital infection
secondary outcome 
Per PRAC request, retained severe 
genital infection as an outcome and
added a description of 
complications of genital infection
6.0
03 Dec 
2018
Section 
9.3.3
Added description of 
cases of elevated 
To gain more knowledge about the 
potential hepatotoxicity of 

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
liver enzymes 
identified through 
laboratory results 
empagliflozin
6.0
03 Dec 
2018
Section 
9.4.1
Added description of 
CPRD Aurum
Per PRAC request
6.0
03 Dec 
2018
Section 
9.7.1
Provided additional 
details on potential 
methods to deal with 
propensity score 
deciles with zero 
events
To suggest alternative methods of 
estimating the adjusted treatment 
effect from propensity scores (in the 
situation of zero margins in 
propensity score strata)
6.0
03 Dec 
2018
Section 
9.7.5
Additional 
clarifications have 
been added
To account for situations where 
multiple imputation would not be 
applicable
6.0
03 Dec 
2018
Section 
9.7.7
Provided more detail
on meta-analysis 
techniques
To describe in more detail the meta-
analytic techniques and clarify that 
a random-effects model will be 
used as the main analysis and the 
fixed-effects model will be used in 
a sensitivity analysis
6.0
03 Dec
2018
Section 9.9
Added limitations
Per PRAC request. To provide 
details on limitations by data 
source, limitations due to current 
new user definition and to study 
size using all data sources, and 
generalisability of the results
6.0 
03 Dec 
2018
Annex 4
Reintroduced Read 
codes to identify
study outcomes
Per PRAC request
5.0
17 May 
2018
Section 3
Added responsible 
parties from the new 
data sources added to 
the study
To incorporate new responsible 
parties
5.0
17 May 
2018
Section 4
Updated abstract 
To reflect all changes to version 5.0
5.0
17 May 
2018
Section 6
Updated milestones, 
with a final report in 
2021
Changed due to extension of the 
study period and considering the 
time lag between the end of the 
study period and data extraction 
and the time needed for analysis 
and validation of the outcomes in 
each data source

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
5.0
17 May 
2018
Section 7
Updated 
epidemiology data 
for DKA
A study of interest was published 
after the approval of protocol 
version 4.0
5.0
17 May 
2018
Section 8
Deleted the 
comparison between
empagliflozin and 
other SGLT2 
inhibitors from the 
study objectives
The comparator group “other 
SGLT2 inhibitors” was qualified as 
exploratory in previous reviews of 
the protocol done by the EMA. The 
study is evaluating class effects, so 
it is not expected to find differences 
in the risk of the outcomes of 
interest between different SGLT2 
inhibitors; if differences exist, they 
will be small, and this study will 
not have the power needed to detect 
them. MAHs of other SGLT2 
inhibitors are doing similar analyses
for their products in similar or the 
same data sources. 
5.0
17 May 
2018
Section 8
Updated study 
objectives
To reflect changes in comparator, 
clarify that incidence rates of 
secondary outcomes will also be 
estimated, and streamline stratified 
analyses
5.0
17 May 
2018
Section 9.1
Update study design 
to add data sources 
and extended the 
study period
Per EMA feedback to the second 
interim report
5.0
17 May 
2018
Section 9.2
Updated setting to 
add data sources and 
extended the study 
period
Per EMA feedback to the second
interim report
5.0
17 May 
2018
Section 9.2
Updated study 
population to modify 
the definition of new 
users to not have a 
prescription or 
dispensing of the 
study medications 
during the 12 months
prior to the index 
date (previously 
defined as no prior 
use ever)
This will allow inclusion of more 
users of empagliflozin in the study, 
the main limitation of which is the 
accrual of patients exposed to the 
drug of interest. This definition has 
been used in other EMA-approved 
PASS, and it is considered
appropriate because the 
comparators are indicated for the 
same target population and same 
stage of the disease, and a 12-
month wash-out period is 
considered enough for the acute 

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
outcomes being evaluated.
5.0
17 May 
2018
Section
9.3.1
Updated exposures to 
delete other SGLT2 
inhibitors
Discussed above (see amendments 
to Section 8); exposure identified 
by prescriptions
5.0
17 May 
2018
Section
9.3.2
Deleted mention of 
Read codes and 
referred to codes in
the CPRD as 
“primary care” codes
To refer to all potential codes that 
may appear in the CPRD primary 
care databases: CPRD GOLD uses 
Read codes, but CPRD Aurum, 
which may be needed in the future, 
uses Read codes, SNOMED codes, 
and EMIS local codes
5.0
17 May 
2018
Section
9.3.2
Modified the ALI 
primary outcome 
definitions to be 
hospitalisation or 
referral to a specialist 
for ALI in patients 
with no predisposing 
conditions
To have a primary outcome that can 
be assessed in the three data sources 
included in the study. Outpatient 
ALI cannot be assessed in Denmark 
due to lack of primary care data but 
will be assessed in a sensitivity 
analysis in the CPRD and HIRD
5.0
17 May 
2018
Section
9.3.2
Modified ALI 
secondary endpoint 
definition to be
hospitalisation or
referral to a specialist
for ALI in patients 
with and without 
predisposing 
conditions
To have a secondary outcome that 
can be assessed in the three data 
sources included in the study
5.0
17 May 
2018
Section
9.3.2
Modified the AKI 
primary outcome 
definitions to be 
hospitalisation or 
referral to a specialist
for AKI
To have a primary outcome that can 
be assessed in the three data sources 
included in the study. Outpatient 
AKI cannot be assessed in 
Denmark due to lack of primary 
care data but will be assessed in a 
sensitivity analysis in the CPRD 
and HIRD
5.0
17 May 
2018
Section
9.3.2
Deleted UTI 
secondary outcome 
and modified 
primary UTI 
outcome to include 
outpatient diagnosis
Based on PRAC feedback to 
versions 1 and 2 of the protocol

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
5.0
17 May 
2018
Section
9.3.2
Deleted the genital 
infection secondary 
outcome
The genital infection primary 
outcome already includes outpatient 
and inpatient cases and is 
considered appropriate and 
adequate to address this safety 
concern
5.0
17 May 
2018
Section
9.3.3
Updated covariates 
section
Updated based on type and 
availability of data in each data 
source
5.0
17 May 
2018
Section 9.4
Added data sources 
and extended the 
study period
Per EMA feedback to the second 
interim report
5.0
17 May 
2018
Section
9.7.1
Clarified the selected 
approach for using 
propensity scores to
adjust for 
confounding
Based on literature, we have 
selected stratification by propensity 
score categories to adjust for 
confounding
5.0
17 May 
2018
Section
9.7.4
Specified 
stratification
variables during 
follow-up and 
deleted mention of 
the method
Specific method to evaluate 
potential confounders during 
follow-up will be defined in the 
statistical analysis plan 
5.0
17 May 
2018
Section
9.7.7
Added analysis using 
positive predictive 
value
To correct for outcome 
misclassification
5.0
17 May 
2018
Section
9.7.8
Added meta-analysis 
To combine the incidence rate 
ratios obtained from the main 
analysis of the cohort study 
performed in the different data 
sources
5.0
17 May 
2018
Section 9.8
Updated quality-
control section
To describe quality-control process 
in the newly added data sources
5.0
17 May 
2018
Section 9.9
Updated limitations
To discuss limitations driven by 
changes in the protocol given the 
addition of new data sources
5.0
17 May 
2018
Annex 4
and 5
Read codes have 
been deleted 
To retain codes that are common to 
the three data sources, streamline 
the protocol, and because CPRD 
Aurum, which uses other coding 
systems, may be used

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Version 
number
Date
Section of 
study 
protocol
Amendment or 
update
Reason
5.0
17 May 
2018
Annex 7 
and 8 
These annexes were 
deleted. Details on
the CPRD in 
previous Annex 7 
have been integrated 
with details on the 
Danish Health 
Registries and HIRD. 
Information on 
Spanish data sources 
has been deleted
To facilitate comparison of the 
three data sources in one table 
instead of two or three tables and to
update the annex to include the new 
study data sources
4.0
10 Jun 
2016
Cover page 
and 
abstract
Addition of Synjardy 
(empagliflozin/ 
metformin)
Synjardy came on the market in 
August 2013, after the approval of 
protocol version 3.0
4.0
10 Jun 
2016
Section 7.1
Added data on DKA 
in clinical trials and 
safety studies
New safety outcome added to the 
study
4.0
10 Jun 
2016
Section 7.7
Added data on the 
epidemiology of 
DKA
New safety outcome added to the 
study
4.0
10 Jun 
2016
Section 8
Added the evaluation
of the risk of DKA as 
a primary objective
New safety outcome added to the 
study
4.0
10 Jun 
2016
Section
9.3.2 and 
Annex 5
Added definition of 
the DKA outcome
New safety outcome added to the 
study
4.0
10 Jun 
2016
Section 9.6
Changed chi-square 
sample size 
calculation method 
for Poisson method
The Poisson method is considered 
more appropriate for rare events, 
and confidence intervals are also 
going to be estimated using Poisson 
method
4.0
10 Jun 
2016
Annex 6
Added covariates to 
be considered for 
inclusion in the 
propensity score 
model for DKA
New safety outcome added to the 
study
AKI = acute kidney injury; ALI = acute liver injury; CPRD = Clinical Practice Research Datalink; DKA = diabetic 
ketoacidosis; EMA = European Medicines Agency; HIRD =
Integrated Research DatabaseSM; 
MAH = marketing authorisation holder; PASS = post-authorisation safety study; PRAC = Pharmacovigilance Risk 
Assessment Committee; SGLT2 = sodium-glucose cotransporter 2; UTI = urinary tract infection.

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6.
MILESTONES
Milestone
Planned Date
Actual / Revised Date
Protocol 
(version 3.0)
endorsed by
the EMA
January 2016
January 2016
Protocol amendment no 1 (version 
4.0 to add DKA) endorsed by 
EMA in September 2017
Start of data 
collection1
15 March 2016 
15 March 2016 (monitoring in the
UK)
September 2019 (first data source) 
through December 2019 (last data 
source)
End of data 
collection2
31 December 2017 
July 2020 (first data source) 
through March 2022 (dependent on 
the start of data collection and 
duration of validation activities in 
each data source)
First interim
report 
Based on data available 19 months 
after use of empagliflozin was first 
captured in the CPRD
Expected in June 2016
Submitted in June 2016
Second 
interim report 
Based on data available 26 months 
after use of empagliflozin was first 
captured in the CPRD
Expected in June 2017
Submitted in June 2017
Third interim 
report 
Based on data available 37 months 
after use of empagliflozin was first 
captured in the CPRD
Expected in June 2018
Submitted in June 2018
Registration in 
the EU PAS 
Register3
10 May 2016 
10 May 2016 
(last updated 03 Jun 2020)
Annual 
progress 
reports4
Expected in June 2019 and June 
2020
Submitted in June 2019 and June
2020

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Milestone
Planned Date
Actual / Revised Date
Final report of 
study results 5
As per protocol version 3.0 final
report expected in July 2018.
As per Protocol version 7.0, the
planned date for completion of the
study report is September 2021.
As per Protocol version 8.0, the
planned date for completion of the
study report is December 2022.
December 2022
CPRD = Clinical Practice Research Datalink; EMA = European Medicines Agency; UK = United Kingdom.
Note: Approvals by data protection, data custodian, ethics, and scientific review bodies are pending. Timelines may be 
impacted by approvals of these bodies, duration of contract reviews, and availability of data and staff at research 
institutions once contracts and approvals are finalised.
1.
Start of data collection: the date from which information on the first study subject is first recorded in the study data set 
or, in the case of secondary use of data, the date from which data extraction starts [IR Art 37(1)]. Simple counts in a 
database to support the development of the study protocol, for example, to inform the sample size and statistical 
precision of the study, are not part of this definition [R13-5420]. For additional details on the dates of start of data 
collection, see the feasibility assessment (listed in Annex 1).
2.
End of data collection: the date from which the analytical data set is completely available [IR Art 37(2)] [R13-5420].
3.
ENCEPP/SDPP/13413; http://www.encepp.eu/encepp/viewResource.htm?id=13414.
4.
Will include monitoring the number of users in the databases, including CPRD Aurum, and study status.
5.
Study milestone for the final report is dependent on the initiation of validation activities in CPRD. December 2022 is 
an estimate based on communication received from CPRD on 09 Jul 2021, indicating that validation would be initiated 
end of July 2021.
7.
RATIONALE AND BACKGROUND
Jardiance (empagliflozin), a highly potent and selective inhibitor of the sodium-glucose 
cotransporter 2 (SGLT2), was approved in Europe in May 2014 for the treatment of type 2
diabetes mellitus (T2D) to improve glycaemic control in adults. SGLT2 is highly expressed 
in the kidney; as the predominant glucose transporter, it is responsible for the reabsorption of 
glucose from the glomerular filtrate back into the circulation. Empagliflozin improves 
glycaemic control in patients with T2D by reducing renal glucose reabsorption [R14-4617].
The recommended starting dose is 10 mg empagliflozin once daily for monotherapy and add-
on combination therapy with other glucose-lowering medicinal products including insulin. In 
patients tolerating empagliflozin 10 mg once daily who have an estimated glomerular 
filtration rate (eGFR) ≥60 mL/min/1.73 m2 and need tighter glycaemic control, the dose can 
be increased to 25 mg once daily. The maximum daily dose is 25 mg [R14-4617].
The overall frequency of treatment-emergent adverse events observed in the empagliflozin 
clinical trials and safety studies was comparable between treatment groups, between 70% and 
74% [P14-17456].
As part of the risk management plan, Boehringer Ingelheim International GmbH (BI) has 
committed to conduct a post-authorisation safety study (PASS) to evaluate the liver safety of 
empagliflozin due to a higher frequency of serious hepatic events in clinical trials and renal 

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safety of empagliflozin due to its mechanism of action. For the available information on renal 
and liver safety of empagliflozin, please refer to Section 7.1.
The study will also evaluate the risks of (1) severe complications of urinary tract infection 
(UTI) and (2) genital infection (GI). The rationale for looking at these risks is the fact that 
inhibition of SGLT2 in patients with T2D leads to excess glucose excretion in the urine
[R14-4617], which, together with hyperglycaemia, may be the main cause of increased 
susceptibility of patients with diabetes to UTI and GI. Although this mechanism is not
completely understood, it is known that increased glucose levels in genitourinary tissues 
enhance yeast adhesion and growth; thus, by providing a favourable growth environment for 
otherwise commensal microorganisms, glycosuria could potentially increase the risk for 
UTIs, vulvovaginitis, and balanitis. Moreover, hyperglycaemia not only impairs various 
aspects of host defence, including neutrophils and complement proteins, but also promotes 
the virulence of infecting organisms in patients with diabetes [P14-02878, R14-5237].
In addition, version 4.0 of the protocol added DKA as a safety topic of interest. The rationale 
for assessing this risk was that cases of DKA occurred in patients taking SGLT2 inhibitors 
for T2D, and a number of these cases had been atypical, with patients not having blood sugar 
levels as high as expected or even with levels in the normal range [P15-08785]. Clinically, 
DKA is defined by the biochemical triad of ketosis, hyperglycaemia, and acidosis. The 
condition usually occurs as a consequence of absolute or relative insulin deficiency that is 
accompanied by an increase in counter-regulatory hormones (i.e., glucagon, cortisol, growth 
hormone, catecholamines). This type of hormonal imbalance enhances hepatic 
gluconeogenesis and glycogenolysis, resulting in severe hyperglycaemia. Enhanced lipolysis 
increases serum free fatty acids that are then metabolised as an alternative energy source in 
the process of ketogenesis. This results in accumulation of large quantities of ketone bodies 
and subsequent metabolic acidosis. Although DKA has been considered to be indicative, or 
even diagnostic, of type 1 diabetes mellitus (T1D), cases of ketone-prone T2D are 
increasingly being recognised [R16-1372, R16-1373]. Atypical DKA reported in patients 
with T2D treated with SGLT2 has a different origin than that observed in patients with type 1
diabetes mellitus (T1D). Full-dose SGLT2 inhibition induces a rapid increase in urinary 
glucose excretion, ranging from 50 to 100 g/day, lasting slightly more than 24 hours.
Concomitant insulin intensification therapy was a common factor in most if not all cases. 
Depending on body size, glomerular filtration rate, and degree of hyperglycaemia, SGLT2-
induced glucose loss can make up a substantial fraction of daily carbohydrate availability
[P15-08785]. The different pathophysiology of DKA vs. atypical DKA induced by SGLT2 
inhibitors is that (1) in the latter, insulin deficiency and insulin resistance are milder, with less
glucose overproduction and underutilisation, which in most cases led to significant reductions 
in total daily insulin requirements, consequently leading to hypoinsulinaemia, and (2) renal 
glucose clearance (i.e., the ratio of glycosuria vs. glycaemia) is twice as large in atypical 
DKA as in DKA. Ketoacidosis follows the same sequence of events in both presentations of
DKA. However, in SGLT2-treated patients with T2D, the lower insulin-to-glucagon ratio 
stimulates lipolysis (increase in free fatty acids) and enhances lipid oxidation at the expense 
of carbohydrate oxidation. At low glucose concentrations, non-oxidative glucose disposal 
falls. The augmented free fatty acids delivered to the liver result in mild stimulation of 
ketogenesis, while fasting and mean post-meal beta-hydroxybutyrate levels increase; 

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conversely, plasma lactate levels decrease as an expression of reduced carbohydrate 
utilisation [P15-08785].
This protocol describes a cohort study, to be conducted among patients with T2D, comparing 
the incidence of the outcomes of interest in patients initiating empagliflozin compared with
patients initiating a DPP-4 (dipeptidyl peptidase-4) inhibitor. For each outcome, different 
inclusion/exclusion criteria will be applied, resulting in slightly different study cohorts to be
assessed for the risk of each outcome.
7.1
DATA ON THE OUTCOMES OF INTEREST IN EMPAGLIFLOZIN 
CLINICAL TRIALS AND SAFETY STUDIES
When the original protocol was developed, according to the Jardiance assessment report, 
published 20 March 2014 and including data across empagliflozin clinical trials and safety 
studies, as of 31 August 2012, there were 3,522 patients in the placebo group, with a total 
duration of exposure of 2,758.1 patient-years; 3,630 patients in the empagliflozin 10-mg 
group, with a total duration of exposure of 3,258.2 patient-years; and 4,602 patients in the 
empagliflozin 25-mg group, with a total duration of exposure of 4,448.1 patient-years
[P14-17456].
The frequency of hepatic injury (Standard MedDRA Query) was low and similar for all 
treatment groups (see Table 1) [P14-17456]. However, the number of serious hepatic events 
was higher in patients treated with empagliflozin than in the placebo group, with 19 of the 
22 cases of serious liver enzyme elevations occurring in one of the empagliflozin groups. 
There was also some imbalance seen for elevations of alanine aminotransferase (ALT) and/or 
aspartate transaminase (AST) (≥5 x the upper limit of the normal range [ULN], ≥10 x ULN, 
and ≥20 x ULN), when comparing empagliflozin and placebo users. A total of 7 patients 
(5 during treatment with empagliflozin, 1 after treatment with empagliflozin, and 1 during the 
screening period) had laboratory values consistent with Hy’s Law of drug-induced liver 
injury [R14-5256], although none of them were finally qualified as drug-induced liver injury 
due to plausible alternative hypotheses.
The frequency of decreased renal function was low and similar for all treatment groups (see
Table 1) [P14-17456]. The most common adverse event was renal impairment: 0.5% among 
the placebo group and 0.7% each among the empagliflozin 10-mg and 25-mg groups.
The frequency of UTIs was similar for all treatment groups (see Table 1) [P14-17456]. The 
incidence rate of UTI was 10.9 per 100 patient-years among the placebo group, 10.5 per 
100 patient-years among the empagliflozin 10-mg group, and 9.6 per 100 patient-years 
among the empagliflozin 25-mg group.
The frequency of GI was consistently higher among empagliflozin groups, compared with
placebo (see Table 1) [P14-17456]. The proportion of women with GI was 2-fold higher 
among women than among men. Empagliflozin groups had a 4-fold higher rate of GI than 
comparator groups irrespective of sex [P14-17456].

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In a retrospective analysis of randomised phase 2 and 3 empagliflozin trials 
(13,000 participants with T2D), there were eight events consistent with DKA, with no 
imbalance observed between patients treated with empagliflozin 10 mg (two events), 
empagliflozin 25 mg (one event), and placebo (five events). In the cardiovascular outcome 
trial EMPA-REG, with approximately 7,000 patients, the frequency of reported blinded 
events of DKA was less than 0.1% [P15-08785].
A meta-analysis of clinical trials of users of SGLT2 inhibitors vs. users of other antidiabetic 
medications reported an overall odds ratio of AKI of 0.80 (95% CI, 0.67-0.96), of UTI of 
1.15 (95% CI, 1.00-1.33), of male genital infections of 3.61 (95% CI, 3.10-4.19), of female 
genital infections of 3.17 (95% CI, 2.15-4.68), and of DKA of 1.96 (95% CI, 0.77-4.98)
[P18-00901].
Table 1
Frequency of adverse events of interest by treatment group in the 
empagliflozin clinical trials and safety studies – all patients
Adverse event
Frequency (%) of adverse events by treatment group
Placebo
(N = 3,522)
Empagliflozin 10 mg
(N = 3,630)
Empagliflozin 25 mg
(N = 4,602)
Hepatic injury
1.5
1.2
1.4
Decreased renal 
function
1.0
1.1
1.3
UTI
8.1
8.9
8.8
GI
1.0
4.4
4.7
DKA1
5
2
1
DKA = diabetic ketoacidosis; GI = genital infection; UTI = urinary tract infection.
1
Source for diabetic ketoacidosis: Rosenstock and Ferrannini [P15-08785]. The total number of patients in each 
treatment group does not include the diabetic ketoacidosis outcome, for which these numbers were not reported.
Source for adverse events except for diabetic ketoacidosis: Jardiance, European Public Assessment Report [P14-17456].
7.2
EPIDEMIOLOGY OF ACUTE LIVER INJURY
7.2.1
Epidemiology of acute liver injury in general population
The incidence of acute liver injury (ALI) and drug-induced liver injury in the general 
population has been poorly investigated. Data from several observational studies suggest that 
the annual incidence of drug-induced ALI in the general population ranges from 0.7 cases per 
100,000 persons (95% confidence interval [CI], 0.6-0.9) [P03-00488] to 13.9 cases per 
100,000 persons [P02-05969].
The study with the lowest incidence was performed in a hospital network surveillance system 
in Spain between 1993 and 1998 and identified 107 cases of ALI with a total follow-up of 
14.6 x 106 person-years [P03-00488]. The study with the highest incidence was conducted in 
France using intensive surveillance of cases in a well-defined geographic region between 

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1997 and 2000 and identified 34 cases of ALI [P02-05969]. Other cohort studies reported an 
incidence rate (per 100,000 persons) of drug-induced ALI of 2.3 (n = 77 cases) in a hospital 
outpatient hepatology clinic in Sweden between 1995 and 2005 [P06-11008] and 
3.4 (N = 461 cases) in a Spanish regional register between 1994 and 2004 [P05-08822].
Similarly, in a study conducted in the United Kingdom (UK) Clinical Practice Research 
Datalink (CPRD) between 1994 and 1999, 128 cases of ALI were identified, and the 
estimated incidence rate was 2.4 per 100,000 person-years (95% CI, 2.0-2.8) [P04-07683].
7.2.2
Epidemiology of acute liver injury in the diabetes population
Even fewer data are available on the incidence of ALI among patients with diabetes. The 
incidence rate of ALI among patients with diabetes without risk factors for liver disease in 
the UK CPRD between 1994 and 1998 was estimated to be 14.2 cases per 100,000 person-
years (n = 14 cases) [P03-03701]. Among users of oral glucose-lowering drugs (GLDs) the 
incidence rate was 22.0 cases per 100,000 person-years (n = 9 cases), and among users of 
insulin the incidence rate was 13.2 per 100,000 person-years (n = 3 cases). Among patients 
with diabetes, the adjusted relative risk of ALI among users of GLDs or insulin, compared 
with non-users of these medications, was 2.8 (95% CI, 0.6-12.5). In the same study, the 
incidence rate of ALI was estimated to be 8.8 per 100,000 person-years in the general 
population without diabetes [P03-03701].
In a cohort study performed in the United States (US) Veterans Affairs database between 
1985 and 2000, 173,643 hospitalised veterans with type 1 and type 2 diabetes, identified 
through ICD-9 (International Classification of Diseases, 9th Revision) code 250, were 
matched to 650,620 hospitalised veterans without diabetes. The incidence rate of ALI was
2.31 per 10,000 person-years (n = 346 cases after 1,494,995 person-years of follow-up) 
among patients with diabetes, and 1.44 per 10,000 person-years (n = 942 cases after 
6,556,350 person-years of follow-up) among patients without diabetes, with an adjusted 
hazard ratio of 1.44 (95% CI, 1.26-1.63). Chronic liver disease and increasing age increased 
the risk of ALI. Congestive heart failure was more frequent among patients with diabetes and 
ALI (31%) than patients without diabetes and ALI (22%). The 6-week mortality after 
hospitalisation with acute liver failure was 60% among patients with diabetes and 63% 
among patients without diabetes [R12-3632].
For the study size and power calculations (see Section 9.5), the estimates of the ALI 
incidence in the population with diabetes were used as reported by the two studies above 
[R12-3632, P03-03701]. Only one of these studies was performed in CPRD; however, as this 
study used data from 1994-1998 and was in a highly selected population (diabetes patients 
without risk factors for liver disease), both available studies were considered for the study
size calculations.

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7.3
EPIDEMIOLOGY OF ACUTE KIDNEY INJURY
Acute kidney injury (AKI) is characterised by an abrupt decline in renal function. The 
definition of acute renal failure in epidemiologic studies has been based on absolute increases 
of serum creatinine from normal values (1.7 or 2 x ULN) or change from baseline (20% to 
50%) or both [P02-05226, P05-04032, P14-17372, P14-17373, P14-17376, P14-17377].
7.3.1
Epidemiology of acute kidney injury in general population
Two studies have used large administrative and/or claims databases to examine secular trends 
in the epidemiology of AKI among the general population in the US. The first study was 
based on a total of 5,403,015 hospital discharges for AKI based on 5% of Medicare claims
and reported that the incidence of AKI rose from 14.6 to 36.4 per 1,000 discharges between 
1992 and 2001 [R11-5329]. The second study, using the Nationwide Inpatient Sample,
analysed a total of 1,083,745 AKI discharges (320,370 of which required dialysis) and 
reported that AKI incidence rose from 4 to 21 per 1,000 discharges between 1988 and 2002. 
For AKI requiring dialysis, the percentage of annual discharges increased from 0.3 in 1988 to 
2 per 1,000 discharges in 2002. For AKI requiring dialysis, the incidence rose from 4 per 
100,000 population in 1988 to 27 per 100,000 population in 2002 [R14-5285].
7.3.2
Epidemiology of acute kidney injury in the diabetes population
Among patients with diabetes, a study performed in the UK CPRD between 2003 and 2007 
reported an incidence rate of 198 per 100,000 person-years among patients with T2D and 
27 per 100,000 patient-years among those without T2D. The adjusted incidence rate ratio 
(IRR) of AKI was 2.5 (95% CI, 2.2-2.7) among patients with T2D compared with patients 
with no T2D [R11-5319]. Although the manuscript does not provide the incidence of 
hospitalisation for AKI, it could be estimated to be 65% of the above incidence rates given 
that this percentage of patients with AKI was identified through a referral or hospitalisation 
for AKI.
Scarce data have been published on the risk of AKI associated with exposure to antidiabetic 
medications. A nested case-control study performed in the UK CPRD between 1997 and 
approximately 2004 (end of study period not reported) reported a relative risk of AKI of 
2.5 (95% CI, 0.8-7.8) among patients with current exposure to insulin (n = 5) compared with
unexposed patients (n = 98). Similarly, the relative risk of AKI was 1.3 (95% CI, 0.5-3.1) 
among patients exposed to other antidiabetic drugs (n = 11), compared with unexposed
patients (n = 88) [P05-04032]. A cohort study compared the risk of AKI among SGLT2 
inhibitor users and non-users using data from the 
and the
cohort. Hazard ratios of AKI among users vs. non-users
were 0.4 (95% CI, 0.2-0.7) and 0.6 (95% CI, 0.4-1.1), respectively [P17-09718].
For the study size and power calculations, the estimates of the AKI incidence in the 
population with diabetes were used as reported in the UK CPRD study [R11-5319]. In 
addition, due to sparse data available, estimates reported in general population [R14-5258]
have been used as well; see Section 9.5.

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7.4
EPIDEMIOLOGY OF CHRONIC KIDNEY DISEASE
In a cross-sectional analysis of random samples from the nationally representative Health 
Survey for England that took place in England in 2003 and in 2009-2010, there were 
13,896 adults aged 16 years or older participating. Among 305 participants in 2003 and 
322 participants in 2009-2010 with doctor-diagnosed diabetes, the prevalence of chronic 
kidney disease (CKD) was 17.3% [R15-3134].
In a retrospective, longitudinal study assessing adults with prevalent or incident CKD 
(identified using estimated glomerular filtration rate readings and/or primary care codes) in 
the CPRD in 2010, the prevalence of stage 3-5 CKD in 2010 was estimated to be 5.9% 
(n = 165,942), and the prevalence of mildly impaired eGFR was 21.2% (n = 602,437), being 
the denominator for prevalence calculations the total CPRD population (n = 2,836,476). The 
prevalence of diabetes was 19.2% among patients with CKD stage 3-5, 13.2 among patients 
with mildly impaired eGFR and 6.1% in the general population [R15-3139]
The UK Prospective Diabetes Study (UKPDS) [R03-0585] was a clinical trial designed to 
evaluate the effects of improved blood glucose control and/or blood pressure control on the 
incidence of complications in patients with hypertension and newly diagnosed type 2
diabetes. The study included 5,102 participants 25-65 years of age (mean, 53 years), 
60% male; 4,031 without albuminuria and 5,032 with normal plasma creatinine at diagnosis. 
All patients were followed until the trial ended in 1997. The renal outcomes assessed were 
two measures of albuminuria (micro- and macroalbuminuria) and two measures of renal 
impairment (reduced creatinine clearance and doubling of baseline plasma creatinine). A 
reduced glomerular filtration rate was defined as an estimated creatinine clearance 
≤60 mL/min per 1.73 m2. Altogether, 1,544 of 4,031 patients (38%) developed albuminuria 
and 1,449 of 5,032 (29%) developed renal impairment over a median of 15 years after 
diagnosis of type 2 diabetes [R12-1479].
In the same UKPDS study, the absolute risk of renal failure was 1.4 events per 1,000 patient-
years among patients with tight control of the diabetes, and 2.3 events per 1,000 patient-years 
among patients with less tight control of diabetes. The absolute risk of death from renal 
failure was 0.3 event per 1,000 patient-years among patients with tight control of the 
diabetes, and 1 event per 1,000 patient-years among patients with less tight control of 
diabetes [R03-0585].
7.5
EPIDEMIOLOGY OF SEVERE COMPLICATIONS OF URINARY 
TRACT INFECTION
Untreated UTIs can lead to acute or chronic kidney infections (pyelonephritis), which could 
permanently damage the kidneys, and lead to urosepsis [R14-5259, R14-5286]. People with 
T2D are at higher risk for infections than people without diabetes [R12-1100], and women 
with T2D have a 2-fold higher risk of culture-confirmed UTIs than women without diabetes
[R12-1083, R14-5236, R14-5283].

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7.5.1
Epidemiology of severe UTI in general population
In a US hospital-based study of the general population, using the 1997 Healthcare Cost and 
Utilization Project Nationwide Inpatient Sample Release 6, the incidence of hospital 
discharges for acute pyelonephritis was estimated to be 11.7 per 10,000 persons-years in 
females (n = 160,848), and 2.4 per 10,000 persons-years in males (n = 30,718) [R14-5258]. 
Similarly, in another US study, 4,887 enrolees of Group Health Cooperative, based in Seattle,
Washington (US), received a diagnosis of acute pyelonephritis from 1997 through 2001. The 
annual rates of pyelonephritis among women were 12 to 13 outpatient cases per 10,000 
population and 3 to 4 inpatient cases per 10,000 population; among males, the annual rates of 
pyelonephritis were 2 to 3 outpatient cases per 10,000 population and 1 to 2 inpatient cases 
per 10,000 population [P14-17370].
7.5.2
Epidemiology of severe UTI in the diabetes population
In a review of hospital charts of pyelonephritis (n = 838 cases, 35 among patients with 
diabetes) and UTI (n = 976 cases, 11 among patients with diabetes) conducted in Canada
between 1991 and 1992, the rate of hospitalisations due to pyelonephritis ranged from 66 to 
144 per 10,000 person-years among women with diabetes and from 24.7 to 34.3 per 
10,000 person-years among men with diabetes, compared with 6.0 to 11.2 per 10,000 person-
years among females without diabetes and 1.7 to 10 per 10,000 person-years among males 
without diabetes [R14-5251].
Another cohort study performed in Denmark evaluated 10,063 individuals from the Danish 
general population who were participants in The Copenhagen City Heart Study and estimated 
the risk of hospitalisation caused by any infectious disease between 1991 and 2000. The 
study reported a total of 314 hospitalisations due to UTI and an incidence rate for
pyelonephritis of 158 per 10,000 person-years among patients with diabetes and 41 per 
10,000 person-years among patients from the general population [R12-1080].
A cohort study of the computerised medical database of the 
 
 General Practitioners Research Network selected all patients aged 45 years or older 
with diabetes between 1995 and 2003; the estimated annual incidence rate of pyelonephritis 
among patients with diabetes was 3 per 1,000 person-years (n = 16 cases), while the rate of 
outpatient diagnosis of UTI was 101 per 1,000 person-years (n = 2,000 cases) [R12-1105].
In a more recent study performed in the UK CPRD for the period 1990 to 2007, the incidence 
of outpatient diagnosis of UTI per 1,000 person-years was 46.9 (95% CI, 45.8-48.1) among 
patients with diabetes and 29.9 (95% CI, 28.9-30.8) among patients without diabetes. The 
study reported that, over the 1-year follow-up period, 5,967 UTI events were observed among 
patients with diabetes, and 3,708 UTI events were observed among patients without diabetes. 
The relative risk of UTI was 1.46 (95% CI, 1.40-1.53) among newly diagnosed patients with 
diabetes compared with patients without diabetes. Similarly, the relative risk of UTI was
2.08 (95% CI, 1.93-2.24) among patients with previously diagnosed diabetes compared with 
patients without diabetes. The risk was higher among females, older patients, patients with 

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previous diagnosis of diabetes, worst level of diabetes control, and a recent history of UTI
[R12-5226].
7.5.3
Epidemiology of sepsis in general population and in diabetes patients
The reported incidence rates of sepsis vary by study design and methods. A review of the
variations in the incidence and mortality of severe sepsis in the US used four methods or 
definitions and found that the annual incidence of sepsis ranged from 3 to 10.3 per 
1,000 patient-years, depending on the method used [R14-5287].
Among patients with diabetes, the incidence rate of sepsis was evaluated in a cohort study 
comparing all people with diabetes in Ontario, Canada, between 1999 and 2000, to a matched 
cohort without diabetes (513,749 patients in each group). The rate of sepsis among the 
diabetes cohort was 5.4 per 1,000 patient-years (number of cases not reported), and the risk 
ratio of sepsis vs. the non-diabetes cohort was 2.45 (95% CI, 2.23-2.68) [R10-6632]. The rate
of septicaemia among patients with T2D in Denmark in 2004-2012 was 5.5 per 1,000 person-
years, with an adjusted rate ratio of 1.60 (95% CI, 1.53-1.67) compared with individuals
without diabetes [P16-10382].
For the study size and power calculations, the incidence estimates of the acute pyelonephritis 
in the population with diabetes were drawn from the study in Netherlands [R12-1105]; 
estimates from the study performed in UK CPRD [R12-5226] could not be used as it had 
evaluated all forms of UTI including mild and not resulting in hospitalisation. Incidence rate 
of UTI hospitalisations reported in Denmark [R12-1080] has been used for the power 
calculations as well; see Section 9.5.
7.6
EPIDEMIOLOGY OF GENITAL INFECTIONS
Individuals with T2D are at higher risk for infections, including GI, than patients without
diabetes [R10-6632, R12-1080, R12-1088, R12-1100, R12-3639, R14-5248], and T2D is a 
risk factor for vaginal infections and balanitis [R12-2432, R14-5237, R14-5260]. Moreover, 
patients with diabetes have up to a 4-fold greater risk of dying due to infectious disease than 
patients without diabetes [R10-6632, R12-1080]. Women with diabetes have increased rates 
of asymptomatic vaginal carriage of Candida species and increased frequency of 
symptomatic infections [R12-2432, R14-5254].
While assessing the incidence or prevalence of GI using existing databases it is important to 
remember that the rates may be underestimated, as some of these cases may be self-limiting 
or may be treated with over-the-counter medications only.
An observational cohort study in the UK evaluated the risk of vaginitis and balanitis among 
patients with T2D and patients without diabetes in the UK CPRD database using electronic 
medical records between 1990 and 2007 [R12-3639]. Among females with T2D, there were 
1,243 cases of vaginitis: 87.5% recorded as vaginitis/candidiasis, 8.6% vulvitis, 2.2% 
bacterial vaginosis, and 1.7% related sexually transmitted diseases (STDs). The incidence 
rate of vaginitis was 21 per 1,000 person-years among patients with T2D and 10.3 per 

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1,000 person-years among females without diabetes (adjusted relative risk [RR], 1.81;
95% CI, 1.64-2.00). Similarly, there were 592 cases of balanitis among patients with T2D
classified as 85.4% balanitis/candidiasis, 8.1% penile/Candida infection, and 6.5% other (no 
STDs). The incidence rate of balanitis was 8.4 per 1,000 person-years among males with T2D
and 2.5 per 1,000 person-years among males without diabetes (RR, 2.85; 95% CI, 2.39-3.39).
The incidence rate of vaginitis and balanitis decreased with increasing age for males and 
females with T2D and females without diabetes, but not for males without diabetes (see
Table 2). Among patients with T2D, previous history of GI predisposed to GI, with an 
adjusted RR of 6.99 (95% CI, 5.97-8.18) for vaginitis and an adjusted RR of 11.22 (95% CI,
9.02-13.97) for balanitis. Also, worse control of diabetes, assessed by measuring glycated 
haemoglobin (HbA1c), was associated with an increased risk of GI among both treated and 
untreated patients with T2D (see Table 2).
Table 2
Incidence of vaginitis and balanitis among patients with T2D and patients 
without diabetes in the UK CPRD, 1990-2007
Vaginitis (females)
Balanitis (males)
T2D
(N = 62,537, 59,279
patient-years)
No diabetes
(N = 62,700, 57,844 
patient-years)
T2D
(N = 73,383, 70,088 
patient-years)
No diabetes
(N = 73,220, 67,676 
patient-years)
All ages
21 (19.8-22.1)
10.3 (9.5-11.1)
8.4 (7.8-9.1)
2.5 (2.1-2.9)
Age 18-39
~531
~26
~18
~2
Age 40-49
~42
~20
~16
~2
Age 50-59
~24
~11
~9
~2
Age 60-69
~19
~10
~7
~3
Age 70+
~12
~8
~5
~3
Not treated 
fair control
11.7 (10.0-13.5)
4.6 (3.6-5.6)
Not treated 
poor control
38.2 (31.6-44.8)
20.7 (16.6-24.8)
Treated fair 
control
15.0 (12.4-17.7)
4.4 (3.1-5.7)
Not treated 
poor control
23.9 (20.8-27.0)
11.5 (9.6-13.5)
T2D = type 2 diabetes mellitus.
Note: Incidence rates (95% CIs) are per 1,000 person-years.
1.
Incidence rates with an ~ symbol are approximate estimates derived from the published graph [R12-3639].
Another cohort study conducted in Canada (1999-2000) compared administrative data from 
all people with diabetes (n = 513,749) in Ontario with a matched cohort of 513,749 of people
without diabetes. The rate of GI among male patients with diabetes was 1,340 per 

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100,000 patients. The rate of GI among female patients with diabetes was 234 per 
100,000 patients [R10-6632].
For the study size and power calculations, the incidence estimates of the GI in men and 
women with diabetes were drawn from the study performed in UK CPRD [R12-3639], as it is 
most relevant for the study setting; see Section 9.5.
7.7
EPIDEMIOLOGY OF DIABETIC KETOACIDOSIS
DKA is the most common hyperglycemic emergency in patients with diabetes mellitus, 
leading to more than 100,000 hospital admissions each year in the US and comprising 4% to 
9% of all hospital discharge summaries among patients with diabetes mellitus. In Denmark, 
the annual incidence of DKA in the general population was estimated at 12.9 per 
100,000 [R16-4879]. In 20% to 30% of the cases of DKA, DKA may be the initial 
manifestation of diabetes, particularly for T1D [R16-1981]. Although DKA occurs most 
frequently in patients with T1D, it can also occur in patients with T2D [R15-2053]. The 
incidence of DKA is difficult to establish, ranging from 4.6 to 8 episodes per 1,000 patients 
with diabetes in population-based studies from the US [R16-1373]. In England, according to
the National Diabetic Audit, the 5-year prevalence of recorded DKA was over 12% in people 
with T1D and less than 1% in people with T2D. DKA occurred in 3.9% of the people with 
T1D and 0.48% of all people with diabetes (T1D and T2D) during 2009-2010; the occurrence 
of DKA in people with T2D was not reported [R16-1374]. In a recent UK study based on the 
CPRD 1998-2013, the incidence of hospital admission for DKA in T1D was 36 per 
1,000 person-years, and in T2D was 0.9 per 1,000 person-years [R18-1217].
The incidence of DKA among patients with T2D is not well established. A review of the 
medical records of all adult patients admitted to the medical intensive care unit of a medical 
centre in an Arizona (US) identified 226 patients with DKA: 47% had T1D, 26% had T2D, 
and 27% had DKA as the initial manifestation of diabetes (type not specified) [R16-1375]. A 
retrospective population-based study performed in Sweden on data from 1997 through 2000 
was performed to determine the occurrence of DKA in adult patients with T1D and T2D
[R14-3272]. All adult patients with severe hyperglycaemia or suspected DKA admitted to 
The Umeå University Hospital with a diagnosis code of DKA (ICD-10 codes: E10.0, E10.1, 
E11.0 and E11.1) were included. The average annual incidence rate for DKA was 5.9 per 
100,000 adult inhabitants. The annual incidence rate for DKA in patients with diabetes was 
50 per 100,000 adult patients with T2D and 1,585 per 100,000 adult patients with T1D. A 
total of 25 patients developed DKA: 8 (32%) had T2D, while 17 (68%) had T1D [R14-3272].
In a similar study performed in an Arizona (US) hospital, 226 patients with DKA were 
identified: 47% had T1D, 26% had T2D, and 27% had DKA as the initial manifestation of 
diabetes (type not yet specified) [R16-1375].
The incidence of DKA among patients with T2D using SGLT2 inhibitors in the context of 
routine clinical practice is not well understood. The low incidence of DKA in patients with 
T2D did not allow for conclusions on a potential association with SGLT2 inhibitor use. A
cohort study in the Truven MarketScan database, published in 2017, evaluated the risk of 
DKA among patients with diabetes mellitus who newly initiated either an SGLT2 inhibitor or 

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a DPP-4 inhibitor and found that the risk of DKA within 180 days of initiating an SGLT2 
inhibitor was 2.2 times greater than the risk for those initiating a DPP-4 inhibitor (hazard 
ratio after propensity score matching, 2.2; 95% CI, 1.4-3.6). However, it is important to note 
that this study, based on a limited number of cases, only reported data on SGLT2 inhibitors as 
a class and no drug-specific data were presented [R18-1215].
In 2016, a 5-year enhanced pharmacovigilance surveillance study of DKA (1245.146) was 
initiated by BI upon request by the US FDA. The first interim report for the DKA 
surveillance study was submitted and assessed by the EMA in 2017 [c19231123-01].
7.8
EPIDEMIOLOGY OF DIABETES AND ANTIDIABETIC TREATMENT 
PATTERNS
In the UK, the prevalence of diabetes has increased from 2.8% in 1996 to 4.3% in 2005, and
the incidence has increased from 2.7 per 1,000 person-years in 1996 to 4.4 per 1,000 person-
years in 2005.
In Denmark, 252,750 people were diagnosed with diabetes as of 01 January 2016, which
corresponds to 4.4% of the population. The number of people with diabetes (80% T2D) has 
more than doubled from 2000 to 2016. In 2016, about 16,300 new cases of diabetes were 
diagnosed in Denmark. About 60,000 Danes do not yet know that they have T2D, and 
another 300,000 are estimated to have precursors for T2D (prediabetes) [R18-1554].
In the US in 2015, 30.3 million Americans had diabetes (9.4% of the population); most had
T2D, and 1.25 million (~4.3%) had T1D. Approximately 1.5 million Americans are 
diagnosed with diabetes every year. Of the 30.3 million adults with diabetes, 23.1 million
were diagnosed and 7.2 million were undiagnosed; 84.1 million Americans aged 18 years or 
older had prediabetes [R18-1560]. From 1988-1994 to 2011-2012, the prevalence of diabetes 
increased significantly in the US population. The estimated prevalence of diabetes among US 
adults was 12% to 14% from 2011-2012 [R18-1558].
During the period 1996-2005, a change in oral GLD use has occurred, predominantly from 
sulfonylureas to metformin [R11-5320]. Moreover, since 2005-2006, the use of 
thiazolidinediones has decreased due to concerns about cardiovascular safety, which led to 
suspension of the rosiglitazone marketing authorisation in the European Union in 2010
[R12-1620]. Together with the introduction in the market of DPP-4 inhibitors, this has 
changed the selection of second-line treatment regimens, as shown in two studies performed 
in the UK. One was a cohort study performed in the CPRD from 2000 to 2010, which found
that the combination of metformin and DPP-4-inhibitors represented 0.7% of all second-line 
regimens in 2007, but DPP-4 inhibitors were prescribed in 20.2% of all second-line regimens
in 2010 [R14-5249]. On the other hand, the combination of metformin and thiazolidinediones 
(pioglitazone or rosiglitazone) represented 34% of the all second-line regimens in 2007 but 
only 9.8% in 2010 [R14-5249]. The other study was performed in The Health Improvement 
Network (THIN) database, where the annual incidence of prescriptions of thiazolidinediones 
decreased from 1.2 per 1,000 person-years in 2007 to 0.8 per 1,000 person-years in 2009, at 

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the same time that “other glucose-lowering drugs,” including DPP-4 inhibitors, increased 
from 0.2 per 1,000 person-years to 1.1 per 1,000 person-years [R14-5244].
A change in the use of GLDs in the last decade was also observed in a study performed in 
Denmark using data from medstat.dk, a publicly accessible webpage from the Danish Health 
Data Authority that provides aggregate statistics on sale of pharmaceuticals in Denmark, 
based on individual-level data. During the period 1999 through 2014, the annual prevalence 
of GLD users increased more than twofold, from 19 per 1,000 inhabitants (n = 98,362) in 
1999 to 41 per 1,000 (n = 233,230) in 2014. The most frequently prescribed GLDs were 
metformin (72% of all persons using GLDs), followed by insulin (33%) and sulfonylureas 
(15%). Use of sulfonylureas decreased since 2007. In contrast, prescribing of DPP-4 
inhibitors increased steadily since their introduction in 2007; in 2014, 3 per 1,000 used a 
combination pill of metformin and a DPP-4 inhibitor and 3 per 1,000 redeemed a prescription 
of a DPP-4 inhibitor noncombination pill. SGLT-2 inhibitor use reached 0.8 per 1,000 within 
the third year after introduction to the Danish market (123 using a combination pill with 
metformin and SGLT-2 inhibitor and 4,398 using a noncombination pill). The prevalence of 
thiazolidinedione users decreased from 0.7 per 1,000 in 2007 to 0.03 per 1,000 in 2014. 
Prescriptions of alpha-glucosidase inhibitors and meglitinides remained low over time. 
Despite a steadily increasing absolute number of insulin users, the proportion of all GLD
users who used insulin declined from 41% in 1999 to 33% in 2014[R18-1559].
In the US, among participants with self-reported physician diagnosis of diabetes in the 2000
through 2009 National Health Interview Surveys, 38% reported use of antidiabetic 
monotherapy, 52% use of combined antidiabetic therapy, and 10% reported no drug use for
diabetes. Among users of monotherapy, the most frequent medication was insulin (33.0% to 
37.2%), followed by metformin (27.3% to 33.3%) and sulfonylureas (21.9% to 25.9%). The 
most common combination therapies were metformin with sulfonylureas (20.1% to 21.9%), 
followed by insulin with any oral GLD (15.3% to 16.9%); thiazolidinediones with any other 
oral GLD (13.1% to 13.6%); metformin with sulfonylurea and thiazolidinediones (6.8% to 
7.8%); and metformin, sulfonylureas, and insulin (5.0% to 6.9%). Any other combination of 
GLDs was used by 36.3% to 36.5% of the patients using combination therapies [R18-1557].

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8.
RESEARCH QUESTION AND OBJECTIVES
The primary research question is to evaluate whether, among patients with T2D, initiation of
empagliflozin changes the adjusted incidence of outcomes compared with initiation of a
DPP-4 inhibitor.
The primary objectives of the study are as follows:

To estimate the adjusted IRR of hospitalisation, emergency department (ED) visit, or 
specialist visit for ALI in patients with no predisposing conditions, by comparing 
patients initiating empagliflozin with patients initiating a DPP-4 inhibitor, among 
patients with T2D.

To estimate the adjusted IRR of hospitalisation, ED visit, or specialist visit for AKI by 
comparing patients initiating empagliflozin with patients initiating a DPP-4 inhibitor,
among patients with T2D.

To estimate the adjusted IRR of severe complications of UTIs (pyelonephritis and 
urosepsis) (inpatient and outpatient) by comparing patients initiating empagliflozin
with patients initiating a DPP-4 inhibitor, among patients with T2D.

To estimate the adjusted IRR of GI (inpatient and outpatient) by comparing patients 
initiating empagliflozin with patients initiating a DPP-4 inhibitor, among patients with 
T2D.

To estimate the adjusted IRR of hospitalisation or ED visit for DKA by comparing 
patients initiating empagliflozin with patients initiating a DPP-4 inhibitor, among 
patients with T2D.
The secondary objectives of the study are as follows:

To estimate the adjusted IRR of hospitalisation, ED visit, or specialist visit for ALI in 
patients with or without predisposing conditions, by comparing patients initiating 
empagliflozin with patients initiating a DPP-4 inhibitor, among patients with T2D.

To estimate the adjusted IRR of CKD (inpatient and outpatient), by comparing 
patients initiating empagliflozin with patients initiating a DPP-4 inhibitor, among 
patients with T2D.

To estimate the adjusted IRR of severe GI by comparing patients initiating 
empagliflozin with patients initiating a DPP-4 inhibitor, among patients with T2D.

To estimate adjusted IRRs for each of the primary outcomes (ALI in patients with no
predisposing conditions, AKI, UTI, GI, and DKA) and secondary outcomes (ALI in 
patients with or without predisposing conditions, CKD, severe GI)—stratified by 
categories of insulin use at the index date, age, sex, and other variables of interest 
such as diabetes control—by comparing patients initiating empagliflozin with patients 
initiating a DPP-4 inhibitor, among patients with T2D.

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
To estimate adjusted incidence rates for each of the primary outcomes (ALI in 
patients with no predisposing conditions, AKI, UTI, GI, and DKA) and secondary 
outcomes (ALI in patients with or without predisposing conditions, CKD, severe 
GI)—overall and stratified by categories of insulin use at the index date, age, sex, and 
other variables of interest such as diabetes control—among patients with T2D
initiating empagliflozin or a DPP-4 inhibitor.
9.
RESEARCH METHODS
9.1
STUDY DESIGN
An observational cohort study will be conducted in the CPRD in the UK, and for the 
evaluation of the rarest outcomes (ALI, AKI, and DKA) also in the Danish Population 
Registries in Denmark, and in the 
 Integrated Research DatabaseSM (HIRD) in 
the US. The study will use a new-user (also known as incident-user) design and will compare
new users of empagliflozin with new users of DPP-4 inhibitors.
The new-user design avoids comparing a population predominantly composed of first-time
users of a newly marketed drug such as empagliflozin with a population of prevalent users of 
an older drug who may have stayed on the comparator treatment for a longer time and be less 
susceptible to the events of interest. To avoid the inclusion of prevalent users, patients 
starting empagliflozin will be required to be new users, defined as having no exposure to 
empagliflozin, another SGLT2 inhibitor drug, or a DPP-4 inhibitor during the 12 months
before or at the index date. Patients starting a DPP-4 inhibitor will be required to have no
exposure to a DPP-4 inhibitor, empagliflozin, or another SGLT2 inhibitor during the 
12 months before or at the index date (see further details in Section 9.2.3,New user 
definition) [R13-1120, R14-4378].
Empagliflozin is usually a second- or third-line treatment for T2D; thus, it is expected that 
few patients with T2D initiating empagliflozin will be treatment naive. For the majority of 
patients, empagliflozin will be added to an existing treatment (e.g., added to metformin), or 
patients will be switched to empagliflozin (e.g., from metformin plus an oral GLD other than 
the study drugs to metformin plus empagliflozin) due to disease progression, treatment 
failure, or side effects that may be related to study outcome. According to newer guidelines, 
double and even triple therapy may be started at diabetes debut if there is poor glucose 
control [P18-01920]. In this scenario, if analysis evaluating confounding and interaction 
suggest that the effect of drug exposure varies between patients on second- vs. third-line 
therapy, and if the number of events is sufficient, additional analysis will be done to achieve a 
fair comparison [R13-1120]. In the same way, patients starting a combination of 
empagliflozin and metformin (whether a fixed-dose or free combination) will be compared 
with patients starting a combination of a DPP-4 inhibitor and metformin.
A cohort design will allow direct estimation of the absolute rates, rate differences, and 
relative risk or hazard ratios of multiple outcomes of interest among new users of 
empagliflozin compared with new users of a DPP-4 inhibitor. A cohort study design will also 
allow accurate chronologic confounder assessment and assessment of the outcomes at 

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multiple time points. The covariate information will be assessed during the time preceding 
treatment initiation and will include all historical information available for each patient. 
Follow-up will start the day after treatment initiation. In the context of data sources such as 
the CPRD, Danish Population Registries, and HIRD, the use of a cohort design has more 
advantages than limitations compared with the use of a nested case-control design—see the 
appendix discussion in Schneeweiss (2010) [R13-1120] and Patorno et al. (2014) 
[R14-4378].
DPP-4 inhibitors have been selected as a comparator group for several reasons. First, the 
 appraisal of dapagliflozin (an
SGLT2 inhibitor) recommended that dapagliflozin should be used as described for DPP-4 
inhibitors. The 
 Evidence Review Group considered that, overall, “DPP-4 inhibitors are 
the key comparators for dapagliflozin in both the dual therapy and triple therapy settings”
[R13-5134]. Second, DPP-4-inhibitors, SGLT2 inhibitors, and thiazolidinediones 
(pioglitazone) have similar indications and target population, while dual therapy with GLP-1 
(glucagon-like peptide-1) analogues has a restricted target population [P14-17374]. Finally, 
the use of thiazolidinediones has decreased in recent years, given increasing concerns about 
their safety, and at the same time, use of DPP-4 inhibitors increased, making second-line 
regimens with DPP-4-inhibitors the most common second-line regimens after metformin with 
sulfonylurea (see Section 9.4) [R14-5244, R14-5249].
Propensity scores will be estimated for each cohort member based on information before or at 
the index date. Propensity scores will incorporate measured potential predictors of the 
outcome as independent variables and exposure group status as the dependent variable. 
Propensity scores will be used to minimise confounding.
9.2
SETTING
9.2.1
Study population
Empagliflozin is expected to be prescribed mainly by general practitioners (GPs) and 
specialists, and most of the follow-up prescriptions (for chronic treatment) will also be issued 
by GPs or primary care physicians. Thus, the selected study populations will be adult patients 
identified using data on prescriptions written by GPs in the CPRD, dispensings in community
pharmacies in Denmark, and health insurance claims for outpatient medication dispensings in 
the HIRD during the study period.
For ascertainment of hospitalisation-related study outcomes, hospital data from each data 
source will be obtained for more complete information on the study outcomes. For the CPRD, 
linkage with Hospital Episode Statistics (HES) will be available for a subset of available 
patients. Among patients not linkable to HES in the CPRD, GP records of hospitalisations 
will be used to identify hospitalisation-related study outcomes. For Denmark, ascertainment 
of hospitalisation-related study outcomes will be based on data from inpatient hospital 
discharge diagnoses that are available for all patients across Denmark. For the HIRD, 
ascertainment of hospitalisation-related study outcomes will be based on data from inpatient 
hospital discharge diagnoses that are available for all patients in the HIRD database.

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The study population will include eligible adult male and female patients with T2D initiating 
treatment with empagliflozin or initiating a DPP-4 inhibitor. Type 2 diabetes mellitus will be 
identified based on the type and availability of data in each data source. In the CPRD, 
patients with T2D will be identified based on a combination of outpatient and inpatient codes 
for T2D, T1D, diabetes unspecified, and GP prescriptions for insulin and non-insulin GLD 
using an adapted definition from Holden et al. [R13-3433]. In Denmark, patients with T2D 
will be identified based on a combination of community pharmacy prescription data, hospital 
codes, and primary care procedure codes [R18-1213]. In the HIRD, patients with T2D will be 
identified based on outpatient and inpatient health care claims with ICD-9-CM or 
ICD-10-CM diagnosis codes for T2D, as well as pharmacy dispensing claims for antidiabetic 
medications. These criteria are based on published studies in which similar algorithms had 
PPVs greater than 85% for identifying T2D in health care claims data [R16-3197, R18-3576, 
R18-3667].
9.2.2
Study period
The study period will start in August 2014, the month of empagliflozin launch in the UK,
Denmark, and the US. Based on interim counts, the study end date (originally August 2017)
will be extended through August 2019.
9.2.3
New user definition
New users will be patients with a prescription/dispensing for empagliflozin or a DPP-4 
inhibitor during the study period and no prescription/dispensing for empagliflozin, another 
SGLT2 inhibitor drug, or a DPP-4 inhibitor during the previous 12 months. Patients will be 
allowed to be new users of a study medication only once during the study period but will be 
allowed to be new users of the other study medication if they fulfil the inclusion/exclusion 
criteria.
9.2.4
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 metformin, when available.
9.2.5
Index date
The index date will be defined as the date on which each identified new user receives the 
index prescription for empagliflozin or DPP-4 inhibitor comparator.
9.2.6
Baseline and lookback period
To characterise the empagliflozin and DPP-4 inhibitor 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, 
i.e., will include the index date, unless otherwise specified. As all cohort members are 

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required by inclusion criteria to have at least 12 months of data before the index date
(baseline period), the lookback period will include at least 365 days during which covariates 
can be evaluated. For some of the cohort members, more data on covariates might be
available beyond 365 days, and all available information will be considered for covariate 
classification related to diabetes, diabetes medications, and concomitant chronic conditions.
Nevertheless, for comedications (i.e., for diseases other than diabetes) the lookback time 
period will be limited to 180 days before or at the index date. Lookback time periods for a 
small number of specific covariables may be adapted in each data source, e.g., to define body 
mass index (BMI) in the CPRD, the closest data in the 3 years before or at the index date will 
be used [R15-4888, R16-1231].
If the distribution of the duration of lookback time period is different among empagliflozin
and DPP-4 inhibitor groups, categories of lookback time will be created using indicator 
variables. Those indicator variables will then be used as covariates in the multivariable 
regression models for outcome prediction, and for propensity score development, to control 
for possible differences in availability of information between the empagliflozin and 
comparator cohorts.
9.2.7
Inclusion criteria
All patients will be required to meet all of the following criteria:

Be aged 18 or more years at the index date.

Have at least 12 months of continuous registration before or at the index date. In the 
CPRD this means registration in a primary care practice with up-to-standard data. In 
Denmark, this means residency in the country. In the HIRD, this means enrolment in 
the health care plan.

Have T2D ever before or at the index date: the algorithm to identify patients with T2D
will be adapted to the type of data available in each data source. This algorithm may
include medication codes and will be described in the statistical epidemiological 
analysis plan.
The empagliflozin-exposed population must also meet the following criteria:

Have at least one prescription for empagliflozin or fixed-dose combination of 
empagliflozin with metformin, with or without treatment with another GLD.

Have no prior prescriptions of any SGLT2 inhibitor (including empagliflozin) or a 
DPP-4 inhibitor alone or in fixed-dose combination during the previous 12 months.

The population exposed to a DPP-4 inhibitor must meet the following criteria:

Have at least one prescription for a DPP-4 inhibitor or a fixed-dose combination of a 
DPP-4 inhibitor with metformin with or without treatment with other GLDs.

Have no prior prescriptions of a DPP-4 inhibitor or an SGLT2 inhibitor (including 
empagliflozin) alone or in fixed-dose combination during the previous 12 months.

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9.2.8
Exclusion criteria
Patients with a confirmed diagnosis of T1D before or at the index date will be excluded from 
the study. The final algorithm to identify patients with T1D will be adapted to the type of data 
available in each data source. This algorithm may include a combination of diagnosis and 
drug prescription codes and will be described in the statistical epidemiological analysis plan.
Patients prescribed/dispensed combinations of SGLT2 inhibitors with DPP-4 inhibitors at the 
index date (as fixed-dose combinations such as Glyxambi® [empagliflozin and linagliptin], 
or as non–fixed-dose combinations of the two individual medications prescribed on the same 
date) will be excluded.
9.2.8.1
Exclusion criteria by outcome of interest
Different exclusion criteria will be applied to generate sets of cohorts for the analysis of the 
outcomes of interest.
For analysis of the primary outcome “ALI in patients with no predisposing conditions,” the 
following set of exclusion criteria will be applied:
1. A diagnosis of ALI is recorded any time before or at the index date (i.e., during the 
available lookback time). Annex 3 contains ICD-10 (International Statistical 
Classification of Diseases and Related Health Problems, 10th Revision) codes for 
these exclusion conditions (Annex 3 Table 1).
2. Pregnancy at the index date, because pregnancy can be associated with an increased 
risk of hepatic injury. Specific liver disorders associated with pregnancy include 
preeclampsia, acute fatty liver of pregnancy, intrahepatic cholestasis of pregnancy, 
and hyperemesis gravidarum [P15-00346]. Pregnancy will be identified through 
diagnosis codes compatible with initiation and/or termination of pregnancy, and 
duration of pregnancy will be estimated through specific time windows set up around 
the date of diagnosis.
3. A diagnosis of the following chronic conditions recorded any time before or at the 
index date—Annex 3 contains ICD-10 codes (Annex 3 Table 1):

Chronic liver disease

Chronic alcoholism

Chronic infectious hepatitis

Chronic disease involving the liver or causing hyperbilirubinaemia

Chronic cholelithiasis and cholecystitis

Intra- or extrahepatic biliary obstruction

Chronic pancreatic disease

Primary or secondary hepatic, biliary, or pancreatic cancer

Congestive heart failure
For analysis of the ALI secondary outcome, patients will be excluded if they meet any of the 
following criteria:

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1. A diagnosis of any of the following acute conditions within 6 months before or at the 
index date—Annex 3 contains ICD-10 (International Statistical Classification of 
Diseases and Related Health Problems, 10th Revision) codes (Annex 3 Table 1) for 
these exclusion conditions:

ALI

Acute infectious hepatitis

Acute cholelithiasis and cholecystitis

Acute intra- or extrahepatic biliary obstruction

Acute pancreatic disease

Decompensated congestive heart failure (i.e., hospitalisation)
2. Pregnancy at the index date
For analysis of the AKI primary outcome, patients will be excluded if they meet any of the 
following criteria:

A diagnosis of AKI is recorded within 6 months before or at the index date. Annex 3 
contains ICD-10 codes (Annex 3 Table 2) for AKI.

A diagnosis of CKD is recorded any time before or at the index date (i.e., during the 
available lookback time). Annex 3 contains ICD-10 codes (Annex 3 Table 3) for 
CKD.
For the analysis of CKD (kidney secondary outcome), patients will be excluded if they meet 
the following criterion:

A diagnosis of CKD is recorded any time before or at the index date (i.e., during the 
available lookback time). Annex 3 contains ICD-10 codes (Annex 3 Table 3) for 
CKD.
For analysis of the UTI outcome, patients will be excluded if they meet any of the following 
criteria:

The patient experienced chronic or acute pyelonephritis within the 6 months before or 
at the index date (see Annex 3 Table 4 for ICD-10 codes for pyelonephritis).
9.2.9
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 a DPP-4 inhibitor.
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; a diagnosis of ALI, AKI or CKD, severe 
complications of UTI, GI, or DKA.

The date of death.

The date of study end.

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
The date of transfer out of the practice or last collection date of a practice in the 
CPRD, emigration date in Denmark, or end of health plan eligibility in the HIRD.

The date that outcome-specific exclusion criteria are met (see exclusion criteria in
Section 9.2.8). Exclusion criteria will be specific for primary and secondary outcomes, 
e.g., for the ALI primary outcome, criteria such as chronic liver disease occurring any 
time before or at the index date.

The end date of the first continuous treatment of the index drug (empagliflozin or 
DPP-4 inhibitor) plus a defined grace period (see also Section 9.3.1.1):

Current use analysis (main analysis): 30 days after the end of the last 
prescription’s supply.

Recent use analysis: 90 days after the end of current use, i.e., 120 days after 
the end of the last prescription’s supply.

Sensitivity analysis: the earliest of 90 days after the end of the last 
prescription’s supply or the date on which a new treatment episode starts with the 
same index drug.

Intention-to-treat sensitivity analysis: follow-up will not be censored at the end 
of the first continuous treatment of the index drug, i.e., this criterion will not be 
applied for this analysis.

Within each exposure cohort, the date on which a new treatment episode with any of 
the other index drugs or other SGLT2 inhibitors starts. This criterion will not be 
applied for the intention-to-treat sensitivity analysis.
Patients will be able to re-enter another study cohort (not the original cohort) if they fulfil 
inclusion and exclusion criteria, including no prior use of any of the study medications during 
the previous 12 months. Follow-up will not be censored if oral or injectable GLDs other than 
the index drugs are prescribed in addition to empagliflozin or a DPP-4 inhibitor after the 
index date. All censoring criteria, except otherwise specified, will be applied in the intention-
to-treat analysis.
9.3
VARIABLES
9.3.1
Exposures
For this study, eligible patients will be identified from prescriptions/dispensings of the study 
medications of interest listed in the data sources included in the study.
Empagliflozin alone (Jardiance, ATC code A10BX12 before 2016, A10BK03 beginning in 
2017) or in fixed-dose combination with metformin hydrochloride (Synjardy, ATC code 
A10BD20) will be the study drug of interest. The oral GLDs currently suggested as 
comparators are DPP-4 inhibitors (see Sections 9.1 and 9.4). Empagliflozin in fixed-dose 
combination with linagliptin, a DPP-4 inhibitor (ATC code A10BD19) will not be included 
as a study medication group. Currently, the following DPP-4 inhibitors, as available in each 
country, will be comparator medications for study purposes:

Sitagliptin: ATC code A10BH01

Vildagliptin: ATC code A10BH02

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
Saxagliptin: ATC code A10BH03

Alogliptin: ATC code A10BH04

Linagliptin: ATC code A10BH05

Sitagliptin and metformin hydrochloride: ATC code A10BD07

Vildagliptin and metformin hydrochloride: ATC code A10BD08

Saxagliptin and metformin hydrochloride: ATC code A10BD10

Alogliptin and metformin hydrochloride: ATC code A10BD13

Linagliptin and metformin hydrochloride: ATC code A10BD11
Users of SGLT2 inhibitors in fixed-dose combination with DPP-4 inhibitors, such as 
Glyxambi (empagliflozin/linagliptin), will not be included in the study. If additional DPP-4 
inhibitor drugs are marketed in the future in the UK, Denmark, or the US during the study 
period, they will also be considered to be members of the comparator group.
In clinical practice, new users of index drugs (empagliflozin and DPP-4 inhibitors) may be 
prescribed the drug in the context of (1) adding it to an existing GLD regimen as double or 
triple therapy or (2) switching from one GLD to the study drug as monotherapy or 
combination therapy. Relatively few patients with T2D will be starting DPP-4 inhibitors 
naive to other GLDs since monotherapy indication for these drugs is restricted to patients 
intolerant to metformin and sulfonylureas. Thus, new users of the study drugs would usually 
be (1) switching from monotherapy with another GLD to monotherapy with a study drug, 
(2) switching from dual or triple therapy with another GLD to dual or triple therapy with a 
study drug and other GLDs, or (3) adding a study drug to therapy with one or two other 
GLDs to become patients on dual or triple therapy. However, new users of the study drugs 
may also have started SGLT2 inhibitors or DPP-4 inhibitors from the start of diabetes therapy 
if hyperglycaemia was substantial at diabetes diagnosis, i.e., new users may be combination 
therapy users from the beginning. This approach is consistent with the new-user design 
described previously in Section 9.1 [R13-1120]. Information on whether patients received 
prior GLD therapy or if they were “added on” or “switched to” empagliflozin or a DPP-4
inhibitor at the time of inclusion in the study will be collected. Patients will be classified 
according to their treatment complexity as receiving mono vs. dual vs. triple therapy.
9.3.1.1
Exposure and time at risk
For this study, it will be assumed that the risk of ALI, AKI, severe complications of UTI, 
DKA, and GI related to use of empagliflozin or DPP-4 inhibitors (the index drugs) increases 
at the beginning of therapy, is maintained at an increased level for the duration of treatment 
and decreases gradually to the background risk once treatment is stopped.
Only use at the first continuous treatment will be considered, defined as having consecutive 
prescriptions/dispensings separated by 30 days or less. Therefore, the risk/exposure time 
window for each new user of an index drug—empagliflozin or DPP-4 inhibitor—will be 
categorised into two mutually exclusive categories of risk, as follows (Figure 1):

Current use (current time at risk): The risk/exposure window for current use starts on 
the date of the prescription and ends 30 days after end of supply. The main analysis is 

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based on current use. This time at risk will be used for comparisons and estimation of 
IRRs in the study main analysis.

Recent use (recent time at risk): The risk/exposure window for recent use starts at the 
end of current use (30 days after end of supply) and ends the earliest of 90 days later 
(which is 120 days after end of supply) or at any censoring event (including a new 
prescription for a study medication). The time at risk for recent use will be used in an 
additional analysis (see Section 9.7.3).
Overlapping time at risk from current use for consecutive prescriptions/dispensings of the 
index medication will be concatenated, with the overlapping time added at the end of the 
concatenated prescription. For consecutive prescriptions/dispensings of the index medication 
separated by gaps of 30 days or less, time at risk from current use will include the gaps
between prescriptions/dispensings.
In the CPRD and in the US, since most oral GLD prescriptions/dispensings are supplied for 
30 days, for the majority of cohort members, the risk window defining current use will end 
60 days after the last prescription date. By adding 30 days to the end of the days’ supply, a 
delayed increase in risk for ALI, AKI, severe complications of UTI, DKA, or GI after 
termination of the index drugs can be detected. To define duration of use similarly in the 
three data sources, the carry-over period in the main analysis will also be 30 days in 
Denmark. However, in Denmark, some medications are supplied for 90 days; for this reason, 
in a sensitivity analysis, the risk/exposure window for current use starts on the date of the 
prescription and ends 90 days after the end of supply. This sensitivity assessment will allow 
exploration of any further potential delay in effect. A 90-day period was selected because this 
time is long enough to account for non-adherence and extended use of the discontinued index 
drug and a delay in effect.
Duration of exposure will be based on the duration of current use. Categories of duration will 
be defined based on available data.
Dose will be the dosage at index date. When the dose is missing, the dose will be estimated 
from the available recorded information (e.g., strength, number of units, amount of drug 
prescribed). Evaluation of different doses of empagliflozin will be performed if variation in 
the dose used by the empagliflozin cohort is observed and an adequate number of events 
occur within the different daily dose categories.

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Figure 1
Exposure Definition
Note: End of supply will be estimated according to prescription instructions in the CPRD or based on available information 
on the duration of dispensings (e.g., number of packages bought, strength, number of pills) in Denmark and the HIRD.

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9.3.2
Study outcomes
The primary outcomes of interest for this study are ALI in patients with no predisposing 
conditions, AKI, severe complications of UTI, DKA, and occurrence of GI. Secondary 
outcomes are ALI in patients with or without predisposing conditions, CKD, and severe GI.
Scarce literature exists on the validity of algorithms used to identify GI and hospitalisations 
due to severe complications of UTI or to DKA. Validation of the algorithms used to identify
cases to confirm diagnosis and date of the event will be implemented for all primary and 
secondary outcomes and for ALI and AKI non-specialist outpatient cases (CPRD, US). Each 
outcome-specific section that follows includes a case definition to be used for validation 
purposes and the algorithm of codes that will be used for case identification. The final section
describes the common validation process that will be followed for all outcomes (see 
Section 9.3.2.9).
9.3.2.1
ALI: Hospitalisation, emergency department (ED) visit, or specialist visit for ALI
in patients with no predisposing conditions, primary outcome

Outcome type: primary

Secondary outcomes within this section: yes (hospitalisation, ED visit, or specialist
visit for ALI in patients with or without predisposing conditions)

Further outcomes within this section: none

Outcome name: ALI in patients with no predisposing conditions

Time frame: up to 5 years

Safety issue: no
Acute liver injury has been defined in terms of an elevation in the serum concentration of 
ALT or AST, conjugated bilirubin, or alkaline phosphatase (ALP). It has been considered that 
elevations of ALT/AST are indicators of liver injury, whereas increases of conjugated 
bilirubin are measures of overall liver function. Liver injury alone may not lead to clinically 
significant liver damage, whereas impaired liver function is a marker of severe drug-induced 
hepatotoxicity. Thus, a combined elevation of ALT or AST and conjugated bilirubin without 
evidence of intra- or extra-biliary obstruction (i.e., no significant elevation of ALP) could be 
used to define potentially clinically significant elevations of serum liver enzyme levels
[P06-02059]. The concept of combining markers of liver injury and function evolved from 
the observation of Hyman Zimmerman [R05-1093] that “drug-induced hepatocellular 
jaundice is a serious lesion.” Zimmerman noted that the combination of pure hepatocellular 
injury (ALT elevation without much ALP elevation) and jaundice among patients with 
drug-induced liver injury had a poor prognosis, with a mortality of 10% to 15% [R14-5256, 
R05-1093, P14-17375, P09-12413]. This observation is referred to as “Hy’s Law” by the 
FDA and has been used by the FDA over the years to assess the potential for a drug to cause 
severe liver injury—that is, irreversible liver failure that is fatal or requires liver 
transplantation [P09-12413, P14-17375, R14-5256].

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According to the international Expert Working Group on drug-induced liver injury 
[R14-1933], ALI is defined as abnormal liver function test as summarised in Table 3.
According to the Working Group, persistent drug-induced liver injury is defined as evidence 
of continued liver injury more than 3 months after hepatocellular or mixed liver injury and 
more than 6 months after cholestatic liver injury; increases of these parameters for more than 
1 year are compatible with chronic liver injury.
Table 3
Clinical criteria for “severe” or “clinically significant” acute liver injury
Endpoint
Definition
Clinically 
significant ALI1
All the following criteria2:

ALT or AST ≥5 × ULN,
or

ALT or AST ≥3 × ULN and total bilirubin ≥2 × ULN,
or

ALP ≥2 × ULN
ALI = acute liver injury; ALP = alkaline phosphatase; ALT = alanine aminotransferase; AST = aspartate aminotransferase; 
ULN = upper limit of normal range.
1.
Sources: Aithal et al. (2011) [R14-1933].
2.
For the secondary endpoint, where patients with predisposing conditions are also included, if a patient has previous 
liver disease, ULN is replaced by the mean baseline values obtained before exposure to the suspect drug, and the 
changes should be proportionate to this modified baseline (i.e., 5 x baseline for ALT, 2 x baseline for ALP, and 2 x
baseline for total bilirubin with associated 3 x baseline elevation in ALT).
9.3.2.1.1
Validation case definition
In this study, a case of ALI is defined as any person with a recorded diagnosis compatible 
with “severe” or “clinically significant” ALI who meets the criteria recommended by the 
international Expert Working Group on drug-induced liver injury [R14-1933] (Table 3).
In addition, among those ALI cases identified through diagnosis codes and that will undergo 
validation, the number of cases that had elevated liver enzymes ALT and/or AST ≥3 x ULN 
but < 5 ULN and therefore did not fulfil the Aithal et al. criteria [R14-1933] will also be 
described.
9.3.2.1.2
Case identification
Potential cases of liver injury will be identified by the following process:

In the CPRD, potential cases will be identified through primary care codes (currently 
Read codes but may also be SNOMED codes and local EMIS codes in the future) and 
liver function test results associated with codes for hospitalisation, ED visit, or 
specialist visit. In HES data, potential cases will be identified through hospital 
discharge ICD-10 codes suggestive of ALI. No ED visit information is available in 
HES; ED visits will be identified from the CPRD primary care records.

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
In Denmark, potential cases will be identified through hospital discharge ICD-10 
codes, ED visit ICD-10 codes, or hospital outpatient clinic ICD-10 codes suggestive 
of ALI.

In the HIRD, potential cases will be identified through hospital claims, ED visit 
claims, or specialist claims with an ICD-10-CM code and/or laboratory results 
suggestive of ALI.
Annex 4 contains a preliminary list of ICD-10 codes suggestive of ALI (Annex 4 Table 1).
For the assessment of this primary outcome, predisposing exclusion criteria will be applied to 
the cohorts as described in Section 9.2.8.1. Follow-up will be censored at the occurrence of 
any exclusion criteria for this cohort, e.g., any predisposing condition such as chronic liver
disease, as described in Section 9.2.9.

ALI sensitivity, all cases: a sensitivity analysis will be performed, also including 
outpatient cases of ALI in the data sources where primary care data are available (the 
CPRD and HIRD). The exclusion and censoring conditions will be the same as for the 
primary outcome.

ALI sensitivity, based on results from validation: another sensitivity analysis will 
repeat the primary outcome analysis for ALI, including only confirmed cases; 
however, when less than 70% of the cases are validated, other methods will be 
explored, e.g., correct the IRRs for the positive predictive value (PPV) [R18-1561].
9.3.2.2
ALI: Hospitalisation, ED visit, or specialist visit for ALI in patients with or 
without predisposing conditions, secondary outcome

Outcome type: secondary

Secondary outcome: none

Further outcomes within this section: none

Outcome name: ALI in patients with or without predisposing conditions

Time frame: up to 5 years

Safety issue: no
For the assessment of this secondary outcome, ALI in the 6 months before or at the index 
date and pregnancy at the index date will be used, and exclusion criteria will be those
described in Section 9.2.8.1. Follow-up will be censored by the occurrence of the outcome 
(ALI) or any exclusion criteria applied to the selection of this cohort, such as pregnancy 
exclusion criteria, but not by the occurrence of an exclusion criterion used for the primary 
outcome, e.g., any predisposing condition such as chronic liver disease, as described in 
Section 9.2.9.
9.3.2.3
Hospitalisation, ED visit, or specialist visit for AKI, primary outcome

Outcome type: primary

Secondary outcomes within this section: Yes (CKD)

Further outcomes within this section: none

Outcome name: AKI

Time frame: up to 5 years

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
Safety issue: no
Multiple definitions of AKI have been used in clinical practice and research.

In 2002, an international consensus conference of the Acute Dialysis Quality Initiative 
(ADQI) proposed the RIFLE criteria for defining and classifying AKI [R14-5242].
The RIFLE acronym indicates Risk of renal dysfunction, Injury to the kidney, Failure 
of kidney function, Loss of kidney function, and End-stage kidney disease. The 
RIFLE criteria are based on three levels of renal dysfunction (risk, injury, and failure) 
and two clinical outcomes (loss of function and end-stage renal disease). The RIFLE 
classification includes separate criteria for serum creatinine, glomerular filtration rate 
(GFR), and urine output. The serum creatinine (SCr) and GFR criteria are based on 
changes from baseline values. An increase of 1.5 times the baseline SCr indicates risk 
of kidney dysfunction, 2 times the baseline SCr indicates injury to the kidney, and 
3 times the baseline SCr indicates failure of kidney function. A decrease of > 25% to 
≤50% of the baseline GFR indicates risk of kidney dysfunction, a decrease of > 50% 
and ≤75% of the baseline indicates injury to the kidney, and a decrease of > 75% of 
the baseline indicates failure of kidney function.

According to the most recent Kidney Disease: Improving Global Outcomes (KDIGO)
guideline on AKI [R13-4387], AKI is defined as any of the following (Not Graded): 
an increase in SCr of by ≥0.3 mg/dL (≥26.5 µmol/l) within 48 hours; or an increase 
in SCr to ≥1.5 times baseline, which is known or presumed to have occurred within 
the prior 7 days; or a urine volume < 0.5 mL/kg/h for 6 hours.
The definition of AKI in epidemiologic studies has been based on absolute increases of serum 
creatinine from normal values (1.7 or 2 times the ULN) or changes from baseline (20% to 
50%) or both [P02-05226, P05-04032, P14-17372, P14-17376, P14-17377].
9.3.2.3.1
Validation case definition
In this study, a case of AKI is defined as any person with AKI according to the following 
criteria:

At least a 2-fold increase in serum creatinine from the lowest baseline value recorded 
at any time before or at the index date, and the value is above the ULN; or

An increase in serum creatinine to at least 2 times the ULN in the absence of a 
recorded baseline value; and

Absence of a recorded diagnosis of chronic renal failure (defined as CKD stage 3 or 
higher) at any time before or at the index date.
9.3.2.3.2
Case identification
Potential cases of hospitalisation, ED visit, or specialist visit for AKI will be identified by the 
following procedure:

In the CPRD, potential cases will be identified using primary care codes suggestive of 
AKI and associated with codes for hospitalisation, ED visit, or specialist visit. In the 

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HES, potential cases will be identified through hospital discharge ICD-10 codes
suggestive of AKI. No ED visit information is available in the HES; ED visits will be 
identified from the CPRD primary care records.

In Denmark, potential cases will be identified through hospital discharge ICD-10 
codes, ED visit ICD-10 codes, or hospital outpatient clinic ICD-10 codes suggestive 
of AKI.

In the HIRD, potential cases will be identified through hospital claims, ED visit 
claims, or specialist claims with an ICD-10 code or laboratory results suggestive of 
AKI.
Preliminary lists of ICD-10 codes are presented in Annex 4 Table 3. For the assessment of 
this AKI primary outcome, CKD exclusion criteria will be applied to the cohort as described 
in Section 9.7.2.1. Follow-up will be censored at the occurrence of a code for CKD as 
described in Section 9.2.9.

AKI sensitivity, all cases: a sensitivity analysis will be performed, also including 
outpatient cases of AKI, in the data sources where primary care data are available 
(CPRD and HIRD). The exclusion and censoring conditions will be the same as for 
the primary outcome.

AKI sensitivity, based on results from validation: another sensitivity analysis will 
repeat the primary outcome analysis for AKI, including only confirmed cases; 
however, when less than 70% of the cases are validated, other methods will be 
explored, e.g., correct the IRRs for the PPV [R18-1561].
9.3.2.4
Chronic kidney disease (inpatient and outpatient), secondary outcome

Outcome type: secondary

Secondary outcome: none

Further outcomes within this section: none

Outcome name: CKD

Time frame: up to 5 years

Safety issue: no
CKD will be defined based on the estimated glomerular filtration rate (eGFR), as calculated 
using the 2009 CKD-EPI equation as described below [R13-4387; R12-1392; R15-5270].
141 × min(SCr/k, 1)α × max(SCr/k, 1)-1.209 × 0.993Age [× 1.018 if female] [× 1.159 if 
black]
SCr is serum creatinine (in mg/dL), k is 0.7 for females and 0.9 for males, α is −0.329 for 
females and −0.411 for males, min is the minimum of SCr/k or 1, and max is the maximum 
of SCr/k or 1. As race is not available for all patients in CPRD, the race coefficient will not 
be applied if race is missing; this may result in underestimation of eGFR in black patients.
CKD will be differentiated from AKI by requesting confirmation of the first abnormal test 
result.

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9.3.2.4.1
Validation case definition
In this study, a case of CKD is defined as any person meeting the following criteria after the 
index date:

Estimated GFR < 60 mL/min/1.73 m2
AND

Estimated GFR < 60 mL/min/1.73 m2 is confirmed in a separate test result performed 
at least 3 months after the initial post-index date at which the abnormal result was 
identified.
AND

Absence of a recorded diagnosis of CKD or an estimated GFR < 60 mL/min/1.73 m2
at any time before or at the index date.
9.3.2.4.2
Case identification
Potential cases of CKD will be identified by diagnosis codes suggestive of CKD (CKD 
stage 3 or higher). In the CPRD, potential cases will be identified using any primary care
codes suggestive of CKD, irrespective of whether these are associated with a specialist visit,
referral, hospitalisation, or ED visit [R15-3136]. In the HES, potential cases will be identified 
through hospital discharge ICD-10 codes suggestive of CKD [R15-3138]. Preliminary lists of 
codes are presented in Annex 4 Table 5 (ICD-10 codes). All codes selected and displayed in 
the tables had PPVs larger than 70% [R15-3136, R15-3138].
9.3.2.5
Severe complications of UTI (inpatient and outpatient pyelonephritis and 
urosepsis), primary outcome

Outcome type: primary

Secondary outcome within this section: No

Further outcomes within this section: none

Outcome name: severe complications of UTI

Time frame: up to 5 years

Safety issue: no
9.3.2.5.1
Validation case definition
To define pyelonephritis, the criteria established by Patkar et al. (2009) [R14-5253] will be 
used.
1. At least two of the following will have to be present:

History of fever or documented fever > 38.0°C or 104.0°F

Dysuric complaints

Flank pain/costovertebral angle tenderness

Leukocytosis (white blood cell count > 12,000/cubic mm)

Abnormal urine (cloudy, frank pus or blood in urine, foul smell)
AND (2 OR 3)
2. Any one of the following:

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
Computed tomography, magnetic resonance imaging, or ultrasonography
findings consistent with renal inflammation

Computed tomography, magnetic resonance imaging, or ultrasonography
findings consistent with renal abscess

Computed tomography, magnetic resonance imaging, or ultrasonography
findings consistent with hydronephrosis
OR
3. Any one of the following:

Blood cultures and urine cultures positive for the same organism

Blood cultures positive for Gram-negative organisms, Enterococcus species, or
Staphylococcus saprophyticus

Urine culture positive for more than 105 Gram-negative organisms
(e.g., Escherichia coli), Enterococcus species, or S. saprophyticus

Urine culture positive for fewer than 105 of any organism AND patient treated
for at least 7 days with antibiotics
Urosepsis is clinically defined as sepsis caused by infection of the urinary tract and/or male 
genital organs (e.g., prostate). Patients are affected by microorganisms capable of inducing 
inflammation within the urinary and male genital tract. The following criteria from 
Wagenlehner et al. (2008) [R14-5286] need to be met for the diagnosis of urosepsis:
1. Diagnosis of infection of the urinary tract
AND
2. One of the following criteria:

Proof of bacteraemia

Clinical suspicion of sepsis
AND
3. Two or more of following, which indicate the presence of systemic inflammatory
response syndrome (SIRS):

Body temperature ≥38°C or ≤36°C

Tachycardia (≥90 beats per minute)

Tachypnoea (≥20 breaths per minute)

Respiratory alkalosis (PaCO2 ≤32 mm Hg)*

Leucocytes ≥12,000 per μL or ≤4,000 per μL or band forms > 10%
The case definition allows a patient to meet the criteria for both pyelonephritis and urosepsis,
but the case will be counted only once for analysis purposes.
*PaCO2 = partial pressure of carbon dioxide.

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9.3.2.5.2
Case identification
The outcome severe complications of UTI comprises any of the following conditions:

Hospitalisation, ED visit (as recorded in the CPRD primary care database), or a GP 
record for pyelonephritis (ICD-10 codes in Annex 4 Table 7)

Hospitalisation, or ED (as recorded in the CPRD primary care database), or outpatient
visit for urosepsis. Combination of diagnosis code for UTI and a diagnosis code for 
sepsis within 1 week (ICD-10 codes for sepsis in Annex 4 Table 7; ICD-10 codes for 
UTI in Annex 4 Table 9).
9.3.2.6
Genital infections (inpatient and outpatient), primary outcome

Outcome type: primary

Secondary outcome: severe GI

Further outcomes within this section: none

Outcome name: GI

Time frame: up to 5 years

Safety Issue: yes
Diabetes is a risk factor for vaginal infections and balanitis, especially those produced by 
Candida species, with studies suggesting that the rate of vulvovaginal candidiasis and 
balanitis is higher among patients with diabetes [R14-5237, R12-3639, R12-2432, R14-5260,
R14-5243].
This study will include only non-sexually transmitted GI. For women, bacterial vaginosis and 
vulvovaginal candidiasis will be included. For men, only non-sexually transmitted cases of 
balanitis will be included, which comprise Candida balanitis and aerobic balanitis.
Clinical diagnosis of bacterial vaginosis is presumptive and based on the presence of typical 
symptoms of vulvovaginitis, elevated pH (> 4.7 or > 4.5), and the presence of clue cells in 
saline wet mount or Gram stain of vaginal discharge. Diagnosis is enhanced by fishy odour of 
vaginal discharge after addition of 1-2 drops of 10% potassium hydroxide. Cultures are not 
useful. Gardnerella vaginalis is commonly found in women with bacterial vaginosis. Other 
organisms associated with bacterial vaginosis include Prevotella species, Mycoplasma 
hominis, and Mobiluncus species [R14-5247, R14-5252].
Clinical diagnosis of vulvovaginal candidiasis is presumptive if there are typical symptoms of 
vulvovaginitis and microscopic identification of yeast forms or hyphae in Gram stain or 
potassium hydroxide wet mount preparations of vaginal discharge. Diagnosis is definitive by 
positive culture for C. albicans (or other Candida species) in symptomatic women
[R14-5247, R14-5252].
Balanitis is defined as an inflammation of the penis that often involves the prepuce 
(balanoposthitis). Clinical diagnosis of balanitis is established based on clinical symptoms 
followed by culture confirmation; in the case of Candida balanitis, the isolation of yeast is 

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definitive proof of fungal infection. There is a wide variety of causes and predisposing factors 
such as not being circumcised, neutropenia, or diabetes [R14-5248, R14-5243]. Balanitis can 
be due to several microorganisms, but Candida is the most common organism in patients 
with diabetes [R12-3639].
Non-sexually transmitted balanitis may also be caused by anaerobic and aerobic organisms, 
(such as Gardnerella vaginalis and Group B Streptococcus). Typical symptoms of Candida 
balanitis include burning and itching of the penis with generalised erythaema of the glans 
and/or prepuce (which may have a dry, glazed appearance) and with erosions, papules, and
white discharge. In patients with diabetes, the presentation may be more severe, with oedema 
and fissuring of the foreskin, which may become non-retractile. Symptoms of Gardnerella
balanitis are milder and include irritation of the prepuce and glans penis, macular erythaema,
and fishy subpreputial discharge. Symptoms of balanitis due to Group B Streptococcus
include non-specific erythaema with or without exudate [R14-5243].
9.3.2.6.1
Validation case definition
Vulvovaginitis: all potential cases (outpatient and inpatient) of non-sexually transmitted 
vulvovaginitis will be included in the study and classified as vulvovaginal candidiasis,
bacterial vaginosis, or non-specific vulvovaginitis or vulvitis.
Based on the clinical diagnosis mentioned above [R14-5247], either of the following criteria 
will need to be met for the diagnosis of vulvovaginal candidiasis:
1. A specific diagnosis of vulvovaginitis due to Candida AND any of the following
a.
Treatment with antifungals
b.
Yeast in Gram stain
c.
Culture positive for Candida
2. Non-specific diagnosis of vulvovaginitis OR symptoms of vulvovaginitis AND two or 
more of the following:
a.
Treatment with antifungals
b.
Yeast in Gram stain
c.
Culture positive for Candida
Based on the clinical diagnosis mentioned above [R14-5247], either of the following criteria 
will need to be met for the diagnosis of bacterial vaginosis:
1. A specific diagnosis of vulvovaginitis due to bacterial vaginosis AND any of the 
following:
a.
Treatment with metronidazole
b.
Clue cells in saline wet mount or Gram stain
c.
Culture positive for Gardnerella
d.
pH > 4.7
2. Non-specific diagnosis of vulvovaginitis OR symptoms of vulvovaginitis AND two or 
more of the following:
a.
Treatment with metronidazole

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b.
Clue cells in saline wet mount or Gram stain
c.
Culture positive for Gardnerella
d.
pH > 4.7
Cases with diagnosis or symptoms of vulvovaginitis or vulvitis that do not fulfil the above 
criteria will be classified as “non-specific vulvovaginitis or vulvitis” or excluded from the 
analysis if the event is suggestive of an alternative diagnosis such as a sexually transmitted
GI.
Balanitis: all potential cases of non-sexually transmitted balanitis (outpatient and 
hospitalised) will be included in the study and classified as Candida balanitis, aerobic 
balanitis, or non-specific balanitis.
Based on the clinical diagnosis mentioned above [R14-5247], either of the following criteria 
will need to be met for the diagnosis of Candida balanitis:
1. A specific diagnosis of balanitis due to Candida AND any of the following:
a.
Treatment with antifungals
b.
Yeast in Gram stain
c.
Culture positive for Candida
2. (Non-specific diagnosis of balanitis OR symptoms of balanitis) AND two or more of 
the following:
a.
Treatment with antifungals
b.
Yeast in Gram stain
c.
Culture positive for Candida
Based on the clinical diagnosis mentioned above [R14-5247], either of the following criteria 
will need to be met for the diagnosis of aerobic balanitis:
1. Non-specific diagnosis of balanitis AND culture positive for a non-sexually 
transmitted microorganism such as Gardnerella or Group B Streptococcus.
2. Symptoms of balanitis AND culture positive for a non-sexually transmitted 
microorganism such as Gardnerella or Group B Streptococcus.
Cases with diagnosis or symptoms of balanitis that do not fulfil the above criteria will be 
classified as “non-specific balanitis” or excluded from the analysis if the event is suggestive 
of an alternative diagnosis such as a sexually transmitted GI.
9.3.2.6.2
Case identification
Vulvovaginitis: potential cases of vulvovaginitis will be identified by the presence of an 
outpatient diagnosis or a hospitalisation or ED visit (as recorded in the CPRD primary care 
database) for vulvovaginitis, specifically, codes for specific diagnosis of bacterial vaginosis 
or vulvovaginal candidiasis, codes for non-specific diagnosis of vulvovaginitis, codes for 
specific microbiology results for Candida or Gardnerella, or diagnosis codes for non-specific
positive microbiology results (see ICD-10 codes in Annex 4 Table 11, and Read codes in

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Annex 4 Table 12). Cases will be excluded if there is a diagnosis code with a specific 
diagnosis for a sexually transmitted infection within 30 days before or after the index 
infection date (see Annex 4 Table 13).
Balanitis: potential cases of balanitis will be identified by the presence of an outpatient 
diagnosis of or a hospitalisation or ED visit (as recorded in the CPRD primary care database) 
for balanitis, including Candida balanitis, aerobic balanitis, and non-specific balanitis (see 
ICD-10 codes in Annex 4 Table 11, and Read codes in Annex 4 Table 14). Cases will be 
excluded if there is a diagnosis code with a specific diagnosis for a sexually transmitted 
infection within 30 days before or after the index infection date (Annex 4 Table 15).
9.3.2.7
Severe genital infections: secondary outcome

Outcome type: secondary

Secondary outcome: none

Further outcomes within this section: none

Outcome name: incidence of severe genital infections

Time frame: up to 5 years

Safety issue: yes
Among the cases of GI identified in the primary outcome, those that resulted in 
hospitalisation will be classified as severe GI. To ensure that GI was the reason for 
hospitalisation and not a nosocomial infection, only primary discharge diagnoses will be used 
to identify GI.
Those GIs identified through an outpatient diagnosis and that required systemic treatment 
with antifungals or antibiotics (as opposed to topical or vaginal treatment) will also be 
classified as severe GI. Systemic treatment will be considered if prescribed on the date of the 
GI diagnosis or within 30 days before or after the GI diagnosis date. The UK recommended 
systemic treatment for vulvovaginitis includes metronidazole and tinidazole for bacterial 
vaginosis and fluconazole and itraconazole for vulvovaginal candidiasis [R14-5247]. The 
systemic treatment for balanitis recommended by the European Union is fluconazole for 
Candida balanitis, erythromycin or amoxicillin/clavulanic acid for aerobic balanitis, and 
metronidazole or amoxicillin/clavulanic acid for anaerobic balanitis [R15-0067].
Complications and severe consequences of GI will be described among severe GI cases. This 
will include patients with codes such as ulcerations, abscesses, boils, or Fournier´s gangrene 
(see ICD-10 codes in Annex 4 Table 11).
9.3.2.8
Hospitalisation or ED visit for DKA: primary outcome

Outcome type: primary

Secondary outcomes within this section: no

Further outcomes within this section: none

Outcome name: incidence of DKA

Time frame: up to 5 years

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
Safety issue: no
DKA is defined by the biochemical triad of ketosis, hyperglycaemia, and acidosis. Serious 
complications of DKA and its treatment are hypokalaemia and hyperkalaemia, 
hypoglycaemia, and cerebral oedema [R16-1372, R16-1373].
9.3.2.8.1
Validation case definition
In this study, a case of DKA is defined as any person with a recorded diagnosis compatible 
with DKA who meets the following criteria recommended by the Joint British Diabetes 
Societies [R16-1372] and the American Diabetes Association [R16-1371, R15-2058]:

Ketonaemia > 1.5 mmol⁄L or ketonuria (+)

pH less than 7.3. In the absence of pH values: anion gap > 10 mEq/L or venous 
bicarbonate (HCO3) below 15 mmol⁄L
Although blood glucose levels are usually a parameter used to define DKA, this criterion will 
not be used because atypical DKA can occur among users of SGLT2 inhibitors, including 
empagliflozin.
In this study, cases of DKA will include only patients requiring hospitalisation for DKA
because some authorities contended that true DKA will always require hospitalisation or ED
admission for treatment; otherwise, this study would include patients with milder forms of 
ketosis and unconfirmed DKA events [R16-1371, R16-1372].
9.3.2.8.2
Case identification
The outcome “hospitalisation due to DKA” comprises hospitalisation, ED visit, or a GP 
record of hospitalisation or referral to hospitalisation for DKA. Potential cases of DKA will 
be identified by diagnosis codes suggestive of DKA.

In the CPRD, potential cases will be identified using primary care codes and 
biochemistry test results, together with codes for hospitalisation or ED visit. In HES 
data, potential cases will be identified through hospital discharge ICD-10 codes in the 
primary or secondary discharge position. No ED visit information is available in the 
HES; ED visits will be identified from the CPRD primary care records.

In Denmark, potential cases will be identified through hospital discharge ICD-10 
codes or ED visit ICD-10 codes suggestive of DKA.

In the HIRD, potential cases will be identified through hospital claims, or ED visit 
claims with an ICD-10 code suggestive of DKA.
Preliminary list of ICD-10 codes for DKA are available in Annex 4 Table 16.

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9.3.2.9
Case validation process
The goal of case validation is to validate the algorithm used to identify the outcomes of 
interest. The target is a random sample of 100 cases each of the primary and secondary
outcomes that will be validated in each data source where the outcome is being evaluated. In 
addition, a random sample of 100 outpatient or primary care cases of ALI and AKI will also 
be validated in the CPRD and HIRD.
Validation will be performed through general practitioner questionnaires in the CPRD and 
through medical record data abstraction in Denmark and the HIRD. The relevant clinical 
information from these sources will be abstracted using a standardised abstraction form. Final 
confirmation of cases will be conducted independently by medical epidemiologists who will 
be blinded to medication exposure. Difficult cases will be evaluated by consensus between 
the validation physicians.
For all outcomes, all cases (whether or not they have been selected for the validation process) 
will be included in the analysis. However, the PPV estimates available from the validation 
will help during interpretation of the results. A sensitivity analysis is planned for the 
validated outcomes that will repeat the primary analysis, including only confirmed cases; 
however, when less than 70% of the cases are validated, other methods will be explored, 
e.g., correct the IRRs for the PPV [R18-1561].
9.3.3
Covariates
Exclusion diagnoses will be identified based on recorded GP diagnoses or hospital outpatient 
or inpatient diagnoses during the lookback period. Definitions of specific variables will be 
adapted to the type and availability of data in each data source.
Variables potentially associated with the outcomes of interest—such as sociodemographic 
variables including age, sex, socioeconomic status or urban/rural area of residence in the 
HIRD, BMI, smoking or alcohol consumption, concomitant medications, comorbidities, 
Deyo-Charlson Comorbidity Index, health care utilisation, and duration of lookback period 
(see Annex 5)—will be identified for all cohort members before or at the index date, when 
available. Severity of T2D will be assessed by HbA1c values, diagnosis codes, and duration 
since the first diagnosis, when available. These and other variables that can differ by 
exposure group will be considered for inclusion as predictors in the logistic regression 
models used to generate the propensity scores. Propensity scores will be used in the analysis 
to quantify the probability of receiving empagliflozin at the index date for new users of 
empagliflozin or DPP-4 inhibitors.
At the index date, cohort members will also be classified by indicator variables on the 
calendar year at the index date, whether the index treatment (empagliflozin or DPP-4
inhibitor) was added to existing medication (adding on) or initiated as a replacement for 
another GLD (switching from the existing GLD to empagliflozin or DPP-4 inhibitor), and 
whether this treatment was received as monotherapy or as dual or triple therapy. A variable 
indicating whether or not patients were receiving insulin at the index date will also be 

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created. At the index date, patients will be classified as “adding on” or “switched to”
empagliflozin or DPP-4 inhibitor based on whether at least one prescription/dispensing of the 
previous GLD treatment recorded in the 3 months before or at the index date is also recorded 
within 3 months after the index date.
The approaches to handling concomitant GLDs (including oral and injectable treatments such 
as insulin) in the analyses are summarised in Table 4.
Table 4
Approaches to handling concomitant glucose-lowering drugs
Timing and Type of GLD Prescription
Analysis Approach
At the index date, any GLD taken during 
baseline that is not the new prescription and is 
not eligible to be a study exposure
Include in propensity score
At the index date, any drug combination that 
includes the study drugs and metformin 
(i.e., empagliflozin plus metformin or a DPP-4 
inhibitor plus metformin)
Include in propensity score and conduct 
additional stratified analyses by metformin 
use at index date (Yes or No)
Designation whether the GLD initiated at the 
index date is an add-on to current medication 
or a switch to a different medication
Include in propensity score
Designation whether the GLD initiated at the 
index date is a first-, second-, or third-line 
therapy
Include in propensity score
Insulin use at the index date
Include in propensity score and conduct 
additional stratified analyses by insulin use at 
index date (Yes or No)
GLD = glucose-lowering drug.
9.3.3.1
Description of cases of elevated liver enzymes
In addition to the evaluation of the ALI endpoint, this study will describe patients with 
elevated liver enzymes irrespective of whether the patients had a diagnosis or symptom code 
suggestive of ALI. Cases of elevated liver enzymes will be classified in the following 
categories:

ALT and/or AST ≥3 × ULN

ALT and/or AST ≥5 × ULN

ALT and/or AST ≥10 × ULN

ALT and/or AST ≥20 × ULN
Availability of laboratory data and identification of patients with cases of increase of liver 
enzymes varies by data source, as follows:

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
In the CPRD, patients with elevated liver enzymes will be identified using outpatient 
laboratory results available in the CPRD primary databases.

In Denmark, patients with elevated liver enzymes can be identified through linkage 
with the clinical laboratory information system databases, where data from all 
hospital-based laboratory tests performed during inpatient stays and outpatient 
hospital visits can be accessed electronically. In addition, if a GP sends samples to 
hospital-based laboratories, the result of the test will be recorded and available even if 
a patient is seen outside the hospital. For the period 2000-2015, linkage with the 
laboratory database is currently possible in the Central Region of Denmark, which 
corresponds to 23% of the total Danish population. On a nationwide level, laboratory 
data for all 5.77 million Danish inhabitants have recently become available for 
research in the new nationwide Register of Laboratory Results for Research (LAB_F), 
tracking all laboratory test results from both primary and secondary care, with 
complete data coverage beginning in 2015 at the Danish Board of Health [R19-1785]. 
Therefore, identification of cases of ALT and/or AST ≥3 × ULN will be possible in 
Denmark for the Central Denmark region (1.30 million people) since approximately
the year 2000 and for all of Denmark (5.77 million people) since approximately the 
year 2015 [R18-3665]. It is still unclear if it will be possible for researchers to retrieve 
individual person-identifiable laboratory data for the entire country of Denmark for 
local validation purposes, e.g., through medical records, because nationwide research 
data at the Danish Board of Health are normally de-identified.

In the HIRD, cases of elevated liver enzymes will be identified using information 
from outpatient laboratory test results available electronically for 30% of the patients 
in the HIRD.
The number and proportion of patients with elevated liver enzymes identified in each data 
source will be described overall and stratified by age and sex, by treatment group, and by 
prior history of predisposing conditions.
9.4
DATA SOURCES
Protocol version 4.0 included the CPRD data source in the UK. A feasibility assessment of 
several data sources based on actual and projected user counts, type and availability of data, 
and possibility of validation, revealed that the most efficient approach to increase study size 
was to include the Danish Population Registries and the HIRD in the US in the study
(Annex 1).
9.4.1
Clinical Practice Research Datalink (CPRD)–UK
Ideally, the proposed study design requires data sources that longitudinally capture inpatient
and ED (and outpatient for some of the outcomes) diagnoses and procedures; capture 
prescription information; and allow validation of the outcomes of interest. A data source 
meeting all those study requirements is the UK CPRD (website: cprd.com), which is 
proposed as the study data source.

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In the UK, nearly all residents are registered in a general medical practice that uses electronic 
medical records. Some of those records are available for research purposes in the CPRD. The 
CPRD contains diagnostic and prescribing information recorded by GPs as part of their 
routine clinical practice in the UK. The CPRD primary care data are divided into two 
databases (CPRD GOLD and CPRD Aurum) that differ in the electronic patient record 
system software. CPRD GOLD uses the VISION software and was the only software
available until recently. Since 2016-2017, primary care practices across the UK are
progressively switching to the Egton Medical Information Systems electronic patient record 
system (EMIS-Web) software, and data from these practices are now collected into CPRD
Aurum. Both databases, i.e., CPRD GOLD and CPRD Aurum, will be used for this study.
As of April 2019, CPRD GOLD contains data for over 16.7 million patients, with research-
quality data from 790 UK practices; 2.6 million of these patients are active (still registered 
with one of the 296 contributing GP practices) [R19-1781]. As of April 2019, CPRD Aurum 
contains data for approximately 22.7 million patients, with research-quality data from 873 GP 
practices in England; 7.3 million of these patients are active (registered with one of the 754 
contributing GP practices). No data on practices from Scotland, Wales, or Northern Ireland 
are available in CPRD Aurum [R19-1782]. It is possible that patients in practices that 
switched from CPRD GOLD to CPRD Aurum may have contributed to both databases. Based 
on the monitoring of users, between 1% and 2% of the users of empagliflozin who are in 
CPRD GOLD are also in CPRD Aurum. Duplicate practices can be identified [R18-0349], 
and patients will be removed from CPRD GOLD because when patients switch from CPRD 
GOLD to CPRD Aurum, validation is possible only in CPRD Aurum. Patients registered in 
CPRD GOLD and CPRD Aurum are representative of the whole UK population in terms of 
age and sex. A large proportion of patients are linkable to central mortality records.
A large and growing proportion of patients can also be linked to hospitalisation records
(hospital discharge diagnoses and procedures are coded using ICD-10 codes in the HES) and 
to death registration data records from the Office for National Statistics (ONS). Linkage is 
done via the patient’s National Health Service number, sex, date of birth, and postal code. 
Updated, valid, linked CPRD data are available through the CPRD Division of the UK 
Medicines and Health Care Products Regulatory Agency. The HES data set to be used is HES 
Admitted Patient Care (APC), which includes information on admissions (including day 
cases) to English NHS health care providers, with admission and discharge dates, diagnoses, 
specialists seen, and procedures undertaken (using OPCS codes). Although a HES Accident 
and Emergency (A&E) linkage database exists and includes individual records of patient care 
administered in accident and emergency settings at English NHS health care providers and 
treatment centres, it is not used because data coverage is incomplete in comparison with
national A&E data attendances. For this study, information on ED visits will come from 
CPRD primary care records, which can be in the form of referrals to A&E or other 
administrative codes indicating that a diagnosis is related to an ED visit.
CPRD GOLD linkage of data to HES and ONS covers approximately 75% of practices 
contributing to CPRD GOLD in England and approximately 54% of practices contributing to 
CPRD GOLD in the UK. Within the participating practices, 88% of research-quality 

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(acceptable) patients have the necessary data to allow linkage to HES and ONS and have not 
dissented from disclosure of personal confidential data to NHS Digital [R19-1734].
CPRD Aurum linkage of data to HES and ONS covers 93% of all CPRD Aurum practices 
available in the June 2018 build, all of which are in England. The large volume of data that 
the CPRD are incrementally onboarding from CPRD Aurum practices means that additional 
practices will be added over subsequent linkage sets [R19-1734].
Detailed information on prescriptions written by GPs, including prescribed dose and duration, 
is routinely recorded in the data source. Read codes are used for diagnoses in CPRD GOLD 
and CPRD Aurum, and SNOMED codes and EMIS local codes are also used in CPRD 
Aurum for diagnoses. Gemscript codes are used for medications in CPRD GOLD, and 
medications are coded using the Dictionary of Medicines and Devices (DM+D) in CPRD 
Aurum. Additional diagnostic and treatment information can be found in letters from 
specialists and hospitals, and other sources. Because GPs serve as the gatekeepers for all 
medical services, any visit to a specialist or hospital requires communication back to the GP, 
who might enter that information into the medical record.
CPRD GOLD and CPRD Aurum contain information on lifestyle factors with a variable 
proportion of missing values. Although information on race is not available, other user 
characteristics of interest are likely to be captured. For example, data on body weight and 
height, smoking, and alcohol use were available for approximately 70% of patients in the 
CPRD [R14-5279]. In contrast, the pharmaceutical exposures and comorbidities are expected 
to be based on outpatient prescriptions and to be complete. The diagnosis of T2D, after 
excluding individuals with diagnosis codes for T1D, has been validated in the CPRD and 
found to have a high PPV: 98.6% [R14-5280].
The number of practices contributing to the CPRD GOLD database is decreasing, and the 
number of practices contributing to the CPRD Aurum database is increasing. The flow of 
patients between CPRD GOLD and CPRD Aurum is not clearly understood at this stage and 
will be monitored closely. The number of empagliflozin users in CPRD Aurum was low as of 
December 2017, but monitoring of users shows a rapid increase in the number of 
empagliflozin users in CPRD Aurum, with a total of 17,650 users between August 2014 and 
31 March 2019. Monitoring of empagliflozin users in CPRD Aurum and CPRD GOLD will 
be reported in the annual progress reports.
The UK is an ideal setting for population-based studies of diabetes because diabetes care is 
largely coordinated by the GP, and metabolic parameters, cardiovascular risk factors, diabetes 
comorbidities, and disease outcomes are collected electronically. Furthermore, clinical 
guidelines in the UK facilitate consistency in patterns of care [R14-5255]. In general, the 
validity of the former General Practice Research Database, upon which the CPRD was 
founded, as a reliable data source for drug safety studies in numerous therapeutic areas is well 
established [R11-2162, R99-1044]. However, all of the outcomes of interest in this study 
have not been well validated in the CPRD. For example, the validity of the diagnosis codes 
for severe complications of UTI or pyelonephritis has not yet been determined and does not 
appear in a recent systematic review of the validated outcomes in the CPRD. For ALI and 
AKI, the PPV of the codes analysed in one study seems to be below 50% [R11-5210]. On the 

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other hand, the combined infectious and parasitic endpoints studied in the CPRD have a 
median proportion of cases confirmed of 93%; for the combined genitourinary system 
endpoints, the median proportion of cases confirmed is 91% [R11-5211].
Access to de-identified, patient-level data from the CPRD is available following approval of 
the study protocol by the Independent Scientific Advisory Committee. A more detailed 
description of data available from the CPRD is shown in Annex 6.
9.4.2
The Danish Population Registries
The Danish health care system provides universal coverage to all Danish residents 
(5.7 million inhabitants; https://www.sundhed.dk/service/english/an-ehealth-
nation/healthcare-in-dk/) [R18-0353]. Health care coverage includes visits to GPs and 
specialists, hospital admissions, and outpatient visits. The costs of medicines are partially 
covered by the Danish health system. The centralised Civil Registration System in Denmark 
allows for personal identification of each person in the entire Danish population [R16-2604]
and for the possibility of linkage to all Danish registries containing civil registration numbers, 
such as the Danish National Patient Register [R18-0262], Danish National Prescription 
Registry [R18-0263], and the clinical laboratory information system research databases 
[R18-0264]. Data collected in these registries 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 [R15-3135, R15-3137]. 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 registries and medical databases.
Three national registries—Danish National Patient Registry, Danish National Prescription 
Registry, and Danish National Database of Reimbursed Prescriptions—will be of particular 
interest. In addition, the Danish National Civil Registration System will be used to obtain 
information on death and migration status.

The Danish National Patient Register includes data on all hospital admissions since 
01 January 1977 and on outpatient clinic and ED visits since 1995 [R15-3137]. 
Hospital discharge diagnoses and information on surgical procedures, in-hospital 
deaths, and some selected drugs are recorded. After 1993, hospital discharge 
diagnoses are coded using ICD-10 codes.

The National Health Services Prescription Database (formerly known as the Danish 
National Database of Reimbursed Prescriptions) encompasses the reimbursement 
records of all reimbursed drugs sold in community pharmacies and hospital-based 
outpatient pharmacies in Denmark since 2004 [R15-3140]. On average, 

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approximately 3.5 million users are recorded in the database each year. Individuals 
are identified by the unique central personal registration (CPR) number assigned to all 
persons born in or immigrating to Denmark. This new data source avoids restrictions 
imposed on data use at the Danish National Prescription Registry. Most importantly, 
CPR numbers are reversibly encrypted, which allows re-identification of medication 
users. These features are very important for validation purposes.

Laboratory results back to 2015 have become available nationwide [R19-1785]. For a 
subpopulation of Danish drug users, i.e., inhabitants of the Central Denmark Region 
(population, 1.3 million; approximately 23% of the Danish population), acute liver 
and kidney injury outcomes can also be assessed through population-based laboratory 
databases with complete coverage back to 2000 [R18-0264, R18-067]. Thus, liver 
injury can be assessed by elevated liver enzyme values (e.g., alanine aminotransferase 
[ALT] values increasing to > 437 U/L for men older than 16 years or ALT > 282 U/L 
for others), and kidney injury through elevated serum creatinine and decreased
estimated glomerular filtration rate (eGFR) (e.g., 1.5-fold increase in serum creatinine 
from baseline or eGFR decreasing to a different kidney dysfunction severity level 
< 60 mL/min/1.73).
Identification and validation of the outcomes of interest in Denmark are summarised in
Table 5.

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Table 5
Evaluation of acute liver injury, acute kidney injury, and hospitalisation for 
diabetic ketoacidosis in the Danish Population Registries
Case ascertainment through electronic 
algorithm: information available/not 
available
Medical record abstraction: information 
available and implications for outcome 
validation

Hospital discharge ICD-10 codes are 
available for all inpatient episodes 
during the study period.

Hospital outpatient ICD-10 codes are 
available for all outpatient specialist 
visits during the study period.

Hospital procedure codes for acute 
dialysis are available to identify the 
most severe AKI cases.

Outpatient primary care diagnoses are 
not available; outpatient primary care 
cases of AKI and ALI cannot be 
identified.

Laboratory results data are available for 
patients treated in Hospitals in the 
Central Denmark Region from 2000
[R18-0264] and nationwide from 2015.

Hospital records for both outpatient 
clinic and inpatient episodes can be 
abstracted for almost 100% of all 
potential cases identified by the 
electronic algorithms.

Laboratory results from hospital 
inpatient and outpatient care and 
outpatient primary care can be 
abstracted from hospital medical 
records, when available.

No validation of outpatient primary care 
cases of ALI and AKI is possible, but 
most ALI and AKI outpatient cases are 
managed in the hospital setting.
AKI = acute kidney injury; ALI = acute liver injury; ICD-10 = International Statistical Classification of Diseases and 
Related Health Problems, 10th Revision.
A more detailed description of data available from the Danish Population Registries is shown 
in Annex 6.
9.4.3
HIRD, US
The HIRD is a large administrative health care database maintained by 
 for use in 
health outcomes and pharmacoepidemiologic research. The HIRD contains longitudinal 
medical and pharmacy claims data from health plan members across the US. The database 
represents claims information from one of the largest commercially insured populations in the 
US.
Member enrolment, medical care (professional and facility claims), outpatient prescription 
drug use, outpatient laboratory test results data available for 30% of the patients, and health 
care utilisation may be tracked for patients in the database dating back to January 2006. 
Diagnoses and procedures are identified by International Classification of Diseases, 9th 
Revision, Clinical Modification codes (ICD-9-CM), International Classification of Diseases,
10th Revision, Clinical Modification codes (ICD-10-CM); Current Procedural Terminology 
(CPT) codes, and Healthcare Common Procedure Coding System (HCPCS) codes for both 

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outpatient visits and inpatient stays. Drug claims are captured by National Drug Codes, which 
can be translated to broader categories such as Generic Product Identifier codes. Information 
on physician speciality is also available in the HIRD.
In addition, the 
 Integrated Research Environment has the ability to link claims 
data in the HIRD to complementary data sources, including inpatient and outpatient medical 
records for the health plan members represented in the HIRD; identify and contact providers 
and members for survey research through vendor relationships; and link data to national vital 
records, such as the National Death Index (NDI), for date and cause of death [R18-0256]. 
Death records are added to the NDI file annually, approximately 12 months after the end of 
the calendar year, although early release files are available with a lag of around 5 months and 
are usually more than 95% complete. Cause-of-death codes can be obtained using the NDI 
Plus service.
Using these resources, 
 conducts a range of real-world research studies, including 
retrospective database studies, medical record review studies, cross-sectional and longitudinal 
patient and provider surveys, and prospective site-based studies. This research team has a 
long experience on pharmacoepidemiology studies, including validation studies and studies 
on ALI and AKI [R18-0255, P14-10229, R18-0350].
Identification and validation of the outcomes of interest in the HIRD are summarised in
Table 6.

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Table 6
Evaluation of acute liver injury, acute kidney injury, and hospitalisation for 
diabetic ketoacidosis in the HIRD
Case ascertainment through 
electronic algorithm: information 
available/not available
Medical record abstraction: information available 
and implications for endpoint validation

Hospital discharge ICD-9 or 
ICD-10 codes (depending on 
the time period) are available
for all inpatient, outpatient, 
and primary care claims during 
the study period.

Laboratory results from large 
national reference laboratories 
from the outpatient setting and 
primary care are available 
electronically for 
approximately 30% of the 
patients.

 has permission to obtain medical 
records for a subset of patients (approximately 
50%). Redacted copies of medical records are 
typically obtained for approximately 60% of the 
patients for whom 
 has access to their 
protected health information.1

These medical records can be from any providers, 
including primary care providers, hospitals, 
emergency departments, and providers of any 
speciality care.

Diagnoses from primary care claims or any other 
outpatient or hospital setting can be validated.

Validation is performed by a trusted third party.

Outpatient laboratory results are available 
electronically for a subset of approximately 30% 
of the patients (no need to abstract outpatient 
laboratory results from medical records, although 
it is possible to access medical records for around 
15% of these patients).

When outpatient laboratory results are not 
available electronically, these can be obtained 
through abstraction of information in outpatient 
medical records, if available.

Inpatient laboratory results can be obtained 
through abstraction of information in hospital 
medical records, if available.
ICD-9 = International Classification of Diseases, 9th Revision; ICD-10 = International Statistical Classification of Diseases 
and Related Health Problems, 10th Revision.
1
 is successful in obtaining redacted copies for 60% of the patients of the ~50% of patients for whom 
 has permission to obtain medical records.
A more detailed description of data available from the HIRD is shown in Annex 6.

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9.5
STUDY SIZE
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 each 
country.
The required study size to detect an IRR of 3 among empagliflozin new users compared with 
DPP-4 inhibitor new users, with a comparator: empagliflozin ratio of 10:1 and a power of 
80%, would be between 18,300 and 30,000 person-years of empagliflozin use for liver injury, 
approximately 8,400 person-years for DKA, and 1,400 to 3,200 person-years for kidney 
injury. For all other outcomes, the number of empagliflozin new-user person-years required 
to detect an IRR of 3 would be less than 1,400 (Table 7).
As of June 2018, the actual and projected number of users of empagliflozin in CPRD GOLD, 
Denmark, and the HIRD are presented in the feasibility assessment (Annex 1). The actual 
number of users of each of the study medications in each data source suggests that the DPP-4 
inhibitor: empagliflozin ratio is likely to be 10:1 or lower. The actual and projected number of 
users of empagliflozin suggest that if the study includes CPRD GOLD, Denmark, and the 
HIRD, at the time of data extraction, there would be around 109,885 patients and 
approximately 21,978 person-years of empagliflozin exposure, which would be sufficient to 
provide a probability of 0.80 that the upper bound of the IRR for empagliflozin compared 
with DPP-4 inhibitors is less than 3 if the true IRR of ALI and DKA is 1.0, and less than 1.5 
if the true IRR of AKI is 1.0.
As of 31 March 2019, the actual number of empagliflozin users in CPRD Aurum 
(N = 17,650) is higher than the number projected in the feasibility assessment (N = 2,541
projected up to December 2019). Because CPRD Aurum now contains a larger number of 
users of empagliflozin, this database will also be included in the study to increase the study 
size and person-years of exposure in the UK. Similarly, as of 31 March 2019, the actual 
number of empagliflozin users in CPRD GOLD (N = 8,316) is also higher than the number 
projected in the feasibility assessment (N = 5,874). Of the 8,316 users in CPRD GOLD, 303
users are also in CPRD Aurum and 8,013 of users are unique to CPRD GOLD. As of 31
March 2019, the actual and projected numbers of empagliflozin users suggest that if the study 
includes CPRD GOLD, CPRD Aurum, Denmark, and the HIRD, at the time of data 
extraction, there would be approximately 151,184 patients and approximately 30,237 person-
years of empagliflozin exposure, which would be sufficient to provide a probability of 0.80 
that the upper bound of the IRR for empagliflozin compared with DPP-4 inhibitors is less 
than 3 if the true IRR of ALI is 1.0, less than 2 if the true IRR of DKA is 1.0, and less than 
1.5 if the true IRR of AKI is 1.0.

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Table 7
Number of empagliflozin-exposed person-years needed to detect an IRR of 1.5, 2, 3, or 4 with a power of 80% and 
alpha = 0.05 (using a two-sided test for the ratio of two Poisson rates)
Outcome
Background 
incidence 
rates1
Comparator:empagliflozin ratio, 10:1
Comparator:empagliflozin ratio, 20:1
IRR, 1.5
IRR, 2
IRR, 3
IRR, 4
IRR, 1.5
IRR, 2
IRR, 3
IRR, 4
ALI
0.14a
309,102 
92,008 
30,027 
16,360 
293,301 
86,858
28,101 
15,200 
0.23b
188,149 
56,005 
18,277 
9,958 
178,531 
52,870 
17,105 
9,252 
AKI
1.29c,d
33,546 
9,985 
3,259 
1,776 
31,831 
9,427 
3,050 
1,650 
1.98c
21,856 
6,506 
2,123 
1,157 
20,739 
6,142 
1,987 
1,075 
2.88e
15,026 
4,473 
1,460 
795 
14,258 
4,222 
1,366 
739 
Acute 
pyelonephritis
3f
14,425 
4,294 
1,401 
764 
13,687 
4,053 
1,311 
709 
UTI leading 
to 
hospitalisation
15.8g
2,739 
815 
266 
145 
2,599 
770 
249 
135 

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Table 7 (cont'd)
Number of empagliflozin-exposed person-years needed to detect an IRR of 1.5, 2, 3, or 4 with a power of 80% 
and alpha = 0.05 (using a two-sided test for the ratio of two Poisson rates)
Outcome
Background 
incidence 
rates1
Comparator:empagliflozin ratio, 10:1
Comparator:empagliflozin ratio, 20:1
IRR, 1.5
IRR, 2
IRR, 3
IRR, 4
IRR, 1.5
IRR, 2
IRR, 3
IRR, 4
Vaginitis2
21h
2,061 
613 
200 
109 
1,955 
579 
187 
101 
Balanitis3
8.4h
5,152 
1,534 
501 
273 
4,888 
1,448 
468 
253 
DKA in T2D
0.5i
86,549 
25,762 
8,408 
4,581
82,124 
24,320 
7,868 
4,256 
AKI = acute kidney injury; ALI = acute liver injury; DKA = diabetic ketoacidosis; IRR = incidence rate ratio; T2D = type 2 diabetes mellitus; UTI = urinary tract infection.
1
Incidence rates per 1,000 patient-years.
2
Patient-years restricted to females.
3
Patient-years restricted to males.
Sources: a Huerta et al. (2002) [P03-03701]; b El-Serag and Everhart [R12-3632]; Girman et al. (2012) [R11-5319]; d Estimate calculated as the 65% of the incidence reported by 
the study, 2 per 1,000 person-years. Only 65% of those were based on hospital records; e Waikar et al. (2006) [R14-5285] (the results reported are on patients without T2D); 
f Venmans et al. (2009) [R12-1105]; g Benfield et al. (2007) [R12-1080]; h Hirji et al. (2012) [R12-3639]; i Wang et al. (2008) [R14-3272].

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9.6
DATA MANAGEMENT
All conversion of the original data to analysis variables will be performed using SAS 
software version 9.2 or higher (
). Data management
for CPRD data will be carried out in accordance with RTI Health Solutions (RTI-HS)
standard operating procedures. Routine procedures include checking electronic files, 
maintaining security and data confidentiality, following the statistical epidemiological 
analysis plan, and performing quality-control checks of all programmes.
Security processes 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. Appropriate data storage and archiving procedures will be followed 
(i.e., storage on CD-ROM and DVD), with periodic backup of files to tape. A more complete 
description of the data management procedures will be included in the statistical 
epidemiological analysis plan.
9.7
DATA ANALYSIS
The final approach to data analysis will be presented in a separate statistical epidemiological 
analysis plan, to be developed before data collection.
9.7.1
Propensity score approach
Decisions to begin a specific GLD are influenced by demographic, medical, and clinical 
factors, and those same factors might be associated with the outcomes of interest. In the 
context of this study where the expected number of patients meeting the case definition is 
small for some of the outcomes (e.g., ALI), the number of covariates that can be used in a 
regression model predicting those outcomes is limited [R08-1486, R08-1494]. To overcome 
this problem, the set of confounding variables will be summarised into a single summary 
confounder score, a propensity score. The propensity score is the predicted probability of 
being assigned to a particular treatment conditional on a set of observed covariates. Because 
the models predict not the probability of experiencing the outcome but the probability of 
being treated with empagliflozin in this study, many more variables can be used in the 
predicting regression model [P12-04844, R14-5241, R14-5284, R14-5389]. Propensity scores 
for the comparison of empagliflozin vs. DPP-4 inhibitors will be generated. Furthermore, 
given the different inclusion/exclusion criteria used for each of the outcomes, the propensity 
scores will be cohort specific to the outcome being analysed (i.e., propensity scores will be 
calculated for only those patients included in the specific outcome analysis).
As a first step, a propensity score is estimated for each cohort member at the index date, 
based on the values of the observed covariates. In this study, propensity scores will be 
estimated by conducting multivariable logistic regression modelling and incorporating 
measured potential predictors of therapy as independent variables and exposure group status 
(empagliflozin group vs. DPP-4 inhibitor group) as the outcome. “Combination with 
metformin” status will be taken into account by indicator variables that will be used in the 
analysis stratified by use of combinations with metformin at the index date.

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The selection of variables to be included in the propensity score modelling (see Section 9.3.3) 
will be based on examination of exposure group differences in the distribution of each 
covariate and within categories of insulin use at the index date. Ideally, the included 
covariates should be associated with the outcomes of interest. Simulation studies show that 
variables that are unrelated to the exposure but are related to the outcome should always be 
included in the estimation of propensity scores [R12-1913]. Inclusion of these variables 
increases the precision of the estimated effect of exposure without increasing bias. In 
contrast, inclusion of variables that are related to the exposure but not to the outcome can 
decrease precision of the estimated effect of exposure without decreasing bias. Thus, 
selection of variables to be included in the propensity score models will be based on their 
independent associations with the outcome rather than with the exposure. Potential 
associations will be evaluated from the literature and, when needed, from bivariate 
associations with the outcome within the data or from methods that account for small 
numbers of outcomes (e.g., Poisson regression or logistic regression using Firth penalised 
likelihood approach), if appropriate.
The variables listed in Annex 4 Table 17 are potential candidates for inclusion in the 
propensity score model: Annex 5 Table 1(ALI), Annex 5 Table 2 (AKI), Annex 5 Table 3
(UTI), Annex 5 Table 4(GI), and Annex 5 Table 5 (DKA).
Those variables will be assessed at the index date and during the previous lookback time 
period. Duration of the lookback period will be categorised, with indicator variables to be 
used for propensity score development and potential adjustment in multivariable regression 
models (see Section 9.7.1).
Prescription patterns change over time, and the confounding influence of the determinants of 
the prescription may also change. To allow for changing prescription patterns for 
empagliflozin from the time it is first available through the date of receipt of the data, a full-
interaction propensity score model will be generated where calendar year will be included as 
a covariate along with its interaction with each of the other covariates. This full-interaction 
propensity score model will allow the influence of each covariate in predicting treatment to 
vary across calendar years (thus accounting for potential channelling bias) and has an 
advantage of efficiency in providing one overall comprehensive model compared with 
generating separate propensity score models by calendar year [R18-1214].
Descriptive analyses of covariates at baseline will include means, standard deviations, and 
medians/interquartile ranges, when appropriate, for continuous variables and percentages for 
categorical variables. Next, selective removal of observations, known as “trimming”
[P12-04844], which occurs at both ends of the propensity score range, will be implemented. 
At the low end of the range, all patients, exposed or unexposed, with a propensity score 
below the 2.5 percentile value of the distribution of scores in the exposed group 
(i.e., empagliflozin) will be excluded. At the upper end of the range, we will exclude all 
patients, exposed and unexposed to empagliflozin, with scores greater than the 97.5 
percentile of scores among the comparator patients (i.e., DPP-4 inhibitor). Trimming will be 
performed separately for each outcome-specific cohort and, within each cohort, for each set 
of propensity scores.

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After trimming is completed, data will be stratified into deciles of propensity scores based on 
the distribution among empagliflozin new users. However, if the resulting decile strata are 
too small (i.e., have zero events in both treatment groups), deciles may be combined (e.g., to 
form quintiles), or alternative methods of producing summary estimates in the presence of 
sparse data will be explored, such as matching weights, which has been demonstrated to yield 
the smallest amount of bias in health care database studies with rare binary outcomes 
[P18-11001]. The propensity scores obtained after trimming will be used in the analysis to 
control for measured confounding variables simultaneously while reducing the loss in 
degrees of freedom that would have been experienced with a multivariable model, which is 
particularly important in studies with rare events. The propensity score methodology to be 
applied in this study will be further detailed in the statistical epidemiological analysis plan.
9.7.2
Primary and secondary objectives: estimate adjusted incidence rate ratios 
and compare adjusted incidence rates for each of the study outcomes
Adjusted incidence rates of ALI, AKI/CKD, severe complications of UTI, and incidence rates 
of GI among new users of empagliflozin and of DPP-4 inhibitors will be estimated and 
compared. Incidence rates will be reported as point estimates (in cases per 1,000 person-
years) and 95% CIs. Ascertainment during follow-up will allow estimation of the number of 
new cases for each of the primary outcomes. Current use person-time for each patient will be 
allocated as the time between the date of the first prescription for either empagliflozin or a 
DPP-4 inhibitor and the end of current time at risk (see Section 9.3.1.1 for time at risk 
definitions). The total person-time of observation among individuals at risk will then be 
calculated.
9.7.2.1
Main analysis
For each of the primary outcomes (primary objective) and the secondary outcomes
(secondary objective) of interest, estimation of adjusted current use IRRs with 95% CIs will 
be considered the main analysis of interest. Adjustment will be implemented by stratifying 
for propensity score deciles among empagliflozin new users vs. DPP-4 inhibitor new users.
More details on the analysis methods will be included in the statistical epidemiological 
analysis plan.
Although IRRs will be estimated using two different comparison groups and for different 
outcomes, no Bonferroni type I error adjustment for multiple comparisons is planned for this 
study [R14-1393, R14-2938].
Crude IRRs will facilitate comparison with the adjusted IRRs to provide an indication of the 
degree of confounding. However, crude IRRs cannot be used for any comparisons given that 
this is a non-randomised, observational study and crude IRRs are expected to be biased due to 
channelling and confounding. Secondary objectives are to estimate adjusted incidence rates 
of each of the outcomes among empagliflozin and DPP-4 inhibitor new users and estimate 
adjusted IRRs stratified by insulin use at baseline.

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9.7.2.2
Secondary outcome analyses
The following adjusted incidence rates for each of the primary and secondary outcomes of 
interest among empagliflozin new users and among DPP-4 inhibitor new users will be 
estimated:

Cumulative incidence function plots will be reported graphically to depict the 
cumulative incidence rates of events during the follow-up.

Adjusted incidence rates of the primary and secondary outcomes, overall and stratified 
by categories of insulin use at the index date, age, sex, and other variables of interest 
such as diabetes control.
Because the patients with T2D treated with insulin may have diabetes in a more advanced 
stage, may receive a different GLD treatment, and may be at different risk of the outcomes of 
interest, the incidence rate for each of the primary outcomes of interest will be estimated 
stratified by insulin use at the index date in each cohort. Sensitivity analysis will include the 
combined analysis of patients with T2D treated with and without insulin, and tests of 
interaction will be performed to evaluate whether these estimates are biased. Incidence rates 
will be reported as point estimates (in cases per 1,000 person-years) and 95% CIs. The 
following estimates and comparisons will be generated:

Summary IRRs after adjusting, by stratifying for propensity score deciles, overall and 
by categories of insulin use at index date, age, sex, and other variables of interest such 
as diabetes control, comparing empagliflozin new users with DPP-4 inhibitor new 
users.
9.7.3
Duration, dose, and recent use effects analysis

Adjusted IRRs by categories of duration of exposure will be estimated among 
empagliflozin new users vs. DPP-4 inhibitor new users. For example, patients with at 
least 1 year of continuous empagliflozin exposure will be compared with patients with
at least 1 year of continuous DPP-4 inhibitor exposure; patients with less than 1 year 
of exposure to empagliflozin will be compared with patients with less than 1 year of 
exposure to DPP-4 inhibitors. Categories of duration will be defined based on 
available data. This analysis will be done if there is enough variation in the duration 
of use within the empagliflozin group.

Adjusted IRRs by exposure dose categories will be estimated among empagliflozin 
new users vs. DPP-4 inhibitor new users. This analysis will be done if dose variation 
occurs within the empagliflozin group.

Main analyses repeated to estimate adjusted IRRs using recent use (recent time at 
risk) instead of current use (current time at risk).

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9.7.4
Interim reports to monitor accrual of empagliflozin users and the event rates 
of acute liver injury and acute kidney injury
Accrual of empagliflozin users was monitored and reported annually in three interim reports 
[BI document numbers c10503662-01, c17493314-01, and c24037075-01]. The interim 
reports included data up to 19, 24, and 36 months after use of empagliflozin was first 
captured in the CPRD were released in June of each year. Crude incidence rates of acute liver 
and kidney injury outcomes (overall, not stratified by treatment) were generated for the 
second and third interim reports and were in line with what it is expected considering that no 
validation was performed. Given the current event rates, the number of new users of 
empagliflozin accrued at 36 months after launch was too low to yield acceptable precision
and statistical power, the study population has been expanded by including countries with 
better market uptake of empagliflozin.
9.7.5
Imputation of missing values
In the CPRD, no high frequency of missing values is expected for most variables, except for
lifestyle variables. If missing data are common for lifestyle variables, multiple imputation 
methods will be used to replace missing values during propensity score generation and 
multivariable analysis. Additional details on when and how multiple imputation methods will 
be used will be provided in the statistical epidemiological analysis plan. We propose to use 
multiple imputation methods because in most cases they allow for better bias correction than 
alternative methods and are more efficient than the complete-case approach. The complete-
case approach can be very costly of information in a body of high-dimensional data, since the 
proportion of complete cases will decline with the increase in the number of variables
[R07-2456, R14-5281]. Multiple imputation methods assume that the data are missing at 
random. If it is determined based on previously established knowledge of the data source that 
the data for particular variables in question are not missing at random (e.g., the data 
collection mechanism is such that sicker patients do not have those variables collected), then 
alternative methods will be explored. Analyses evaluating potential effects of variables that 
are missing not at random on the estimation of the treatment effect are inherent in the 
sensitivity analysis outlined in Section 9.7.6, item 5. Details will be specified in the statistical 
epidemiologic analysis plan.
In Denmark and the HIRD, no data will be available for smoking, alcohol, BMI, HbA1c 
(available in around 30% of the patients in the HIRD), but no high frequency of missing 
values is expected for most of the other variables. Effect of unmeasured confounders will be 
evaluated in a sensitivity analysis.
Of note, for the medical history conditions and comorbidities to be collected for inclusion in 
the propensity score, the absence of a code for a condition will be interpreted as an absence of 
the event.

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9.7.6
Sensitivity analyses
The following sensitivity analyses will be conducted:
1. In the main analysis (see Figure 1) current use ends 30 days after end of supply but in 
this sensitivity analysis current use will end 90 days after end of supply. This change 
will be applied to all exposure groups: empagliflozin new users and DPP-4 inhibitor 
new users. New adjusted IRRs will then be estimated for empagliflozin users vs.
DPP-4 inhibitor users.
2. For cases of ALI and AKI, a sensitivity analysis including outpatient cases of ALI or 
AKI, in the data sources where primary care data are available (CPRD and HIRD). 
The exclusion and censoring conditions will be the same as those for the primary 
outcome.
3. For all outcomes, conduct analyses including only validated cases or correct estimates 
with PPVs: i.e., estimate summary adjusted IRRs among validated cases or, when less 
than 70% of the cases are validated, explore other methods to correct for disease 
misclassification (e.g., correct the IRRs for the PPV obtained from the validation) 
[R18-1561]..
4. Compare characteristics of validated cases with those of cases that were not validated.
5. For cases of CKD, conduct analyses to explore the time between exposure and CKD
using varying time windows to explore the lag time to the outcome. The time window 
will be defined in the statistical epidemiological analysis plan. Exploratory analyses 
using different definitions of CKD will also be conducted to compare definitions and 
to facilitate comparison to other studies. The definitions will be defined in the 
statistical epidemiological analysis plan.
6. Assess the potential effect of unmeasured confounders on the association between 
empagliflozin use and, for example, ALI, by using the method described by Lash et 
al. [R14-5373]. These methods may be of special interest to evaluate HbA1c as a 
measure of disease control, in all data sources, or smoking, BMI, and other variables 
in the HIRD and Denmark, where no data are available. Additionally, these methods 
apply to variables that are missing not at random, as the missingness of these 
variables is ultimately unmeasured confounding. More details and examples of how 
this bias analysis method will be used will be provided in the statistical 
epidemiological analysis plan.
7. Estimate summary adjusted IRRs using intention-to-treat analysis, carrying forward 
the initial exposure status and disregarding changes in treatment status during all 
available follow-up time.
8. Tabulate the crude count of each study outcome by DPP-4 inhibitor type to provide an 
indication regarding whether the distribution of study outcomes in each individual 
type of DPP-4 inhibitor is different from the expected count based on patient use. 
9. Conduct a sensitivity analysis of the meta-analysis (described in Section 9.7.7) to 
combine the IRRs obtained from the main analyses performed in the cohort studies in 
the different data sources. The main meta-analysis will be a Poisson regression model 
with random intervention effects, while the sensitivity analysis will be a Poisson 
regression model with fixed intervention effects.

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9.8
QUALITY CONTROL
Standard operating procedures or guidance documents at the participating institutions will be 
used to guide the conduct of the study.
At RTI-HS, these procedures include internal quality audits, rules for secure and confidential 
data storage, methods to maintain and archive project documents, quality-control procedures 
for programming, standards for writing analysis plans, and requirements for senior scientific 
review. All programming written by one study analyst will be reviewed independently by a 
different analyst, with oversight by a senior statistician. All key study documents, such as the 
analysis plan, abstraction forms, and study reports, will undergo quality-control review, 
senior scientific review, and editorial review.
At RTI-HS, an independent Office of Quality Assurance (OQA) will perform audits and 
assessments that involve various aspects of the project, including but not limited to education 
and training documentation, data entry and data transfer procedures and documentation, and 
IRB documentation. Such audits will be conducted by the OQA according to established 
criteria in standard operating procedures and other applicable procedures. Standard 
procedures will be in place to restore files in the event of a hardware or software failure.
 will follow its standard procedures for data management, data analysis, 
and interpretation and other quality-control and contingency-planning procedures. All reports 
undergo senior review.
At 
 all programming required for study database extraction and creation of the 
analytic data sets from the HIRD and analysis are performed in accordance with 
 
Programming Standards. The 
 Programming Standards are a set of documents 

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describing data extraction methods that are referenced in 
 Standard Operating 
Procedures and provide a guideline for basic, frequently used terms and definitions and 
respective coding information to maintain operational consistency. These documents contain 
confidential and proprietary information but can be available for audit if necessary.
At 
 data quality checks include, but are not limited to, programming checks by an 
individual who is not the main programmer for the study, internal data set consistency, and 
checks to ensure that protocol criteria were met. The distribution and range of all covariates 
are examined to verify that they are within the expected range. If any unexpected 
distributions are identified, or for specific covariates, the raw claims for a sample of not less 
than 15 patients are reviewed to confirm that the questioned variables have been correctly 
specified. Additionally, all the diagnosis, procedure, and drug codes are reviewed in the 
coding scripts provided by a programmer. All quality checks and resolution of issues 
identified are documented in a log.
A quality-assurance audit of this study may be conducted by the sponsor or the sponsor’s 
designees.
9.9
LIMITATIONS OF THE RESEARCH METHODS
There are several methodological challenges when conducting epidemiologic studies to 
evaluate the association between glucose-lowering medications and outcomes of interest 
among patients with diabetes. These challenges include, but are not limited to, changes in 
treatment in response to advancing diabetes or due to adverse effects of specific drugs and
time-varying risk of an outcome depending on duration of exposure [P12-13528, P14-17457, 
R14-4378].
9.9.1
Confounding
Although use of propensity scores will facilitate the control of measured confounders, 
unmeasured and unidentified confounders could still introduce bias if they are differentially 
distributed among the exposed and comparator groups and are related to the outcome. As an 
example, use of over-the-counter medications will remain unmeasured in this study.
Confounding by indication or severity, also known as channelling bias, is a common bias in 
pharmacoepidemiology. Patients starting treatment with a newly marketed drug might have 
more severe disease than patients not taking the medication either because of self-selection or 
because of physician preference. They may also have a less severe form of the disease if 
physicians prefer to test new drugs with a less familiar safety profile in less severely affected
patients. New medications may also be prescribed differentially by physicians who are “early 
adopters” of new technologies and who systematically treat more severely affected patients 
with the new medications. The use of propensity scores and of DPP-4 inhibitors as the 
comparator group—relative to other GLDs such as sulfonylureas (DPP-4 inhibitors were
recently introduced in the market)—reduces the risk of this type of bias, but residual 
confounding could still operate. For example, empagliflozin could be preferentially 
prescribed to patients with more severe diabetes or for whom other GLDs have failed. 

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Empagliflozin could also be more likely prescribed to patients with fewer risk factors for 
severe complications of UTI. Similarly, the decision for hospitalisation could be affected by 
the perceived side effects profile. These channelling patterns could bias the risk estimate 
towards or away from the null.
The occurrence of the outcomes of interest may also vary over time according to the duration 
or cumulative dose of drug exposure. To account for these time-varying hazards, a stratified 
analysis estimating the IRRs of the outcomes of interest by categories of cumulative duration 
of exposure will be conducted.
9.9.2
Other biases
Misclassification bias can occur when study patients are not correctly assigned to the 
outcome and/or exposure. Because prescribing records will be used, misclassification of 
exposure is unlikely. However, analyses will not control for non-adherence to the study 
drugs. Moreover, misclassification of new users could happen if free samples of 
empagliflozin or DPP-4 inhibitor are provided to patients for different periods of time.
Misclassification of the outcome will be reduced by the validation process that has been 
planned for each of the outcomes of interest. Among females, misclassification of Fournier’s 
gangrene, a severe complication of GI, is possible because there are no ICD-10 or Read codes 
for this disease among females.
Empagliflozin will be compared with DPP-4 inhibitors as a group. Information about the risk 
of the outcomes of interest among patients using specific DPP-4 inhibitors is scarce;
therefore, the comparator groups will include specific drugs within each drug class that may 
or may not have a differential risk for some of the outcomes of interest. This could potentially 
bias empagliflozin risk estimates for this study.
The main analysis in this study will be performed on data from patients as treated and during 
current use that will terminate after the days’ supply of the last prescription has elapsed plus 
30 days. However, if drug discontinuation predicts future outcomes of interest, then an 
informative censoring bias may occur because we are removing outcomes from their 
appropriate exposure category. In this study, a sensitivity analysis with varying latency 
periods after drug discontinuation will evaluate the potential for informative censoring bias.
To address potential informative censoring, an additional sensitivity analysis will be 
performed by conducting an intention-to-treat analysis, which will carry forward the initial 
exposure status and disregard changes in treatment status over time.

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9.9.3
Strengths and limitations concerning each study database
9.9.3.1
CPRD, UK
Strengths and limitations of the CPRD:

Data from the primary care database (CPRD GOLD) cover 3.91% of the UK 
population, and data from CPRD Aurum cover 11.12% of the UK population. 
However, CPRD GOLD includes practices from England, Scotland, Wales, and 
Northern Ireland, while CPRD Aurum includes only practices from England (e-mail 
correspondence, 01 April 2019, on file).

The CPRD contains information on primary care for all patients and from hospital 
data for a subset of approximately 54% of patients, although hospital coverage may 
vary in the future. As of April 2019, CPRD Aurum has linkage of data from 93% of 
patients with hospital and death data [R19-1734].

Outpatient laboratory data are available, but no inpatient laboratory data. Inpatient 
laboratory data can be obtained only if results are recorded in the discharge letter and 
if the discharge letter is available to the GP at the time of the GP questionnaire.

Although most of the laboratory results are incorporated in the electronic system 
automatically, microbiology test results are often missing, but the degree of 
missingness has not been described. This may have consequences for UTI and GI case 
validation where microbiology results are needed. The validation of these outcomes 
will include degrees of certainty that can be included in the analysis.

Identification of cases of hospitalisation for ALI, AKI, DKA, or GI is possible 
through linkage to HES. For those patients who are in practices not linkable to HES,
identification of hospitalisations can be done through algorithms that identify codes 
for diagnosis and codes for hospitalisation within a specific time window. The time 
windows commonly used are 7 days or 30 days [R18-3575]. This study will use a 
time window of 30 days to increase the sensitivity for detecting hospitalisations, 
although it may reduce the specificity vs. a time window of 7 days. Recording of 
hospitalisations in the CPRD primary care is not 100% (i.e., the hospitalisation is not 
recorded, or the discharge diagnosis is not recorded). In addition, when the
hospitalisation is recorded, its association with a diagnosis code is not straight-
forward, because there may be other diagnosis codes within the same time window. It 
is expected that after validation, some of the hospitalisations for ALI, AKI, DKA, or 
GI will be discarded [R15-4888, R18-3577]. Emergency department visits can only be 
identified in primary care as recorded by the GP. Although a HES A&E linkage 
database exists, it is not used because data coverage is incomplete in comparison with
national A&E data attendances.

Validation is possible through questionnaires sent to the GPs, who can access primary 
care medical records. Source hospital records cannot be accessed, although the GP 
can access discharge letters recorded in the primary care database.

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9.9.3.2
Danish Population Registries
Strengths and limitations of the Danish data sources:

Data from national registries covers all the Danish population, i.e., includes all age 
ranges in the population.

At the national level, information on all reimbursed care is available.

Primary care outpatient data are not available. Underascertainment of diabetes and 
some of the comorbidities of interest is possible and likely for conditions that are 
managed in the primary care setting. However, the study will include data from the 
outpatient hospital setting, secondary discharge codes, and medication use to define 
some of the covariates of interest. Definitions will be adapted to each data source 
depending on data availability and on the existence of previously validated 
algorithms.

Source medical records can be accessed for selected projects and with special 
approvals for studies conducted in the Danish data sources.

Most potential confounders can be obtained from the national databases, although 
only hospital-based diagnoses are available. Medication data can be used to identify 
proxies for diseases such as diabetes [R18-0259].

Since approximately 2000, the clinical laboratory information system research 
databases contains results of laboratory tests performed at hospital-based laboratories 
for the subpopulation of patients treated in the Central Denmark Region, including 
tests ordered by primary care clinicians from those laboratories [R18-0264]. On a 
nationwide level, laboratory data for all 5.77 million Danish inhabitants have recently 
become available for research with complete data coverage beginning in 2015 and 
onwards in the new nationwide Register of Laboratory Results for Research (LAB_F), 
tracking all laboratory test results from both primary and secondary care [R18-3665].

Identification of hospitalised cases of ALI and AKI is possible. No primary care cases 
can be identified through GP diagnoses, but isolated cases of liver enzyme elevations
(e.g., ALT and/or AST ≥3 × ULN) or eGFR-defined kidney disease in primary care
can be identified through blood samples taken in primary care. For validation, hospital 
laboratory results can be used in the Central Denmark Region subpopulation since 
2000 (e.g., through liver enzyme test values). For the remainder of Denmark’s
population, laboratory data have become available at the Danish Board of Health 
starting in 2015, and it is still unclear whether retrieving individual person-identifiable 
laboratory data for validation purposes on a nationwide scale will therefore be 
possible.

Identification of hospitalisations for DKA is possible. For validation, hospital 
laboratory results in the subpopulation of the Central Denmark Region can be used; 
for the remainder of the population, hospital laboratory results would have to be 
extracted from hospital medical records, if available.

Validation is possible through access to source medical records. This can be done for 
selected projects and with special approvals for studies conducted in the Danish data 
sources.

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9.9.3.3
HIRD, US
Strengths and limitations of the HIRD:

A large percentage of the US population is covered in these data sources.

Patients aged 65 years or older are underrepresented in these data sources. Data are 
available for those who continue to have insurance through employment after the age 
of 65 years and for a subset of Medicare patients. The proportion of patients aged 
65 years or older will be described for the HIRD and for the other study data sources.

Access to medical records is possible for many but not all of the cases requiring 
validation. Medical record retrieval rates have been low for some studies. Redacted 
copies of hospital medical records are expected to be obtained for approximately 60% 
of the patients.

These are claims-based data sources with limited clinical information. Clinical 
information can be available via linkage to patients’ medical records.

Ascertainment of ALI and AKI: identification of inpatient and outpatient cases of ALI 
and AKI is possible, although primary care laboratory results are available 
electronically for approximately 30% of the patients; inpatient laboratory results can 
be obtained only through abstraction of data from hospital medical records, with an 
expected retrieval rate of approximately 60%.

Ascertainment of hospitalisations for DKA: identification of cases is possible, but 
validation will be limited because inpatient laboratory results can be obtained only 
through abstraction of data from hospital medical records, with an expected retrieval 
rate of approximately 60%.

Claims data may include rule-out diagnoses. To increase sensitivity, for the outcomes 
of interest, a record for one of the diagnoses of interest will be enough to be 
considered a potential case. Type 2 diabetes will be defined using ICD-9-CM or ICD-
10-CM diagnosis codes from both outpatient and inpatient health care claims, as well 
as pharmacy dispensing claims for antidiabetic medications. This algorithm was 
derived from similar algorithms with PPVs greater than 85% for identifying T2D in 
health care claims data [R18-3576, R16-3197, R18-3667]. For other covariates of 
interest, algorithms including more than one claim with a diagnosis code or a 
combination of diagnosis and medication use codes may be required. As discussed in 
the definitions of the covariates (Section 9.3.3), the definitions will be adapted to each 
data source depending on data availability and on the existence of previously 
validated algorithms.
9.9.4
Limitations due to the new-user design definition
A new-user design is used for this study to overcome bias associated with the inclusion of 
prevalent users and to better distinguish medication effect from T2D-progression effect. 
However, a new-user design can restrict inclusion (1) to new users of each study medication, 
or (2) as in this study, to new users of a specific study medication without prior use of any of 
the other study medication groups.

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The “medication class new-user design” used for the second interim report [c17493314-01]
used all information available before or at the index date to consider a patient as a new user. 
As a result, more than 50% of patients in the empagliflozin group and in the SGLT2 
inhibitors group were excluded due to prior use of DPP-4 inhibitors. To avoid this loss of 
patients, the medication class new-user design was maintained but evaluated use of 
medications only in the previous 12 months. That is, new users were defined as patients who 
received a first prescription of empagliflozin, other SGLT2 inhibitor, or DPP-4 inhibitor 
during the study period, with no prescriptions of any of the study drugs recorded in the 
12 months (instead of ever) before the start of the study. Based on an exploratory analysis 
conducted for the second interim report, the number of patients increased by approximately
40%. Analysis in the third interim report with 1 year of additional data identified 1,744 and 
1,660 new users of empagliflozin in the ALI and AKI cohorts, respectively.
Bias due to including switchers from DPP-4 inhibitors that may have experienced disease 
progression will be addressed in the final analysis by considering the inclusion of disease 
progression variables and prior use of DPP4-inhibitors (e.g., number of prior prescriptions) in 
the propensity score.
9.9.5
Limitation due to study size
As described in more detail in Section 9.4.1, the CPRD is probably the richest data source to 
conduct this study since it captures lifestyle factors not available in other data sources.
However, the number of patients available for analysis have been monitored during the 
3 years after empagliflozin launch in the CPRD. Actual and projected number of users of 
empagliflozin in the CPRD were low and not enough to address the study objectives. To 
overcome this limitation, the protocol has been amended to extend the study period and add 
the Danish Population Registries and the HIRD data sources.
The new projected study size is estimated to be sufficient to address the study objectives, but
some of the subgroup analyses may be underpowered. The purpose of using multiple 
databases is to increase study size and to be able to accrue more users in a shorter period of 
time; however, analysis at each individual data source may be underpowered for some of the 
outcomes of interest, especially for ALI and DKA in the CPRD UK and in Denmark. Due to 
the rarity of some of the outcomes and the study size in some data sources, it is possible that 
at the time of the analysis, some propensity score strata may contain zero events. In this case, 
alternative methods, such as matching weights, may be used to reduce the amount of bias.
9.9.6
Generalisability
Generalisations from study findings depend on the category of the finding [R14-2938, 
R14-1409].
The CPRD GOLD is a population-based database that provides data from practices in 
England, Scotland, Wales, and Northern Ireland, entered by primary care practitioners in a 
routine clinical care setting. Therefore, the study results can be generalised to similar patients
with T2D in other geographic settings, including most industrialised countries. For the same 

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reason, because CPRD Aurum is also included, although it provides data only from practices 
in England, it is also expected that the study results can be generalised to similar patients with 
T2D in other geographic settings.
The Danish Population Registries cover the full population of Denmark, and thus results from 
this study are likely to be generalisable to the Danish population of new users of the study 
medications. It is also likely that results from Denmark can be generalised to most 
industrialised countries, especially to the other Scandinavian countries with similar health
care systems.
The HIRD is a broad, clinically rich and geographically diverse spectrum of longitudinal 
claims data from 40 million health plan members in the Northeastern, Mid-Atlantic, 
Southeastern, Midwest, Central, and Western regions of the US. It includes both 
commercially insured patients aged less than 65 years and Medicare-insured patients aged 
65 years or more. However, patients aged 65 years or older are underrepresented in this data 
source. Data are available for those who continue to have insurance through employment 
after 65 years of age and for a subset of Medicare patients.
10.
PROTECTION OF HUMAN SUBJECTS
This is a non-interventional study using an existing database (secondary data) and does not 
pose any risks for patients. All data collected in the study will be de-identified with no breach 
of confidentiality with regard to personal identifiers or health information. RTI-HS will apply 
for an independent ethics committee review according to local regulations in the UK; in 
addition, RTI-HS will obtain approval from the RTI International† IRB.
Data protection and privacy regulations will be observed in collecting, forwarding, 
processing, and storing data from study participants.
10.1
RTI INTERNATIONAL
RTI International holds a Federal-Wide Assurance from the
that allows the organisation to 
review and approve human subjects protocols through its IRB committees. RTI International 
currently has three IRB committees available to review research protocols. One IRB 
committee is constituted to review medical research and has two members who are 
physicians. These IRBs have been audited by the US Food and Drug Administration and are 
fully compliant with applicable regulatory requirements.
10.2
CPRD
RTI-HS will submit the final study protocol for approval to the Independent Scientific 
Advisory Committee (ISAC) (http://www.cprd.com/ISAC). The CPRD has obtained ethical 
approval from a Multicentre Research Ethics Committee for all observational research using 
                                                
† RTI Health Solutions is a business unit of RTI International, a private, not-for-profit research organisation.

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CPRD data without patient involvement; however, ISAC may recommend that the
Multicentre Research Ethics Committee review the study documentation if any ethical issues 
arise. The possibility of unintentional (deductive) disclosure arises when cells with small 
numbers of patients are quoted. When reporting the data, CPRD policy is that no cell should 
contain less than 5 events.
10.3
THE DANISH POPULATION REGISTRIES
The study must be approved by the Danish Data Protection Agency. Access to medical charts 
will be approved by the Patient Safety Board, following all standard and required procedures
for such approval. The data will be handled according to the Danish Act on Processing of 
Personal Data. The possibility of unintentional (deductive) disclosure arises when cells with
small numbers of patients are quoted. When reporting the data, Danish policy is that no cell 
should contain less than 5 events.
10.4
HIRD
This study is based on medical and pharmacy claims data from a large insured population in 
the US. There is no active enrolment or active follow-up of study subjects, and no data will 
be collected directly from individuals.
 maintains Data Sharing Agreements and Business Associate Agreements with all 
covered entities who provide data to the HIRD. HealthCore’s access, use, and disclosure of 
protected health information (PHI) are in compliance with the Health Insurance Portability 
and Accountability Act (HIPAA) Privacy Rule (45 CFR Part 160 and Subparts A and E of 
Part 164). 
 does not access, use, or disclose identifiable PHI unless under a 
specific waiver of authorisation (e.g., a HIPAA Waiver of Authorization from an institutional 
review board [IRB]). 
 accesses the data in a manner that complies with federal 
and state laws and regulations, including those related to the privacy and security of 
individually identifiable health information.
As PHI must be accessed to acquire medical records to validate electronic case-finding 
algorithms, a HIPAA Waiver of Authorization will be applied for from an IRB. 
 
will submit the protocol to a central IRB for review and approval. Approval is typically 
provided within 2 to 3 weeks of submission. Once IRB approval is obtained, HealthCore’s 
vendor will proceed with the conduct of medical record acquisition. If changes to the protocol 
are required, 
 will submit an amendment to the IRB. As the IRB is independent, 
 cannot control the approval or whether there are conditions for the approval.
Notwithstanding receipt of approval from a central IRB, in some instances, individual 
institutions may require approval from their local IRB, which would require a separate 
protocol submission and, in some cases, additional fees. In these cases, 
 RTI 
Health Solutions (RTI-HS), and Boehringer Ingelheim will need to agree whether or not to 
proceed with chart acquisition from these institutions.

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 will provide to the vendor only the minimum amount of patient information that 
is necessary to acquire the needed medical records. 
 uses only vendors that follow 
federal and state laws and regulations, including but not limited to privacy and security rules 
such as HIPAA.
At no time during the conduct of this study will 
 provide patient- or provider-
identifying information to RTI-HS or Boehringer Ingelheim. Only aggregated data will be 
reported to RTI-HS or Boehringer Ingelheim. The possibility of unintentional (deductive) 
disclosure arises when cells with small numbers of patients are quoted. When reporting the 
data, HIRD policy is that no cell should contain less than 10 events.
10.5
OTHER GOOD RESEARCH PRACTICE
This study adheres to the Guidelines for Good Pharmacoepidemiology Practices (GPP) of the 
International Society for Pharmacoepidemiology [R11-4318] and has been designed in line 
with the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance 
(ENCePP) Guide on Methodological Standards in Pharmacoepidemiology [R14-5282]. The 
ENCePP Checklist for Study Protocols [R13-1395] is included in Annex 2.
The study is a PASS and will comply with the definition of the non-interventional 
(observational) study referred to in the International Conference on Harmonisation of 
Technical Requirements for Registration of Pharmaceuticals for Human Use tripartite 
guideline Pharmacovigilance Planning E2E [R11-2259] and provided in the EMA Guideline 
on Good Pharmacovigilance Practices (GVP) Module VIII: Post-Authorisation Safety 
Studies [R13-5420] and with the 2012 European Union pharmacovigilance legislation, 
adopted 19 June 2012 [R14-5246]. Following EMA regulations, the study protocol has been 
registered at the EU PAS Register, and an abstract of results will be registered at the EU PAS 
Register (registration number: ENCEPP/SDPP/13413; 
http://www.encepp.eu/encepp/viewResource.htm?id=13414).
11.
MANAGEMENT AND REPORTING OF ADVERSE 
EVENTS/ADVERSE REACTIONS
Based on current guidelines from the International Society for Pharmacoepidemiology
[R11-4318] and the EMA [R13-1970], non-interventional studies such as the one described in 
this protocol, conducted using medical chart reviews or electronic claims and health care 
records, do not require expedited reporting of suspected adverse events/reactions. 
Specifically, as stated in Section VI.C.1.2.1 of Guideline on Good Pharmacovigilance 
Practices (GVP), Module VI – Management and Reporting of Adverse Reactions to 
Medicinal Products, for non-interventional study designs, which are based on use of 
secondary data, reporting of adverse reactions is not required.
The data generated in the course of the study will be monitored by the BI responsible person.
When an observation is identified that may qualify as a special safety issue or that may have 
implications for the benefit-risk balance of empagliflozin, appropriate BI functions will be 
notified according to BI standard operating procedures.

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12.
PLANS FOR DISSEMINATING AND COMMUNICATING 
STUDY RESULTS
Study milestones are agreed with the EMA. The study progress was reported by BI in 
regulatory communications in line with the risk management plan, Periodic Safety Update 
Reports, and other regulatory milestones and requirements. Study reports are prepared using a 
template following the Guideline on Good Pharmacovigilance Practices (GVP), Module VIII, 
Section B.6.3 [R13-5420]. The planned periodic interim reports at 12, 24, and 36 months
were reported within the earliest corresponding Periodic Safety Update Report.
Section V of Guidelines for Good Pharmacoepidemiology Practices (GPP) [R11-4318]
contends that “there is an ethical obligation to disseminate findings of potential scientific or 
public health importance”; for example, results pertaining to the safety of a marketed 
medication. Moreover, a well-developed publication strategy is encouraged in the Guideline 
on Good Pharmacovigilance Practices, Module VIII, Section B.7 [R13-5420].
RTI Health Solutions, Aarhus, and 
reserve 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 [R13-5418]. When 
reporting results of this study, the appropriate STROBE (Strengthening the Reporting of 
Observational Studies in Epidemiology) checklist will be followed [R13-2485].

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13.
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13.1
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13.2
UNPUBLISHED REFERENCES
c10503662-01
Post-authorisation safety study in patients with type 2 diabetes mellitus to 
assess the risk of acute liver injury, acute kidney injury and chronic kidney 
disease, severe complications of urinary tract infection, and the risk of 
genital infections, among patients treated with empagliflozin compared to 
patients treated with other SGLT2 inhibitors or DPP-4 inhibitors – First 
Interim Monitoring Report. Document number c10503662-01, June 2016.
c17493314-01
Post-authorisation safety study in patients with type 2 diabetes mellitus to 
assess the risk of acute liver injury, acute kidney injury and chronic kidney 
disease, severe complications of urinary tract infection, genital infections, 
and diabetic ketoacidosis among patients treated with empagliflozin 
compared to patients treated with other SGLT2 inhibitors or DPP-4 
inhibitors – Second Interim Monitoring Report. Document number 
c17493314-01, June 2017.
c19231123-01
A 5-year enhanced pharmacovigilance surveillance initiative to survey and 
characterise spontaneous occurrence and experience of ketoacidotic events in 
patients treated with empagliflozin–containing products (EUPAS21696), 
Interim Report 1. Document number c19231123-01, December 2017.
c24036731-01
PASS: Evaluation of the feasibility of a post-authorisation safety study of 
empagliflozin in additional data sources from Europe and the United States 
of America. Document number c24036731-01, June 2018.
c24037075-01
Post-authorisation safety study in patients with type 2 diabetes mellitus to 
assess the risk of acute liver injury, acute kidney injury and chronic kidney 
disease, severe complications of urinary tract infection, genital infections, 
and diabetic ketoacidosis among patients treated with empagliflozin 
compared to patients treated with other SGLT2 inhibitors or DPP-4 
inhibitors – Third Interim Monitoring Report. Document number 
c24037075-01, June 2018.

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ANNEX 1. LIST OF STAND-ALONE DOCUMENTS
PASS: Evaluation of the feasibility of a post-authorisation safety study of empagliflozin in 
additional data sources from Europe and the United States of America. Document number: 
c24036731-01, June 2018.

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ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS
Doc.Ref. EMEA/540136/2009
Doc.Ref. EMA/540136/2009
ENCePP Checklist for Study Protocols (Revision 3)
Adopted by the ENCePP Steering Group on 01/07/2016
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 as recommended in the Guidance and Module VIII of the Good 
pharmacovigilance practices (GVP).
Study title:
Post-authorisation safety study in patients with type 2 diabetes mellitus to assess the risk of 
acute liver injury, acute kidney injury and chronic kidney disease, severe complications of 
urinary tract infection, genital infections, and diabetic ketoacidosis among patients treated 
European Network of Centres for 
Pharmacoepidemiology and 
Pharmacovigilance

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with empagliflozin compared to patients treated with DPP-4 inhibitors
Study reference number:
ENCEPP/SDPP/13413; http://www.encepp.eu/encepp/viewResource.htm?id=13414
Section 1: Milestones
Yes
No
N/A
Section 
Number
1.1
Does the protocol specify timelines for 
1.1.1 Start of data collection‡
6
1.1.2 End of data collection§
6
1.1.3 Study progress report(s)
6
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:
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
                                                
‡ Date from which information on the first study is first recorded in the study data set or, in the case of secondary use of data, 
the date from which data extraction starts.
§ Date from which the analytical data set is completely available.

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Section 3: Study design
Yes
No
N/A
Section 
Number
3.2
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?
9.1, 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?
9.1
4.2.4 Disease/indication?
9.2.1
4.2.5 Duration of follow-up?
9.2.9
4.3
Does the protocol define how the study population 
will be sampled from the source population? 
(e.g. event or inclusion/exclusion criteria)
9.2.7, 
9.2.8
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
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?

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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?
9.9.1, 9.9.2
7.1.1. Does the protocol address confounding by 
indication if applicable?
9.9.1
7.2
Does the protocol address:
7.2.1. Selection biases (e.g. healthy user bias)
9.9.1, 9.9.2
7.2.2. Information biases (e.g. misclassification of 
exposure and endpoints, time-related bias)
9.9.2
7.3
Does the protocol address the validity of the study 
covariates?
9.3.3
Comments:
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:

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Section 9: Data sources
Yes
No
N/A
Section 
Number
9.1.1 Exposure? (e.g. pharmacy dispensing, general 
practice prescribing, claims data, self-report, face-to-
face interview)
9.4, 
Annex 1 , 
Annex 6
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, 
Annex 1 , 
Annex 6
9.1.3 Covariates?
9.4, 
Annex 1 , 
Annex 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, 
Annex 1 , 
Annex 6
9.2.2 Outcomes? (e.g. date of occurrence, multiple 
event, severity measures related to event)
9.4, 
Annex 1 , 
Annex 6
9.2.3 Covariates? (e.g. age, sex, clinical and drug use 
history, comorbidity, comedications, lifestyle)
9.4, 
Annex 1 , 
Annex 6
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, 
Annex 1 , 
Annex 6
9.3.2 Outcomes? (e.g. International Classification of 
Diseases (ICD)-10, Medical Dictionary for Regulatory 
Activities (MedDRA))
9.4, 
Annex 1 , 
Annex 6
9.3.3 Covariates?
9.4, 
Annex 1 , 
Annex 6
9.4
Is a linkage method between data sources 
described? (e.g. based on a unique identifier or other)
9.4, 
Annex 1 , 
Annex 6
Comments:
Section 10: Analysis plan
Yes
No
N/A
Section 
Number
10.1
Is the choice of statistical techniques described? 
9.7.1, 
9.7.2, 9.7.7
10.2
Are descriptive analyses included?
9.7.2
10.3
Are stratified analyses included?
9.7.2, 9.7.3
10.4
Does the plan describe methods for adjusting for 
confounding?
9.7.1, 
9.7.2, 9.9.1
10.5
Does the plan describe methods for handling missing 
9.7.5

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Section 10: Analysis plan
Yes
No
N/A
Section 
Number
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? 
9.8
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?
9.9.2
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)
9.9.1
12.2
Does the protocol discuss study feasibility? 
(e.g. study size, anticipated exposure, duration of follow-
up in a cohort study, patient recruitment)
9.9.5, 
Annex 1
Comments:
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:

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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:19 Jul 2021
Signature: 

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ANNEX 3. CODES TO BE USED FOR EXCLUSION CRITERIA
ICD-10 codes are used in the three data sources. The list of Read codes (and SNOMED, and
EMIS local codes, if needed) to be used in the CPRD and ICD-9 codes to be used in the 
HIRD will be generated based on the common ICD-10 list and described in the statistical 
analysis plan.
Annex 3 Table 1
Liver injury exclusion criteria: ICD-10 code
ICD-10 code
Description
History of acute liver injury (For ALI primary outcome, the lookback period is ever before or at the index 
date. For ALI secondary outcome, the lookback period is 6 months before or at the index date)
K71
Toxic liver disease
K72
Hepatic failure, not elsewhere classified (includes acute and subacute hepatic failure, 
chronic hepatic failure, and hepatic failure, unspecified)
Liver transplant (For ALI primary outcome, the lookback period is ever before or at the index date. For 
ALI secondary outcome, the lookback period is 6 months before or at the index date)
Z94.4
Liver transplant status
T86.4
Liver transplant failure and rejection
Pregnancy (For ALI primary and secondary outcomes, algorithms including different time windows for 
different codes will be developed and described in detail in the statistical plan)
O00-O99
Pregnancy, childbirth, and the puerperium
Chronic liver disease and alcoholism (For ALI primary outcome, the lookback period is ever before or at 
the index date)
K70
Alcoholic liver disease
K73
Chronic hepatitis, not elsewhere classified
K74
Fibrosis and cirrhosis of liver
K75
Other inflammatory liver disease
K76
Other disease of liver
K77
Liver disorders in disease classified elsewhere
F10.1-F10.9
Alcohol dependence syndrome/Mental and behavioural disorders due to use of
alcohol: dependence syndrome
I85.00
Oesophageal varices with bleeding
I86.4A
Gastric varices with bleeding
I85.9
Oesophageal varices without mention of bleeding
I86.4
Gastric varices without mention of bleeding
I98.2
I98.3
Oesophageal varices in diseases classified elsewhere/Secondary oesophageal varices 
with bleeding
K29.2
Alcoholic gastritis

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ICD-10 code
Description
Z65.8 
Personal history of alcoholism/Other specified problems related to psychosocial 
circumstances
K85.2
Alcohol-induced acute pancreatitis
K86.0
Alcohol-induced chronic pancreatitis
E24.4
Alcohol-induced pseudo-Cushing’s syndrome
G31.2
Degeneration of nervous system due to alcohol
G62.1, G72.1
Alcoholic polyneuropathy; Alcoholic myopathy
I42.6
Alcoholic cardiomyopathy
Z50.2
Alcohol rehabilitation
Z71.4
Alcohol abuse counselling and surveillance
Infectious hepatitis (For ALI primary outcome, the lookback period is ever before or at the index date. For 
ALI secondary outcome, the lookback period is 6 months before or at the index date)
B15—B19, B26.8, 
A51.4, Z22.5, 
B25.1, 
(B00.8+K77.0), 
B58.1, B65.x, 
A52.7
Acute infectious hepatitis; Mumps hepatitis; Secondary syphilitic hepatitis; Other 
symptomatic late syphilis; Schistosomiasis; Toxoplasma hepatitis; Carrier or 
suspected carrier of viral hepatitis; Personal history of hepatitis/Other secondary 
hepatitis; Cytomegaloviral hepatitis; Herpes viral hepatitis
Chronic disease involving the liver or causing hyperbilirubinaemia (For ALI primary outcome, the 
lookback period is ever before or at the index date)
E83.1
Haemochromatosis
E83.0
Wilson’s disease
E88.0
Deficit of alpha-1-antitrypsin
I82.0
Budd-Chiari syndrome
E80.4, E80.5, 
E80.6, E80.7
Disorders of bilirubin excretion (Gilbert syndrome)
Biliary disease (For ALI primary outcome, the lookback period is ever before or at the index date. For ALI 
secondary outcome, the lookback period is 6 months before or at the index date)
K80
Cholelithiasis
K81
Cholecystitis
K82
Other diseases of gallbladder
K83
Other diseases of biliary tract
K87.0
Disorders of gallbladder and biliary tract in diseases classified elsewhere
Pancreatic diseases (For ALI primary outcome, the lookback period is ever before or at the index date. For 
ALI secondary outcome, the lookback period is 6 months before or at the index date)
K85
Acute pancreatitis
K86
Other diseases of pancreas
K87.1
Disorders of pancreas in diseases classified elsewhere

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ICD-10 code
Description
Hepatobiliary and pancreatic neoplasms (For ALI primary outcome, the lookback period is ever before or 
at the index date. For ALI secondary outcome, the lookback period is 6 months before or at the index date)
C22
Malignant neoplasm of liver and intrahepatic bile ducts
C23
Malignant neoplasm of gallbladder
C24
Malignant neoplasm of other and unspecified parts of biliary tract
Heart failure (For ALI primary outcome, the lookback period is ever before or at the index date. For ALI 
secondary outcome, the lookback period is 6 months before or at the index date)
I50.x, I13.0, I13.2, 
I11.0, I09.81, 
Heart failure, hypertensive heart, and chronic kidney disease with heart failure
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.
Annex 3 Table 2
Kidney injury exclusion criteria: ICD-10 codes
ICD-10 code
ICD-10 term
N00
Acute nephritic syndrome
N10
Acute tubulo-interstitial nephritis
N12
Tubulo-interstitial nephritis, not specified as acute or chronic
N14
Drug- and heavy-metal-induced tubule-interstitial and tubular conditions
N17
Acute kidney injury
N19
Unspecified kidney failure
T86.1
Kidney transplant failure and rejection
Y84.1
Kidney dialysis
Z49
Care involving dialysis
Z94.0
Kidney transplant status
Z99.2
Dependence on renal dialysis
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.

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Annex 3 Table 3
Prior chronic kidney disease exclusion criteria: ICD-10 codes
Read code
Description
N18
Chronic kidney disease
Q61
Cystic kidney disease
Z94.0
Kidney transplant status
C64
Malignant neoplasm of kidney, except renal pelvis
C65
Malignant neoplasm of renal pelvis
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.
Annex 3 Table 4
Prior chronic pyelonephritis exclusion criteria: ICD-10 codes
Read code
Description
N11
Chronic tubulo-interstitial nephritis (including N11.0 Nonobstructive reflux-associated chronic 
pyelonephritis, N11.1 Chronic obstructive pyelonephritis, N11.8 Other chronic tubulo-interstitial 
nephritis, and N11.9 Chronic tubulo-interstitial nephritis, unspecified)
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.

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ANNEX 4. CODES TO DEFINE STUDY OUTCOMES
ICD-10 codes are used in the three data sources. The list of Read codes (and SNOMED, and 
EMIS local codes, if needed) to be used in the CPRD and ICD-9 codes to be used the HIRD 
will be generated based on the common ICD-10 list and described in the statistical analysis 
plan.
Annex 4 Table 1
Acute liver injury, ICD-10 codes
ICD-10 code
ICD-10 term
K71.1
Toxic liver disease with hepatic necrosis 
K71.2
Toxic liver disease with acute hepatitis
K71.6
Toxic liver disease with hepatitis, not elsewhere classified
K71.9
Toxic liver disease, unspecified
K72.0
Acute and subacute hepatic failure 
K72.9
Hepatic failure, unspecified
K76.8
Other specified diseases of liver
K76.9
Liver disease, unspecified
R17
Unspecified jaundice, excludes neonatal
Z94.4
Liver transplant
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at:
http://apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.
Annex 4 Table 2
Acute liver injury and biochemistry tests, Read codes
Read code/ 
biochemistry 
test (enttype)
Description
Enttype=155
Alanine aminotransferase
Enttype=156
Aspartate aminotransferase
Enttype=158
Bilirubin
1675
Yellow/jaundiced colour
1675.11
Jaundice - symptom
2274
O/E - jaundiced colour
2274.11
O/E - jaundiced
7806
Therapeutic endoscopic operations on liver using laparoscope
7807
Diagnostic endoscopic examination of liver using laparoscope
7800111
Auxiliary liver transplant

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Read code/ 
biochemistry 
test (enttype)
Description
7800112
Piggy back liver transplant
7800500
Orthotopic transplantation of liver NEC
7804200
Open wedge biopsy of lesion of liver
7805211
Exploration of liver transplant
7807000
Diagnostic laparoscopic examination and biopsy liver lesion
7807100
Laparoscopic ultrasound examination liver biopsy lesion liver
7807200
Laparoscopic ultrasound examination of liver NEC
44CU.00
Plasma alkaline phosphatase level
44D2.00
Liver function tests abnormal
44E.00
Serum bilirubin level
44E2.00
Serum bilirubin raised
44E6.00
Serum bilirubin borderline
44G2.00
Liver enzymes abnormal
44G3100
ALT/SGPT level abnormal
44H5100
AST/SGOT level abnormal
44H5200
AST/SGOT level raised
46R5.11
Bilirubin in urine
7800z00
Transplantation of liver NOS
7807y00
Diagnostic laparoscopic examination of liver OS
7807z00
Diagnostic laparoscopic examination of liver NOS
780A.00
Diagnostic percutaneous operations on liver
780A000
Percutaneous transvascular biopsy of lesion of liver
780A100
Percutaneous biopsy of lesion of liver NEC
780A111
Menghini needle biopsy of liver
780A112
Needle biopsy of liver NEC
780A113
Sheeba needle biopsy of liver
780Az00
Diagnostic percutaneous operation on liver NOS
780B000
Biopsy of liver NEC
780B011
Biopsy of lesion of liver NEC
780F000
Endoscopic ultrasound examination liver biopsy lesion liver
9N0v.00
Seen in liver clinic
J60.00
Acute and subacute liver necrosis

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Read code/ 
biochemistry 
test (enttype)
Description
J600.00
Acute necrosis of liver
J600000
Acute hepatic failure
J600011
Acute liver failure
J600100
Acute hepatitis – non-infective
J600200
Acute yellow atrophy
J600z00
Acute necrosis of liver NOS
J601.00
Subacute necrosis of liver
J601000
Subacute hepatic failure
J601100
Subacute hepatitis – non-infective
J601200
Subacute yellow atrophy
J601z00
Subacute necrosis of liver NOS
J60z.00
Acute and subacute liver necrosis NOS
J622.00
Hepatic coma
J622.11
Encephalopathy - hepatic
J625.00
[X] Hepatic failure
J625.11
[X] Liver failure
J62y.11
Hepatic failure NOS
J62y.12
Liver failure NOS
J62y.13
Hepatic failure
J63.00
Other liver disorders
J633.00
Hepatitis unspecified
J633000
Toxic hepatitis
J633z00
Hepatitis unspecified NOS
J635.00
Toxic liver disease
J635000
Toxic liver disease with cholestasis
J635100
Toxic liver disease with hepatic necrosis
J635200
Toxic liver disease with acute hepatitis
J635700
Acute hepatic failure due to drugs
J635X00
Toxic liver disease, unspecified
J636.00
Central haemorrhagic necrosis of liver
J63y.00
Other specified liver disorder
J63y100
Non-specific reactive hepatitis

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Read code/ 
biochemistry 
test (enttype)
Description
J63yz00
Other specified liver disorder NOS
J63z.00
Liver disorder NOS
J66y600
Obstructive jaundice NOS
R024.00
[D] Jaundice (not of newborn)
R024000
[D] Cholemia NOS
R024100
[D] Icterus NOS
R024111
[D] Jaundice
R024z00
[D] Jaundice (not of newborn) NOS
R104000
[D] Transaminase or lactic acid dehydrogenase raised
R104013
[D] Transaminase raised
R104200
[D] Alkaline phosphatase raised
R148.00
[D] Abnormal liver function test
R148.11
[D] LFTs abnormal
R148z00
[D] Abnormal liver function test NOS
ZV42700
[V] Liver transplanted
ZV7C000
[V] Assessment for liver transplant
ALT = alanine aminotransferase; AST = aspartate aminotransferase; LFT = liver function tests; NEC = not elsewhere 
classified; NOS = not otherwise specified; O/E = on examination; OS = otherwise specified; SGOT = serum glutamic 
oxaloacetic transaminase; SGPT = serum glutamic pyruvic transaminase.
Sources: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines 
and Health Products Regulatory Agency, United Kingdom, April 2014. Accessed 15 October 2014.

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Annex 4 Table 3
Acute kidney injury, ICD-10 codes
ICD-10 code
ICD-10 term
N00
Acute nephritic syndrome
N10
Acute tubulo-interstitial nephritis
N12
Tubulo-interstitial nephritis, not specified as acute or chronic
N14
Drug- and heavy-metal-induced tubule-interstitial and tubular conditions
N17
Acute renal failure
N19
Unspecified kidney failure
T86.1
Kidney transplant failure and rejection
Y84.1
Kidney dialysis
Z49
Care involving dialysis
Z94.0
Kidney transplant status
Z99.2
Dependence on renal dialysis
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at:
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.
Annex 4 Table 4
Acute kidney injury, Read codes
Read code
Description
K00.00
Acute glomerulonephritis
K00.11
Acute nephritis
K000.00
Acute proliferative glomerulonephritis
K001.00
Acute nephritis with lesions of necrotising glomerulitis
K00y100
Acute exudative nephritis
K00y200
Acute focal nephritis
K00y300
Acute diffuse nephritis
K00z.00
Acute glomerulonephritis NOS
K04.00
Acute renal failure
K040.00
Acute renal tubular necrosis
K041.00
Acute renal cortical necrosis
K042.00
Acute renal medullary necrosis
K042.11
Necrotising renal papillitis
K043.00
Acute drug-induced renal failure
K044.00
Acute renal failure due to urinary obstruction
K04y.00
Other acute renal failure
K04z.00
Acute renal failure NOS

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Read code
Description
14V2.00
H/O: renal dialysis
14V2.11
H/O: kidney dialysis
7L1A.00
Compensation for renal failure
7L1A.11
Dialysis for renal failure
7L1A000
Renal dialysis
7L1A011
Thomas intravascular shunt for dialysis
7L1Ay00
Other specified compensation for renal failure
7L1Az00
Compensation for renal failure NOS
ZV45100
[V] Renal dialysis status
ZV56.00
[V] Aftercare involving intermittent dialysis
ZV56000
[V] Aftercare involving extracorporeal dialysis
ZV56011
[V] Aftercare involving renal dialysis NOS
ZV56100
[V] Preparatory care for dialysis
ZV56y00
[V] Other specified aftercare involving intermittent dialysis
ZV56y11
[V] Aftercare involving peritoneal dialysis
ZV56z00
[V] Unspecified aftercare involving intermittent dialysis
ZVu3G00
[X] Other dialysis
K0D.00
End-stage renal disease
7L1A200
Haemodialysis NEC
7L1A300
Haemofiltration
7L1A700
Haemoperfusion
K06.00
Renal failure unspecified
K06.11
Uraemia NOS
K060.00
Renal impairment
K060.11
Impaired renal function
Kyu2000
[X] Other acute renal failure
G500400
Acute pericarditis - uraemic
7L1A100
Peritoneal dialysis
7L1A400
Automated peritoneal dialysis
7L1A500
Continuous ambulatory peritoneal dialysis
7L1A600
Peritoneal dialysis NEC
14S2.00
H/O: kidney recipient
7B00.00
Transplantation of kidney
7B00000
Autotransplant of kidney

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Read code
Description
7B00100
Transplantation of kidney from live donor
7B00111
Allotransplantation of kidney from live donor
7B00200
Transplantation of kidney from cadaver
7B00211
Allotransplantation of kidney from cadaver
7B00300
Allotransplantation of kidney from cadaver, heart-beating
7B00400
Allotransplantation kidney from cadaver, heart non-beating
7B00500
Allotransplantation of kidney from cadaver NEC
7B00y00
Other specified transplantation of kidney
7B00z00
Transplantation of kidney NOS
ZV42000
[V] Kidney transplanted
H/O = history of; NEC = not elsewhere classified; NOS = not otherwise specified.
Source: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines and 
Health Products Regulatory Agency, United Kingdom, April 2014. Accessed 15 October 2014.
Annex 4 Table 5
Chronic kidney disease, ICD-10 codes
ICD-10 code
ICD-10 term
E132
Other specified diabetes mellitus with incipient diabetes nephropathy adequately or
inadequately controlled by insulin, diet, or oral agents
I12
Hypertensive renal disease
I13
Hypertensive renal and heart disease
N08
Glomerular disorders in diseases classified elsewhere
N18
Chronic renal failure
Source: Fleet et al. (2013) [R15-3138].

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Annex 4 Table 6
Chronic kidney disease, Read codes
Read code
Read term
1Z12.00
Chronic kidney disease stage 3
K05.00
Chronic renal failure
1Z13.00
Chronic kidney disease stage 4
1Z1.00
Chronic renal impairment
9hE0.00
Except chronic kidney disease qual indic: Patient unsuitable
K060.00
Renal impairment
66i.00
Chronic kidney disease monitoring
K06.00
Renal failure unspecified
1Z14.00
Chronic kidney disease stage 5
9Ot0.00
Chronic kidney disease monitoring first letter
K08.00
Impaired renal function disorder
6AA.00
Chronic kidney disease annual review
K060.11
Impaired renal function
1Z1C.00
Chronic kidney disease stage 3 without proteinuria
9Ot.00
Chronic kidney disease monitoring administration
9hE1.00
Exc chronic kidney disease quality indicators: Inform dissen
K050.00
End-stage renal failure
7L1A200
Haemodialysis NEC
7L1A.11
Dialysis for renal failure
9hE.00
Exception reporting: chronic kidney disease quality indicator
7A60100
Creation of arteriovenous fistula NEC
7L1A100
Peritoneal dialysis
K08z.00
Impaired renal function disorder NOS
K06.11
Uraemia NOS
14V2.00
H/O: renal dialysis
4519.00
Deteriorating renal function
D215000
Anaemia secondary to chronic renal failure
D215.00
Anaemia secondary to renal failure
7L1B000
Insertion of ambulatory peritoneal dialysis catheter
1Z1B.00
Chronic kidney disease stage 3 with proteinuria
1Z15.00
Chronic kidney disease stage 3A
8L50.00
Renal transplant planned

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Read code
Read term
7L1A000
Renal dialysis
K05.11
Chronic uraemia
K0D.00
End-stage renal disease
G22.11
Nephrosclerosis
ZV45100
[V] Renal dialysis status
7L1B100
Removal of ambulatory peritoneal dialysis catheter
1Z16.00
Chronic kidney disease stage 3B
1Z1E.00
Chronic kidney disease stage 3A without proteinuria
1Z1J.00
Chronic kidney disease stage 4 without proteinuria
1Z1H.00
Chronic kidney disease stage 4 with proteinuria
SP08300
Kidney transplant failure and rejection
1Z1G.00
Chronic kidney disease stage 3B without proteinuria
SP05613
[X] Peritoneal dialysis associated peritonitis
H/O = history of; NEC = not elsewhere classified; NOS = not otherwise specified.
Source: Denburg et al. (2011) [R15-3136].
Annex 4 Table 7
Pyelonephritis and sepsis, ICD-10 codes
ICD-10 code
Description
A40
Streptococcal sepsis
A41
Other sepsis
N10
Acute tubule-interstitial nephritis
N13.6
Pyonephrosis
N20
Calculus of kidney and ureter
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
http://apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.

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Annex 4 Table 8
Pyelonephritis and sepsis, Read codes
Read code
Description
Pyelonephritis
K101.00
Acute pyelonephritis
K10y000
Pyelonephritis unspecified
K101z00
Acute pyelonephritis NOS
K100600
Calculous pyelonephritis
K10yz00
Unspecified pyelonephritis NOS
K10y.00
Pyelonephritis and pyonephrosis unspecified
K10y000
Pyelonephritis unspecified
K10y100
Pyelitis unspecified
K10y200
Pyonephrosis unspecified
K10y400
Pyelitis in diseases EC
K101000
Acute pyelonephritis without medullary necrosis
K101200
Acute pyelitis
K101300
Acute pyonephrosis
K10y300
Pyelonephritis in diseases elsewhere classified
K103.00
Pyeloureteritis cystica
K106.00
Candida pyelonephritis
Sepsis
A38z.11
Sepsis
A3C.00
Sepsis
K190600
Urosepsis
J666.00
Biliary sepsis
L090y00
Sepsis NOS following abortion/ectopic/molar pregnancy
Q404z00
Umbilical sepsis NOS
L40.11
Sepsis - puerperal
A3Cy.00
Other specified sepsis
A3Cz.00
Sepsis NOS
A3C3.00
Sepsis due to Gram-negative bacteria
A3C0100
Sepsis due to Streptococcus group B
AB2y500
Candidal sepsis
A3C0300
Sepsis due to Streptococcus pneumoniae
A3C1.00
Sepsis due to Staphylococcus

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Read code
Description
A3C2.11
Sepsis due to anaerobes
A270611
Listerial sepsis
A3C1000
Sepsis due to Staphylococcus aureus
A3C0000
Sepsis due to Streptococcus group A
A3C0.00
Sepsis due to Streptococcus
A023.00
Salmonella sepsis
A3C0y00
Other streptococcal sepsis
A396.00
Sepsis due to Actinomyces
A3C2.00
Sepsis due to anaerobic bacteria
A3C3y00
Sepsis due to other Gram-negative organisms
A270600
Sepsis due to Listeria monocytogenes
A3C0z00
Streptococcal sepsis, unspecified
AB2y511
Sepsis due to Candida
EC = elsewhere classified; NOS = not otherwise specified.
Source: Medical and product dictionary browsers, version 1.3. London: General Practice Research Database (now the 
CPRD); March 2010. Accessed 15 October 2014.
Annex 4 Table 9
Urinary tract infections, ICD-10 codes
ICD-10 code
Description
N30
Cystitis
N34
Urethritis and urethral syndrome
N37.0
Urethritis in diseases classified elsewhere
N39.0
Urinary tract infection, site not specified
N41
Inflammatory diseases of prostate
O23.2
Infections of urethra in pregnancy
O23.4
Unspecified infection of urinary tract in pregnancy
O23.5
Infections of the genital tract in pregnancy
O23.9
Other and unspecified genitourinary tract infections in pregnancy
O86.2
Urinary tract infection following delivery
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.

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Annex 4 Table 10
Urinary tract infections, Read codes
Read code
Description
K190z00
Urinary tract infection, site not specified NOS
K15.00
Cystitis
K190.00
Urinary tract infection, site not specified
1AG.00
Recurrent urinary tract infections
K150.00
Acute cystitis
K190.11
Recurrent urinary tract infection
K17y000
Urethritis unspecified
A994.00
Non-specific urethritis
K190300
Recurrent urinary tract infection
K190500
Urinary tract infection
K15z.00
Cystitis NOS
L166800
Urinary tract infection complicating pregnancy
L166.00
Genitourinary tract infections in pregnancy
K17.00
Urethritis due to non-venereal causes
K171.00
Postmenopausal atrophic urethritis
L166z11
UTI - urinary tract infection in pregnancy
K190400
Chronic urinary tract infection
L166600
Urinary tract infection following delivery
L166300
Genitourinary tract infection in pregnancy - not delivered
L166.11
Cystitis of pregnancy
L166z00
Genitourinary tract infection in pregnancy NOS
K17z.00
Urethritis due to non-venereal cause NOS
K17y.00
Other urethritis
L166000
Genitourinary tract infection in pregnancy unspecified
K17yz00
Other urethritis NOS
Kyu5500
[X] Other urethritis
L166100
Genitourinary tract infection in pregnancy - delivered
Kyu5100
[X] Other cystitis
K21.11
Prostatitis and other inflammatory diseases of prostate

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Read code
Description
K211.00
Chronic prostatitis
K210.00
Acute prostatitis
K21z.00
Prostatitis NOS
NOS = not otherwise specified; UTI = urinary tract infection.
Source: Medical and product dictionary browsers, version 1.3. London: General Practice Research Database (now the 
CPRD); March 2010. Accessed 15 October 2014.
Annex 4 Table 11
Genital infections, ICD-10 codes
ICD-10 code
Description
Vulvovaginitis
B37.3
Candidiasis of vulva and vagina
B37.4
Candidiasis of other urogenital sites
N77.1
Vaginitis, vulvitis and vulvovaginitis in infectious and parasitic diseases classified 
elsewhere
N76
Other inflammation of vagina and vulva (includes vaginitis, vulvitis, etc…) 
Additional codes (B95-B98) are used to identify infectious agent
Balanitis
N48.1
Balanoposthitis (additional codes (B95-B98) are used to identify infectious agent)
N51.2
Balanitis in diseases classified elsewhere
B37.4
Candidiasis of other urogenital sites
Complications of GI or severe consequences of GI
N77.0
Ulceration of vulva in infectious and parasitic diseases classified elsewhere
N77.8
Vulvovaginal ulceration and inflammation in other diseases classified elsewhere
N48.2
Other inflammatory disorders of penis, including the following conditions:
Abscess of corpus cavernosum and penis
Boil of corpus cavernosum and penis
Carbuncle of corpus cavernosum and penis
Cellulitis of corpus cavernosum and penis
Cavernitis (penis)
Additional codes (B95-B98) are used to identify infectious agent.
N49.8
Inflammatory disorders of other specified male genital organs
Inflammation of multiple sites in male genital organs (includes Fournier’s gangrene)

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ICD-10 code
Description
Exclude case of vulvovaginitis or balanitis if any of the following is present 30 days before or after the 
index diagnosis code:
A06.8
Amoebic infection of other sites 
A50-A64
Infections with a predominantly sexual mode of transmission (includes syphilis, 
gonococci, chlamydia, trichomonas, herpetic, and other)
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at: 
website: apps.who.int/classifications/icd10/browse/2010/en. Accessed 15 October 2014.
Annex 4 Table 12
Vulvovaginitis, Read codes
Read code
Description
“Specific diagnosis” of bacterial vaginosis or Candida vulvovaginitis
A3By700
Gardnerella vaginalis
AB21.00
Candidal vulvovaginitis
AB21.11
Monilial vulvovaginitis
AB21000
Candidiasis of vulva
AB21100
Candidiasis of vagina
AB21111
Vaginal thrush
AB22.00
Other urogenital candidiasis
AB21z00
Candidal vulvovaginitis NOS
K421900
Bacterial vaginitis
K421911
Bacterial vaginosis
Specific microbiology results
4JK2300
HVS culture - Gardnerella vaginalis
4JK2400
High vaginal swab: fungal organism isolated
4J74.11
Fungus on microscopy
4KE0.00
Clue cells present
4KE.00
Clue cells
Non-specific positive microbiology results
4JK2500
High vaginal swab: white cells seen
4JK7.00
Vaginal swab culture positive
4JK2000
High vaginal swab culture positive
4KA2.00
Vaginal vault smear inadequate
4KA4.00
Vaginal vault smear abnormal

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Read code
Description
Non-specific diagnosis of vulvovaginitis
K421.00
Vaginitis and vulvovaginitis
K421000
Vaginitis unspecified
K421100
Vulvitis unspecified
K421200
Vulvovaginitis unspecified
K421400
Vaginitis in diseases EC
K421500
Vulvitis in diseases EC
K421600
Vulvovaginitis in diseases EC
K421A00
Acute vulvitis
K421z00
Vaginitis and vulvovaginitis NOS
Complications of GI or severe consequences of GI
K421111
Vulval sores
K423.00
Abscess of Bartholin’s gland
K423.11
Vulvovaginal gland abscess
K424.00
Other abscess of vulva
K424000
Abscess of vulva
K424011
Abscess of labia
K424100
Carbuncle of vulva
K424111
Boil of vulva
K424200
Furuncle of vulva
K424z00
Other abscess of vulva NOS
K425.00
Ulceration of vulva
K425000
Ulceration of vulva unspecified
K425200
Ulceration of vulva in Behcet’s disease
K425z00
Ulceration of vulva NOS
K42y000
Carbuncle of vagina
K42y100
Carbuncle of labium
K42y200
Ulcer of vagina
Kyu8500
[X]Vaginits,vulvits+vulvovaginitis/infect+parasitc diseas CE
Kyu8600
[X]Vulvovaginal ulceration+inflammation in other diseases CE
EC = elsewhere classified; HVS = high vaginal swab; NOS = not otherwise specified.
Source: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines and 
Health Products Regulatory Agency, United Kingdom, April 2014. Accessed 15 October 2014.

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Annex 4 Table 13
List of diagnoses and corresponding Read codes and terms 
suggestive of sexually transmitted infection to be used to 
exclude vulvovaginitis cases
Read code
Read term
4JK2200
HVS culture - trichomonas vaginalis
43U8.00
Chlamydia test positive
K5A3.11
Senile (atrophic) vaginitis
A78A.00
Chlamydial infection
A98z.11
Gonorrhoea
K420900
Chlamydia cervicitis
A541100
Herpetic vulvovaginitis
AD10111
Trichomonal vaginitis
AD10100
Trichomonal vulvovaginitis
Ayu4L00
[X] Vulval warts
43U1.00
Chlamydia antigen ELISA positive
A78A000
Chlamydial infection of lower genitourinary tract
A78AX00
Chlamydial infection of genitourinary tract, unspecified
K5A5.00
Perimenopausal atrophic vaginitis
A78A500
Chlamydial infection of genital organs NEC
A541200
Herpetic ulceration of vulva
4JQA.00
Gonorrhoea test positive
A980.00
Acute gonorrhoea of lower genitourinary tract
Ayu6200
[X] Chlamydial infection, unspecified
A980z00
Acute gonorrhoea of lower genitourinary tract NOS
Ayu4D00
[X] Sexually transmitted chlamydial infection of other sites
A980200
Acute gonococcal vulvovaginitis
Ayu4K00
[X] Chlamydial infection of genitourinary tract, unspecified
A78A300
Chlamydial inf of pelviperitoneum oth genitourinary organs
Kyu8500
[X] Vaginitis, vulvitis + vulvovaginitis/infect + parasitic diseas CE
A982200
Chronic gonococcal vulvovaginitis
A982.00
Chronic gonorrhoea lower genitourinary tract
Ayu6100
[X] Other chlamydial diseases
A981z00
Acute gonorrhoea upper genitourinary tract NOS
A981.00
Acute gonorrhoea of upper genitourinary tract

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Read code
Read term
A913500
Secondary syphilis of vulva
Kyu8400
[X] Ulceration of vulva in infectious + parasitic diseases CE
A983.00
Chronic gonorrhoea of upper genitourinary tract
A982z00
Chronic gonorrhoea of lower genitourinary tract NOS
K421300
Postirradiation vaginitis
K5A3.00
Postmenopausal atrophic vaginitis
A980200
Acute gonococcal vulvovaginitis
Ayu4K00
[X] Chlamydial infection of genitourinary tract, unspecified
A78A300
Chlamydial inf of pelviperitoneum oth genitourinary organs
Kyu8500
[X] Vaginitis, vulvitis + vulvovaginitis/infect + parasitic diseas CE
A982200
Chronic gonococcal vulvovaginitis
CE = classified elsewhere, EC = elsewhere classified; ELISA = enzyme amplified immunoassay; HVS = high vaginal swab;
NEC = not elsewhere classified; NOS = not otherwise specified.
Source: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines and 
Health Products Regulatory Agency, United Kingdom, April 2014. Accessed 15 October 2014.
Annex 4 Table 14
Balanitis, Read codes
Read code
Description
K272.11
Infection of penis
K271z00
Balanoposthitis NOS
K271100
Posthitis
K271000
Balanitis
K271.11
Balanitis
K271.00
Balanoposthitis
AB22000
Candidal balanitis
2663.11
O/E - discharge - penis
Kyu6A00
[X] Balanitis in diseases classified elsewhere
AB22011
Penile candidiasis (thrush)
4JK8000
Penile swab culture positive
Complications of GI or severe consequences of GI
K272000
Penile abscess
K272100
Penile boil

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Read code
Description
K272200
Penile carbuncle
K272300
Cellulitis of penis
K284600
Fournier’s gangrene of scrotum
GI = genital infections; NOS = not otherwise specified; O/E = on examination.
Source: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines and 
Health Products Regulatory Agency, United Kingdom, April 2014. Accessed 15 October 2014.
Annex 4 Table 15
List of diagnoses and corresponding Read codes and terms 
suggestive of sexually transmitted infection that will be used to
exclude balanitis cases
Read code
Description
K271200
Zoon’s balanitis
A78A000
Chlamydial infection of lower genitourinary tract
A78AX00
Chlamydial infection of genitourinary tract, unspecified
A78A500
Chlamydial infection of genital organs NEC
A541300
Herpetic infection of penis
K274.11
Balanitis xerotica obliterans
A060.00
Balantidiasis
A980.00
Acute gonorrhoea of lower genitourinary tract
A980z00
Acute gonorrhoea of lower genitourinary tract NOS
A05y100
Amoebic balanitis
A982z00
Chronic gonorrhoea of lower genitourinary tract NOS
A781212
Penile warts
A78A.00
Chlamydial infection
A98z.11
Gonorrhoea
4JQA.00
Gonorrhoea test positive
Ayu4D00
[X] Sexually transmitted chlamydial infection of other sites
A78A300
Chlamydial inf of pelviperitoneum oth genitourinary organs
Ayu4K00
[X] Chlamydial infection of genitourinary tract, unspecified
NEC = not elsewhere classified; NOS = not otherwise specified.
Source: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines and 
Health Products Regulatory Agency, United Kingdom, April 2014. Accessed 15 October 2014.

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Annex 4 Table 16
Diabetic ketoacidosis, ICD-10 codes
ICD-10 code
Description
E11.1
Type 2 diabetes mellitus, with ketoacidosis
E12.1
Malnutrition-related diabetes mellitus, with ketoacidosis
E13.1
Other specified diabetes mellitus, with ketoacidosis
E14.1
Unspecified diabetes mellitus, with ketoacidosis
E11.0
Type 2 diabetes mellitus, with coma
E12.0
Malnutrition-related diabetes mellitus, with coma
E13.0
Other specified diabetes mellitus, with coma
E14.0
Unspecified diabetes mellitus, with coma
Source: International Statistical Classification of Diseases and Related Health Problems 10th Revision. Available at:
http://apps.who.int/classifications/icd10/browse/2010/en. Accessed 16 March 2016.
Annex 4 Table 17
Diabetic ketoacidosis, Read codes
Read code
Description
C362700
Ketoacidaemia NEC
C362600
Metabolic ketoacidaemia
C10FP11
Type II diabetes mellitus with ketoacidotic coma
C10FP00
Type 2 diabetes mellitus with ketoacidotic coma
C10FN11
Type II diabetes mellitus with ketoacidosis
C10FN00
Type 2 diabetes mellitus with ketoacidosis
C10A100
Malnutrition-related diabetes mellitus with ketoacidosis
C103z00
Diabetes mellitus NOS with ketoacidotic coma
C103100
Diabetes mellitus, adult onset, with ketoacidotic coma
C103.00
Diabetes mellitus with ketoacidotic coma
C101z00
Diabetes mellitus NOS with ketoacidosis
C101y00
Other specified diabetes mellitus with ketoacidosis
C101100
Diabetes mellitus, adult onset, with ketoacidosis
C101.00
Diabetes mellitus with ketoacidosis
NEC = not elsewhere classified; NOS = not otherwise specified.
Source: CPRD Medical and Product Dictionary Browsers, version 1.4.0. Clinical Practice Research Datalink, Medicines and 
Health Products Regulatory Agency, United Kingdom, February 2016. Accessed 16 March 2016.

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ANNEX 5. COVARIATES TO BE CONSIDERED FOR INCLUSION IN 
THE PROPENSITY SCORE MODEL, BY OUTCOME
HOSPITALISATION, ED VISIT, OR SPECIALIST VISIT FOR ACUTE LIVER 
INJURY
Annex 5 Table 1
Acute liver injury outcome: variables of interest to be collected 
for propensity score development
Demographic or lifestyle
Age
Sex
Calendar year of index date
Duration of lookback time
Body mass index > 30 or obesity surgery
Smoking history
Alcohol consumption
History of alcohol abuse
Socioeconomic status: Index of multiple socioeconomic 
deprivation, quintiles: first least deprived, fifth most 
deprived 
Medications
Drugs associated with liver injury 1
Acarbose
Acetaminophen (prescription)
Allopurinol
Amiodarone
Amitriptyline
Amoxicillin + clavulanic acid
Anabolic steroids
Azathioprine
Baclofen
Bupropion
Captopril
Carbamazepine
Chlorpromazine
Clindamycin
Clopidogrel
Cyproheptadine
Enalapril
Erythromycins
Estrogens
Fluoxetine
Flutamide
HAART drugs
Irbesartan
Isoniazid
Ketoconazole
Lisinopril
Losartan
Methotrexate
Mirtazapine
Nitrofurantoin
NSAIDs
Omeprazole
Oral contraceptives
Paroxetine
Phenobarbital
Phenothiazines
Phenytoin
Pyrazinamide
Rifampicin
Risperidone
Sertraline
Statins
Sulfonamides
Terbinafine
Tetracyclines
Trazodone
Trazodone
Tricyclics
Trimethoprim-sulfamethoxazole
Trovafloxacin
Valproic acid
Verapamil

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Other medications
Cardiovascular system drugs
Lipid-modifying agents
Other antirheumatic agents
Hormone-replacement therapy
Insulins
Other oral antidiabetic drugs
(including specification of add-
on or switch)
Antiepileptics
Drugs for asthma and obstructive 
airways disease
Systemic corticosteroids
Systemic tacrolimus
Azathioprine
Methotrexate
Cyclosporin
Other immunosuppressants 
excluding systemic tacrolimus
Systemic antivirals
Other antimicrobials
Medical comorbidities
Ischaemic heart disease
Hypertensive disease
Heart failure
Peripheral vascular disease
Other cardiovascular disease
Cerebrovascular disease
Hyperlipidaemia
Autoimmune disease
Asthma
Chronic obstructive pulmonary 
disease, emphysema, respiratory 
insufficiency
Diffuse diseases of connective 
tissue
Rheumatoid arthritis
Osteoarthrosis
Polymyalgia rheumatica
Renal insufficiency
Other malignancies
Dementia
Peptic ulcer disease
Colon polyps
Crohn’s disease
Ulcerative colitis
Pancreatitis
Urinary infections (chronic or 
recurring)
Immunosuppressive diseases such 
as human immunodeficiency 
virus infection/AIDS
Being hospitalised, especially for 
a serious condition that requires 
intensive care
Length of hospitalisation
Chronic disease score 2
Indicators of diabetes severity
Renal insufficiency or diabetic 
nephropathy
Retinopathy
Neuropathy
Peripheral vascular disease
Coronary heart disease
Cerebrovascular disease
Amputations
Time since first diagnosis of type 2 diabetes mellitus 
HAART = highly active antiretroviral therapy; NSAIDs = non-steroidal anti-inflammatory drugs.
1.
Source: Navarro and Senior, 2006.
2.
For example, scores like the ones developed by Elixhauser et al. [R13-3591] or Charlson/Deyo [R13-3589] to be 
specified in analysis plan.

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HOSPITALISATION, ED VISIT, OR SPECIALIST VISIT FOR ACUTE KIDNEY 
INJURY
Annex 5 Table 2
Acute kidney injury outcome: variables of interest to be 
collected for propensity score development
Demographic or lifestyle
Medications
Age
Sex
Calendar year of index date
Duration of lookback time
Body mass index > 30 or obesity surgery
Smoking history
History of alcohol abuse
Socioeconomic status: index of multiple 
socioeconomic deprivation, quintiles–
first least deprived to fifth most 
deprived 
Antihypertensives, diuretics including angiotensin-converting enzyme 
inhibitors/angiotensin II receptor blockers, beta blockers, calcium-
channel blockers, other antihypertensives, antiarrhythmics, digoxin, 
nitrates
NSAIDs (non-steroidal anti-inflammatory drugs)
Statins, fibrates
Oral steroids
Zoledronic acid
Lipid-modifying agents
Other: acetaminophen, antibiotics (penicillins, sulfa), anticonvulsants, 
antifungals, antituberculars, chemotherapeutic agents, methotrexate, 
aspirin and other antiplatelets (e.g., clopidogrel, ticlopidine, prasugrel), 
systemic antivirals, anticoagulants
Concomitant antidiabetics (including specification of add-on or switch)
Medical comorbidities
Indicators of diabetes severity 
Prior history of acute kidney injury 
> 6 months before or at the index 
date
Being hospitalised, especially for a 
serious condition that requires 
intensive care
Length of hospitalisation
High blood pressure
Heart failure
Chronic renal disease or renal dialysis
Liver disease
Peripheral artery disease
Chronic disease score 1
Other cardiovascular disease
Autoimmune disease
Chronic obstructive pulmonary 
disease, emphysema, respiratory 
insufficiency
Diffuse diseases of connective tissue
Rheumatoid arthritis
Osteoarthrosis
Polymyalgia rheumatica
Urinary infections (chronic or 
recurring)
Kidney stones
Crohn’s disease
Ulcerative colitis
Pancreatitis
Immunosuppressive diseases such as 
HIV/AIDS
Peptic ulcer disease
Dementia
Asthma
Renal insufficiency or diabetic 
nephropathy, peripheral
Retinopathy
Neuropathy
Peripheral vascular disease
Coronary heart disease
Cerebrovascular disease
Amputations
Time since first diagnosis of type 2
diabetes mellitus, if available 
1.
For example, scores like the ones developed by Elixhauser et al. [R13-3591] or Charlson/Deyo [R13-3589], to be 
specified in analysis plan.

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SEVERE COMPLICATIONS OF URINARY TRACT INFECTION (INPATIENT 
AND OUTPATIENT PYELONEPHRITIS AND UROSEPSIS)
Annex 5 Table 3
Urinary tract infection outcome: variables of interest to be 
collected for propensity score development
Demographic or lifestyle
Medications
Age
Sex
Calendar year of index date
Duration of lookback time
Body mass index > 30 or obesity 
surgery
Smoking history
History of alcohol abuse
Socioeconomic status: Index of 
multiple socioeconomic 
deprivation, quintiles—first least 
deprived to fifth most deprived
Antihypertensives/diuretics including angiotensin-converting enzyme 
inhibitors/angiotensin II receptor blockers, beta blockers, calcium-channel 
blockers, other antihypertensives, antiarrhythmics, digoxin, nitrates
NSAIDs (non-steroidal anti-inflammatory drugs)
Statins, fibrates
Oral steroids
Zoledronic acid
Lipid-modifying agents
Other: acetaminophen, antibiotics (e.g., penicillins, sulfa), anticonvulsants, 
antifungals, antituberculars, chemotherapeutic agents, methotrexate, aspirin 
and other antiplatelets (e.g., clopidogrel, ticlopidine, prasugrel), 
anticoagulants, systemic antivirals
Concomitant antidiabetics (including specification of add-on or switch)
Medical comorbidities
Indicators of diabetes severity 
Prior history of UTI leading to 
hospitalisation or acute 
pyelonephritis > 6 months before 
or at the index date
Being hospitalised, especially for a 
serious condition that requires 
intensive care
Length of hospitalisation
Kidney diseases
Kidney and genitourinary stones 
and disease
Pregnancy
High blood pressure
Heart failure
Liver disease
Other cardiovascular disease
Autoimmune disease
Chronic obstructive pulmonary 
disease, emphysema, respiratory 
insufficiency
Diffuse diseases of connective 
tissue
Rheumatoid arthritis
Osteoarthrosis
Polymyalgia rheumatica
Urinary infections (chronic or 
recurring)
Crohn’s disease
Ulcerative colitis
Pancreatitis
Immunosuppressive diseases such as 
HIV/AIDS
Peptic ulcer disease
Dementia
Asthma
Chronic disease score 1
Renal insufficiency or diabetic 
nephropathy, peripheral
Retinopathy
Neuropathy
Peripheral vascular disease
Coronary heart disease
Cerebrovascular disease
Amputations
Time since first diagnosis of 
type 2 diabetes mellitus,
(CPRD only) 
HIV = human immunodeficiency virus.
1.
For example, scores like the ones developed by Elixhauser et al. (1998) [R13-3591] or Charlson/Deyo [R13-3589], to 
be specified in analysis plan.

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GENITAL INFECTIONS (INPATIENT AND OUTPATIENT)
Annex 5 Table 4
Genital infections outcome: variables of interest to be collected 
for propensity score development
Demographic or lifestyle
Medications
Age
Sex
Calendar year of index date
Duration of lookback time
Body mass index > 30 or obesity 
surgery
Smoking history
History of alcohol abuse
Socioeconomic status: Index of 
multiple socioeconomic deprivation, 
quintiles—first least deprived to fifth 
most deprived
Antihypertensives/diuretics including angiotensin-converting enzyme 
inhibitors/angiotensin II receptor blockers, beta blockers, calcium-
channel blockers, other antihypertensives, antiarrhythmics, digoxin, 
nitrates
NSAIDs (non-steroidal anti-inflammatory drugs)
Statins, fibrates
Oral steroids
Zoledronic acid
Lipid-modifying agents
Other: acetaminophen, antibiotics (e.g., penicillins, sulfa), 
anticonvulsants, antifungals, antituberculars, chemotherapeutic agents, 
methotrexate, aspirin and other antiplatelets (e.g., clopidogrel, 
ticlopidine, prasugrel), anticoagulants, systemic antivirals
Concomitant antidiabetics (including specification of add-on or switch)
Medical comorbidities
Indicators of diabetes severity 
Prior history of genital infection
Being hospitalised, especially for a 
serious condition that requires 
intensive care
Length of hospitalisation
Kidney diseases
Kidney and genitourinary stones 
and disease
Pregnancy
High blood pressure
Heart failure
Liver disease
Other cardiovascular disease
Autoimmune disease
Chronic obstructive pulmonary 
disease, emphysema, respiratory 
insufficiency
Diffuse diseases of connective 
tissue
Rheumatoid arthritis
Osteoarthrosis
Polymyalgia rheumatica
Urinary infections (chronic or 
recurring)
Crohn’s disease
Ulcerative colitis
Pancreatitis
Immunosuppressive diseases such 
as HIV/AIDS
Peptic ulcer disease
Dementia
Asthma
Chronic disease score 1
Renal insufficiency or diabetic 
nephropathy, peripheral
Retinopathy
Neuropathy
Peripheral vascular disease
Coronary heart disease
Cerebrovascular disease
Amputations
Time since first diagnosis of type 2
diabetes mellitus, (CPRD only) 
HIV = human immunodeficiency virus.
1.
For example, scores like the ones developed by Elixhauser et al. (1998) [R13-3591] or Charlson/Deyo [R13-3589], to 
be specified in analysis plan.

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HOSPITALISATION OR ED VISIT FOR DIABETIC KETOACIDOSIS
Annex 5 Table 5
Diabetic ketoacidosis outcome: variables of interest to be 
collected for propensity score development
Demographic or lifestyle
Medications
Age
Sex
Calendar year of index date
Duration of lookback time
Body mass index > 30 or obesity surgery
Smoking history
History of alcohol abuse
Socioeconomic status: Index of multiple 
socioeconomic deprivation, quintiles—first 
least deprived to fifth most deprived
Cocaine
Clozapine or olanzapine
Lithium
Terbutaline
Corticosteroids
Thiazides
Pentamidine
Concomitant non-insulin antidiabetics (including 
specification of add-on or switch)
Insulin therapy, change in insulin dose
Medical comorbidities
Indicators of diabetes severity 
Prior history of DKA
Acute illness: infections (such as UTI, 
gastroenteritis, urosepsis, influenza), recent 
surgery, or trauma
Thyroid problems (e.g., thyroid storm and 
thyrotoxicosis)
Myocardial ischaemia/infarction
Pancreatitis
Psychological stress
Reduced caloric or fluid intake
Hypovolemia
Alcohol intake
Hypoxemia
Acute renal failure
Heart Failure
Cerebrovascular accident
Chronic disease score 1
Renal insufficiency or diabetic nephropathy, 
peripheral
Retinopathy
Neuropathy
Peripheral vascular disease
Coronary heart disease
Cerebrovascular disease
Amputations
Time since first diagnosis of type 2 diabetes 
mellitus
UTI = urinary tract infection.
1.
For example, scores like the ones developed by Elixhauser et al. (1998) [R13-3591] or Charlson/Deyo [R13-3589], to 
be specified in the analysis plan.

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ANNEX 6. OVERVIEW OF CHARACTERISTICS OF THE DATA 
SOURCES
Annex 6 Table 1
Characteristics of the data sources
Database feature
CPRD
Danish Population 
Registries
HIRD
Population of 
country 1
United Kingdom: 
62,435,709
Denmark: 5,748,800
US: 323.1 million
Database population
5,79 million
Whole country
40 million
Database type
Electronic medical records
Population-based 
registries and databases;
link between all databases 
through Civil Personal 
Registration Number
Insurance claims records 
for health care services
Primary care data 
available
Yes
No on diagnoses, Yes on 
dispensings
Yes
Specialist outpatient 
visits available 
Only if the GP decided to 
include these in the 
medical record
Only hospital clinic visits
Yes
Hospital discharge 
data available
Partial linkage to HES 
(~54%) in CPRD GOLD, 
~93% in CPRD Aurum
Yes
Yes
Data on medications 
and type of 
prescriptions
GP prescriptions issued
Reimbursed-pharmacy-
filled prescriptions
Reimbursed pharmacy-
filled prescriptions
Drug dictionary 
codes/therapeutic 
classification 2
Multilex/British National 
Formulary in CPRD 
GOLD, the Dictionary of 
Medicines and Devices 
(DM+D) in CPRD Aurum
ATC
National Drug Codes, 
which can be mapped to 
other coding systems
Disease and 
procedure coding 
system(s)
Read codes in CPRD 
GOLD, Read codes, 
SNOMED codes, and 
EMIS local codes in 
CPRD Aurum
ICD-10
Surgical procedures: 
NOMESCO
ICD-9, ICD-10, CPT, 
HCPCS
Laboratory 
(requests, results)
Outpatient laboratory 
results available 
electronically for 100% of 
the population. Inpatients 
laboratory results may be 
available in the hospital 
discharge letters and 
obtained through GP 
questionnaires 
Results from hospital 
laboratories available 
electronically for 25% of 
the population; otherwise, 
via abstraction of medical 
records
Outpatient laboratory 
results available 
electronically for 30% of 
the population; otherwise, 
via abstraction of medical 
records

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Database feature
CPRD
Danish Population 
Registries
HIRD
Data availability
Since 1987
Patient register, since 
1977; prescription 
registries, since 1995 (all); 
since 2004 (reimbursed); 
laboratory data since ca. 
1996
Since January 2006
Approximate time 
lag (updates per 
year) 
1 month (monthly)
Varies by data source: 
from 3 to 12 months (1 per 
year)
3 months (monthly 
updates for the pharmacy 
data)
Access to source 
records for 
validation (requires 
special approval)
GPs can be sent 
questionnaires via the 
CPRD for validation
Yes, with an approval 
from the Patient Safety 
Board
Yes, for about 60% of the 
subset of around 50% of 
the patients for whom 
 has 
permission to access their 
protected health 
information
ATC = Anatomical Therapeutic Chemical (classification system); CPRD = Clinical Practice Research Datalink; 
GP = general practitioner or general practice; CPT, Current Procedural Terminology; HCPCS, Healthcare Common 
Procedural Coding System; HES = Hospital Episode Statistics; HIRD =
 Integrated Research Database℠; 
ICD-9 = International Classification of Diseases, 9th Revision; ICD-9-CM = International Classification of Diseases, 
9th Revision, Clinical Modification; ICD-10 = International Statistical Classification of Diseases and Related Health 
Problems, 10th Revision; ICD-10-CM = International Statistical Classification of Diseases and Related Health 
Problems, 10th Revision, Clinical Modification; ICD-9-CM = International Classification of Diseases, 9th Revision, 
Clinical Modification;. NOMESCO = Nordic Medico-Statistical Committee.
1
Eurostat population at 01 January 2017 [R18-0353].
2
Duration derived from prescription/dispensing data (i.e., formulation strength, quantity prescribed/dispensed) and 
defined daily dose.

 
 
 
 
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c03270726
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Post-authorisation safety study in patients with type 2 diabetes mellitus to assess the
risk of acute liver injury, acute kidney injury and chronic kidney disease, severe
complications of urinary tract infection, genital infections, and diabetic ketoacidosis
among patients treated with empagliflozin compared to patients treated with DPP-4
inhibitors
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