Clinical trial NCT03594110
Conditions: Chronic Kidney Disease
Sponsor: Boehringer Ingelheim
Start date: 2019-01-31; Completion date: 2024-07-02
Enrollment: 6609 participants; Allocation: RANDOMIZED; Intervention model: PARALLEL

Brief summary:
The primary aim of the study is to investigate the effect of empagliflozin on kidney disease progression or cardiovascular death versus placebo on top of standard of care in patients with pre-existing chronic kidney disease. After completion of the interventional part of the study (primary study completion) a subset of participants will be followed up in a post-trial observational (non-interventional) manner for cardio-renal outcomes (estimated study completion date).

Detailed description:

Arms: arm 1: Patients with evidence of chronic kidney disease (CKD) at risk of kidney disease progression, with or without diagnosed diabetes mellitus administered orally once daily 10 milligram (mg) film-coated tablets of empagliflozin. arm 2: Patients with evidence of chronic kidney disease (CKD) at risk of kidney disease progression, with or without diagnosed diabetes mellitus administered orally once daily film-coated tablets of placebo to match empagliflozin.
Interventions: intervention 1: Empagliflozin intervention 2: Matching placebo
Intervention descriptions: intervention 1: Taken daily with or without food intervention 2: Taken daily with or without food

Protocol documents:
SAP_008.pdf: 
           
 
                        
Page 1   
MRI substudy Data Analysis Plan (EDMS 7662) 
 
 
 
EMPA-KIDNEY Magnetic Resonance Imaging Substudy 
Data Analysis Plan (EDMS #7662) 
 
Version History 
 
Version Description 
Authors 
1.0 
First released version 
Created by Parminder K Judge, Rebecca Sardell, Natalie Staplin, William G. 
Herrington & Richard Haynes (04/2022) 
Reviewed by Kaitlin Mayne, Will Stevens, Karl Wallendszus, Jonathan 
Emberson, Sue Francis, Maarten Taal, Nick Selby, Jennifer Rayner, Christoph 
Wanner, Martin Landray & Colin Baigent (05/2022) 
Review by Steering Committee (18-MAY-2022) 
Released for use by Parminder Judge (20JUN2022) 
 
This is a controlled document. Distribution and approval is to be managed using the Electronic 
Document Management System.  
 
 


           
 
                        
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MRI substudy Data Analysis Plan (EDMS 7662) 
TABLE OF CONTENTS 
 
Contents 
1 
RELEVANT PROCEDURAL DOCUMENTS ................................................................... 3 
2 
ABBREVIATIONS .......................................................................................................... 3 
3 
INTRODUCTION ........................................................................................................... 3 
4 
BACKGROUND ............................................................................................................. 4 
5 
BASELINE CHARACTERISTICS ................................................................................... 4 
6 
DEFINITIONS OF KEY RANDOMIZED ASSESSMENTS .............................................. 4 
6.1 
Hypotheses ............................................................................................................. 5 
6.2 
Primary randomized assessment ............................................................................ 5 
6.3 
Secondary randomized assessments ...................................................................... 5 
6.4 
Tertiary randomized assessments including subgroup analyses ............................. 6 
7 
STATISTICAL METHODOLOGY ................................................................................... 6 
7.1 
Handling of missing MRI data ................................................................................. 6 
7.2 
Methods of analysis ................................................................................................ 6 
7.3.1 
Subgroup analyses 
7 
7.3.2 
Sensitivity analyses 
7 
8  
REFERENCES .............................................................................................................. 7 
 
 
 


           
 
                        
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MRI substudy Data Analysis Plan (EDMS 7662) 
1 
RELEVANT PROCEDURAL DOCUMENTS 
 
Document title 
EDMS# 
EMPA-KIDNEY Protocol 
5434 
EMPA-KIDNEY MRI Substudy Protocol Supplement 
7083 
EMPA-KIDNEY Data Analysis Plan (SOP11) 
6290 
 
 
2 
ABBREVIATIONS 
 
Abbreviation 
Definition 
ADC 
Apparent diffusion coefficient 
ASL 
Arterial spin labelling 
BOLD 
Blood oxygen level dependency 
CKD 
Chronic kidney disease 
EDMS 
Electronic document management system 
eGFR 
Estimated glomerular filtration rate 
MRI 
Magnetic resonance imaging 
MOLLI 
Modified Look–Locker inversion recovery 
SOP 
Standard operating procedure 
TKV 
Total kidney volume 
uACR 
Urine albumin-to-creatinine ratio 
 
 
3 
INTRODUCTION 
This document provides a Data Analysis Plan for the EMPA-KIDNEY magnetic resonance 
imaging (MRI) substudy, which has performed renal and cardiac MRI imaging in a subset of 
approximately 170 EMPA-KIDNEY participants recruited from the UK and Germany. An 
outline MRI data analysis plan was provided in the MRI substudy’s Protocol Supplement. The 
purpose of this MRI Data Analysis Plan is to define, before unblinding of the treatment 
allocation, detail of pre-specified randomized analyses to be presented in initial publication(s) 
of the substudy. The nature of all analyses (randomized or observational) including those 
related to subsequent publications and exploratory analyses cannot be specified in detail but, 
where appropriate, a general analytical approach is set out. Approaches, wherever possible, 


           
 
                        
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MRI substudy Data Analysis Plan (EDMS 7662) 
will follow those set out in EMPA-KIDNEY’s main data analysis plan (to which this document 
should be considered supplementary) so are not repeated here. 
 
 
4 
BACKGROUND  
The aim of this substudy is to evaluate the effect of empagliflozin 10mg versus matching 
placebo on markers of inflammation, fibrosis and perfusion of the kidney at around 18 months 
after randomization. Examples of MRI methods and what they assess are shown in Table 1. 
 
MRI method 
Target measure 
Volumetry 
  
Kidney size 
T1 mapping (using Modified Look-Locker 
inversion recovery [MOLLI]) 
Fibrosis (scarring) and inflammation of 
kidney 
Blood oxygen level dependent (BOLD) T2* Kidney oxygenation 
Phase contrast MRI 
Renal flow and global perfusion 
Diffusion-weighted imaging (DWI)  
Fibrosis of kidney 
Modified Dixon (mDIXON) 
Fat content 
Table 1: MRI methods and what they assess 
 
Note: this pre-specified Data Analysis Plan re-orders the priority of some of the assessments 
set out in the MRI substudy Protocol Supplement. This follows a more detailed review of data 
whilst compiling this plan. This pre-specified Data Analysis Plan therefore supersedes the 
proposed assessments set out in the Protocol Supplement and prevails in the event of any 
discrepancies between the two documents.  
 
 
5 
BASELINE CHARACTERISTICS 
In order to assess balance of baseline characteristics between randomized arms of the MRI 
substudy, the variables recorded at baseline listed in the main trial Data Analysis Plan will be 
presented for each of the empagliflozin and placebo groups.  
 
6 
DEFINITIONS OF KEY RANDOMIZED ASSESSMENTS 
At participating centres (Oxford, Derby, Nottingham, Edinburgh, Würzburg), all randomized 
participants without an obvious contraindication for an MRI scan were invited during the course 


           
 
                        
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MRI substudy Data Analysis Plan (EDMS 7662) 
of trial follow-up to have an MRI scan performed. Only those individuals that were able to have 
an MRI scan will be included in analyses (i.e. consented participants that were not scanned 
due to claustrophobia, or other contraindications will not be included). Therefore, unless 
otherwise specified, all analyses will involve an intention-to-treat comparison among all 
randomized participants with a valid MRI scan to assess the effects of allocation to 
empagliflozin versus placebo on MRI measurements obtained at about 18 months after 
randomization (i.e. all participants will be included irrespective of whether they take none, 
some or all of their allocated treatment).1,2 Handling of missing individual MRI measurements 
is described in section 7.2. 
 
6.1 
Hypotheses 
For all statistical tests (other than tests for heterogeneity or trend), the null hypothesis will be 
that the effect of allocation to empagliflozin on a given MRI measurement in the target 
population is the same as the effect of allocation to placebo (and hence the alternative 
hypothesis will be that the effect of allocation to empagliflozin is not the same as the effect of 
allocation to placebo). 
 
6.2 
Primary randomized assessment 
The primary assessment will be the effect of allocation to empagliflozin versus placebo on 
kidney cortical T1 mapping as measured by MOLLI at about 18 months after randomization 
measured using MRI. The details of all analysis methods are described in section 7.2 Methods 
of analysis. 
 
6.3 
Secondary randomized assessments 
The secondary assessments, at about 18 months after randomization, are:  
 
Kidney measures: 
• 
Kidney size (measured by total kidney volume [TKV])  
• 
Kidney arterial flow (measured using mean of left and right renal arterial flow) 
• 
Kidney global perfusion (measured by phase contrast MRI correct for TKV) 
• 
Kidney diffusion (measured by apparent diffusion coefficient [ADC])   
• 
Kidney oxygenation (measured by BOLD T2*) 
• 
Kidney fat content mapping (measured by mDIXON)  
Cardiac measures: 
• 
Left ventricular mass index (i.e., normalised to body surface area),  
• 
Left ventricular ejection fraction 


           
 
                        
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MRI substudy Data Analysis Plan (EDMS 7662) 
• 
Cardiac fibrosis measured by T1 MOLLI (mean of measurements at apex, wall and 
base of left ventricle) 
• 
Diastolic dysfunction (measured by left ventricular strain, left ventricular global 
longitudinal strain, left ventricular diastolic strain rate, and left ventricular volume) 
 
6.4 
Tertiary randomized assessments including subgroup analyses 
Tertiary assessments include: 
i. 
Subgroup analyses of effects of empagliflozin 10mg versus matching placebo on 
T1 mapping by baseline feature (age, sex, diabetes status, eGFR and uACR).  
ii. 
Amongst the proportion of participants with a baseline MRI scan, assessments of 
the effects of empagliflozin 10mg versus matching placebo on follow-up MRI 
measurements adjusted for baseline. 
 
7 
STATISTICAL METHODOLOGY 
7.1 
Handling of missing MRI data  
Participants included in the MRI substudy with a particular missing MRI measurement, will still 
be included in analyses and these values will be imputed using multiple imputation, using 20 
imputed data sets, with results across imputations being combined using the methods of 
Rubin.3 The imputation procedure will take into consideration each participant’s key baseline 
characteristics, treatment allocation and other available MRI measurement parameters. 
Results from the imputed analyses will be compared with those from equivalent “complete-
case” analyses, but primary emphasis will be placed on the results after multiple imputation. 
All multiple imputation analyses will be implemented using the multiple imputation procedure 
in SAS version 9.4 (SAS Institute, Cary NC), using the expectation-maximization algorithm 
(which assumes a multivariate normal distribution) to impute values. In sensitivity analyses 
conducted in participants with baseline scans, missing baseline MRI measurement 
parameters will be imputed with the median observed value (in both treatment groups 
combined). For participants with missing baseline characteristics required for analyses of 
outcomes (e.g. for subgroup analyses), the median value will be imputed. 
  
7.2 
Methods of analysis 
All MRI measurements will be analysed as a continuous variable. Differences in MRI 
measurements between treatment groups will be assessed using a linear regression approach 
adjusted for the elements included in the minimization algorithm which determined treatment 
allocation (age, sex, prior diabetes, eGFR, and uACR [but not region as the MRI substudy was 


           
 
                        
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MRI substudy Data Analysis Plan (EDMS 7662) 
only conducted in Europe]). If outcomes are not normally distributed then appropriate 
transformations (e.g. log transformation) will be made. 
 
7.3.1 Subgroup analyses 
Subgroup analyses will be conducted by fitting relevant interaction terms for subgroups in 
linear regression models with the aim of assessing whether the effects in specific subgroups 
are statistically different from the overall effect.  
 
7.3.2 Sensitivity analyses 
Among those with both a baseline and follow-up MRI scan, sensitivity analyses will additionally 
be adjusted for the baseline MRI estimates by fitting a linear regression model. 
 
8  
REFERENCES 
1. 
Peto R, Pike MC, Armitage P, et al. Design and analysis of randomized clinical trials requiring 
prolonged observation of each patient. I. Introduction and design. British journal of cancer 1976; 
34(6): 585-612. 
2. 
Peto R, Pike MC, Armitage P, et al. Design and analysis of randomized clinical trials requiring 
prolonged observation of each patient. II. analysis and examples. British journal of cancer 1977; 
35(1): 1-39. 
3. 
Rubin D. Multiple imputation for non-response in surveys.: New York: John Wiley; 1987. 
 
 
 

Prot_005.pdf: 
                                                                                      
 
 
EMPA-KIDNEY MRI substudy justification and design (protocol supplement) 
V2.0 – 25-FEB-2021   
Page  1 of 5      EDMS #7083 
 
 
EMPA-KIDNEY Magnetic Resonance Imaging Substudy Protocol Supplement 
 
Study Title: 
A multicentre international randomized parallel group double-blind placebo-
controlled clinical trial of EMPAgliflozin once daily to assess cardio-renal 
outcomes in patients with chronic KIDNEY disease  
Sponsor protocol number: 1245-0137 
Protocol identifier: 
 
CTSUEMPA-KIDNEY1.4 2018-04-25 
EudraCT number:     
2017-002971-24 
 
Summary 
This document is a substudy protocol supplement which provides the rationale, design and key 
operation details of an EMPA-KIDNEY substudy to image a subset of participants‘ hearts and kidneys 
using multi-parametric magnetic resonance imaging. This protocol substudy document is only relevant 
to sites participating in the substudy and does not alter the main protocol in any respect. The 
procedures in the main protocol should be followed irrepsective of whether a participant joins this 
substudy or not. 
 
Background 
The EMPA-KIDNEY study is investigating whether empagliflozin 10 mg daily reduces the risk of a 
cardiorenal composite outcome among patients with established chronic kidney disease. Trials in 
other populations indicate that sodium-glucose co-transporter-2 inhibitors (SGLT-2i, like 
empagliflozin) do reduce the risk of progression of kidney disease and heart failure (including 
cardiovascular death) among people with diabetes, diabetic kidney disease and – more recently – 
heart failure with reduced ejection fraction (including patients with and without diabetes). However, 
substantial uncertainty remains for many types of patients with chronic kidney disease (CKD) and 
diabetes excluded from these trials and for patients with CKD but without diabetes. 
 
EMPA-KIDNEY and the other SGLT-2i trials will provide clear evidence of the clinical safety and 
efficacy of SGLT-2i, but the mechanisms by which these effects occur remain uncertain. Many 
different mechanisms have been proposed to explain the observed benefits to date, but much of this 
work relies on animal models and whether these mechanisms operate in humans has not been 
confirmed. Magnetic resonance imaging (MRI) offers an opportunity to assess the effects on structure 
and function of the heart and kidneys in patients with CKD. 
 


                                                                                      
 
 
EMPA-KIDNEY MRI substudy justification and design (protocol supplement) 
V2.0 – 25-FEB-2021   
Page  2 of 5      EDMS #7083 
 
MRI allows detailed imaging of organs without ionizing radiation. Cardiac MRI is well-established both 
in research and clinical care and provides accurate assessment of cardiac structure and function. It 
has frequently been used to assess the effects of treatments on cardiac structure (e.g. left ventricular 
mass) and function (e.g. cardiac output) for patients with cardiac disease. Patients with CKD develop 
abnormal cardiac structure and function early in their disease and it is likely that such abnormalities 
underlie some of the large excess risk of cardiovascular morbidity and mortality observed in this 
population. However, few studies to date have tested the effect of treatment in a randomized 
comparison on cardiac MRI among patients with CKD. 
 
MRI of the kidney is a newer discipline and is currently a research tool only. There are many different 
MRI methods that can visualize different aspects of kidney structure and function and their 
combination is called “multiparametric” MRI. Examples of methods and what they assess are shown 
in Table 1. 
MRI method 
Target measure 
Volumetry 
Kidney size, cortical thickness 
T1 mapping 
Fibrosis (scarring) and inflammation of kidney 
Blood oxygen level dependent (BOLD) 
Kidney oxygenation 
Arterial spin labelling (ASL) 
Kidney perfusion 
Diffusion-weighted imaging (DWI) 
Fibrosis of kidney 
Modified Dixon (mDIXON) 
Fat content 
Table 1: Examples of MRI methods and what they assess 
 
Small studies have demonstrated that kidneys in healthy volunteers have different measurements to 
kidneys in patients with CKD. For example, one study found that the mean T1 time among healthy 
volunteers was 1432 (SD 87) ms, whereas among patients with CKD it was 1574 (SD 74) (p<0.001).1 
Cortical perfusion (measured by arterial spin labelling) was lower among patients with CKD (71 [SD 
49] mL/100g/min) than healthy volunteers (200 [SD 56] mL/100g/min) (p<0.001). It is therefore 
plausible that treatments that retard the progression of kidney disease may also delay changes in MRI 
parameters. Furthermore, such MRI parameters could be used to either stratify risk or provide 
additional early data on new drugs during their development. MRI is safe and none of the planned 
measurements require injection of any contrast or other agents. 
 
UK capability 
The UK has a Renal Imaging Network (RIN; https://kidneyresearchuk.org/research/research-
networks/uk-renal-imaging-network/) which is funded by the UK Medical Research Council and is 
undertaking a project to standardize approaches to renal MRI. This collaboration of centres (most of 


                                                                                      
 
 
EMPA-KIDNEY MRI substudy justification and design (protocol supplement) 
V2.0 – 25-FEB-2021   
Page  3 of 5      EDMS #7083 
 
whom are collaborating in the EMPA-KIDNEY trial) mean the UK is ideally placed to host this research. 
This proposal has been written by a collaboration of EMPA-KIDNEY investigators and members of 
the UK RIN. In addition, it may be possible to involve some other international centres although this 
has not been discussed yet. 
 
Aims 
The primary aim of this substudy is to use multiparametric MRI to assess, in a subset of EMPA-
KIDNEY participants, the effect of empagliflozin 10mg versus matching placebo on kidney cortical T1 
at 18 months after randomization. 
 
Secondary aims are to use multiparametric MRI to assess: 
1. The effects of empagliflozin 10mg versus matching placebo at 18 months on: 
o Kidney size and cortical thickness 
o Kidney perfusion (measured by arterial spin labelling) 
o Kidney oxygenation (measured by BOLD) 
o Kidney fat content (measured by mDIXON) 
o Cardiac structure (left ventricular mass, standard volumes) 
o Cardiac function (left ventricular ejection fraction, cardiac output) 
o Cardiac fibrosis (measured by T1) 
2. Whether any effects of empagliflozin 10mg versus matching placebo on kidney fibrosis are 
modified by baseline factors, in particular by level of kidney function, glycosylated haemoglobin, 
body mass index, age, sex and RAS inhibitor use 
 
Exploratory aims are to assess the effects of empagliflozin 10mg versus matching placebo at 18 
months on less well-established MRI measurements (for example diffusion tensor imaging) which 
may only be measured in a subset of participants. 
 
Sample size estimates 
The original plan was to perform two scans in each participant: one at baseline and one at about 18 
months after Randomization. Because of the COVID-19 pandemic it was not possible to perform 
baseline scans and recruitment to the main trial is now very nearly complete. However, it is still 
feasible to make the planned comparisons using a single scan during Follow-up (at least 18 months  
after Randomization). Instead of using the planned ANCOVA analysis (where the 18 month 
measurements are adjusted for baseline), we will use unadjusted measurements. This reduces the 
precision somewhat so a larger sample size is required.  


                                                                                      
 
 
EMPA-KIDNEY MRI substudy justification and design (protocol supplement) 
V2.0 – 25-FEB-2021   
Page  4 of 5      EDMS #7083 
 
It was estimated that at least 64 (of the 6000) EMPA-KIDNEY participants with baseline and 18 
months follow-up MRI data will provide ample power (>90%, 2p=0.05) to detect at least a 50 ms 
difference in T1 (assumed reference range in healthy adults is  1500 ms with a standard deviation of 
100 ms and intra-individual correlation of 0.8) based on analysis of covariance (ANCOVA). By 
changing the design to a single scan, approximately 172 participants are required for equivalent 
statistical power. 
 
Data Analysis Plan  
The primary analysis will estimate the differences in cortical T1 between treatment groups at ~18 
months, regardless of whether a participant received all, some or none of their allocated treatment 
(i.e. intention-to-treat analyses). Secondary outcomes include kidney volumes, perfusion and 
oxygenation and cardiac structure and function. Differences in cortical T1 and the secondary 
outcomes between treatment groups will be adjusted (or stratified) for the elements included in the 
main trial’s minimization algorithm. Missing measurements will be imputed. Results from the imputed 
analyses will be compared with those from equivalent “complete-case” analyses, but primary 
emphasis will be placed on the results after multiple imputation. More complete details of statistical 
methods, including definitions of subgroups, methods of any imputation, approaches to adjustments 
and weighting of averages will be set out in a separate full Data Analysis Plan which will be consistent 
with the main study Data Analysis Plan.  
 
Flowchart of Substudy Activities 
 
INVITATION 
 Invite potential participants after Screening visit complete and participant has entered pre-
randomization Run-in phase; OR 
 Invite potential participants around time of 18 or 24 month Follow-up visit (when a baseline scan 
was not possible) 
INFORMED CONSENT AND BASELINE SCAN 
 Written informed consent is sought from willing individuals when they attend for first MRI scan  
18 MONTHS OF FOLLOW-UP 
 Second MRI scan performed around time of 18-24 month follow-up visit 
 
Design 


                                                                                      
 
 
EMPA-KIDNEY MRI substudy justification and design (protocol supplement) 
V2.0 – 25-FEB-2021   
Page  5 of 5      EDMS #7083 
 
Eligibility: In selected regions, EMPA-KIDNEY Local Clinical Centres (LCCs) with access to an 
appropriate MRI scanner will be invited to join this optional substudy. The only exclusion criteria are 
those for a standard MRI scan: 
 
Cardiac pacemaker 
 
Any unfixed metallic implant or metallic fragments 
 
Excessive tattoos 
 
Fear of closed spaces or claustrophobia 
 
Absence of one kidney 
 
Invitation: Potential participants will be invited to join this substudy before the time of their 
Randomization Visit. If baseline scans were not possible (eg, due to COVID-19), participants will be 
invited around the time of their 18 or 24 month Follow-up visit for a single scan. If participants are 
interested the Research Coordinator will explain the substudy to potential participants using the 
Participant Information Leaflet and Consent Form. Consenting participants will then have an 
appointment made to attend for their MRI scan. 
 
Methods: The MRI scanning staff will double-check the suitability of the patient for an MRI scan and 
explain what it will involve. The participant will need to hold their breath at certain points during the 
process. The planned MRI scans take about 1 hour to complete. 
 
Analysis: The MRI data from all sites will be uploaded to an online secure platform (as used by other 
NHS services such as the Dementias Platform UK) and analysed by a standard pipeline. No 
participant data are required to be transferred with the scan (except for their de-identified unique study 
ID). The results will then be provided to the study statisticians at the University of Oxford for analysis. 
Patients from Oxford may have some of their MRI data also transferred to Perspectum Diagnostics 
who will process the data and provide results to University of Oxford staff. Basic demographic, medical 
history and laboratory details will be provided to staff at the University of Oxford and Perspectum 
Diagnostics to facilitate analysis of the exploratory aims. The primary analyses will not be conducted 
until the end of the main trial because only at this time will the unblinded treatment allocation become 
available. 
 
References 
1. 
Buchanan CE, Mahmoud H, Cox EF et al. Nephrol Dial Transplant 2019; doi 
10.1093/ndt/gfz219 

SAP_003.pdf: 
Page 1 of 7 
EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
EMPA-KIDNEY Post-Trial Follow-Up 
Data Analysis Plan (EDMS 7987)
Version History 
Version
Description
Authors
1.0 
First released version 
Created by: William G. Herrington, Natalie Staplin, Jonathan Emberson, David 
Preiss, Colin Baigent and Richard Haynes (DEC2022-MAR2023) 
Review by Steering Committee (07MAR2023) and sponsor biostatistics and 
data science team (MAR-APR2023) 
Released for use by William G. Herrington (02MAY2023) 
This is a controlled document. Distribution and approval is to be managed using the Electronic 
Document Management System or iPassport 


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EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
TABLE OF CONTENTS
Contents 
1
RELEVANT PROCEDURAL DOCUMENTS ................................................................... 3
2
ABBREVIATIONS .......................................................................................................... 3
3
INTRODUCTION ........................................................................................................... 3
4
PARTICIPANT FLOW & BASELINE CHARACTERISTICS ............................................ 3
5
USE OF SGLT-2 INHIBITORS BY TIME ........................................................................ 4
6
RANDOMIZED ASSESSMENTS ................................................................................... 4
Hypotheses ............................................................................................................. 4
Primary randomized assessment ............................................................................ 4
Secondary randomized assessments...................................................................... 5
Tertiary randomized assessments .......................................................................... 5
6.4.1
Mortality-based outcomes ................................................................................ 5
6.4.2
Subgroup analyses of the primary PTFU assessment ...................................... 5
Exploratory eGFR-based analyses ......................................................................... 6
7
STATISTICAL METHODOLOGY ................................................................................... 6
7.1
Methods of analysis ................................................................................................ 6
Subgroup analyses and tests for heterogeneity ...................................................... 6
Handling of missing and incomplete data ................................................................ 7
7.3.1
Handling of missing central eGFR values ........................................................ 7
Censoring schema for time-to-event endpoints ....................................................... 7
7.4.1
Date of censoring for intention-to-treat analyses .............................................. 7
8
REFERENCES .............................................................................................................. 7


Page 3 of 7 
EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
1 
RELEVANT PROCEDURAL DOCUMENTS 
Document title 
EDMS# 
EMPA-KIDNEY Protocol 
5434 
EMPA-KIDNEY Post-Trial Follow-Up Protocol Supplement 
7279 
EMPA-KIDNEY Data Analysis Plan (SOP11) 
6290 
2 
ABBREVIATIONS 
Abbreviation 
Definition 
CKD 
Chronic kidney disease 
DAP 
Data analysis plan 
EDMS 
Electronic document management system 
eGFR 
Estimated glomerular filtration rate 
MMRM 
Mixed model repeated measures 
MRA 
Mineralocorticoid receptor antagonist 
PTFU 
Post-trial follow-up 
RAS 
Renin-angiotensin system 
SGLT-2 
Sodium glucose co-transporter-2 
3 
INTRODUCTION 
This document provides a Data Analysis Plan (DAP) for the EMPA-KIDNEY Post-Trial Follow-Up 
(PTFU) substudy. The substudy‘s aim is to continue follow-up of a subset of consenting and surviving 
EMPA-KIDNEY participants for at least 2 years after the end of the within-trial period in order to provide 
valuable information on the longer-term effects of empagliflozin 10 mg daily versus matching placebo 
on mortality and kidney disease progression. During this time, participants are not issued with any study 
treatment and no research samples for central analysis are collected: follow-up will be performed 
remotely for selected key pre-specified efficacy outcomes. However, participants may be prescribed a 
sodium glucose co-transporter 2 (SGLT-2) inhibitor by local clinicians. Wherever possible, participants 
and researchers remain blind to original study treatment allocation. 
This DAP sets out the main analyses for the key publications of the EMPA-KIDNEY PTFU substudy. 
The nature of all analyses using PTFU data (randomized or observational) cannot be specified in detail 
but, where appropriate, a general analytical approach is set out. Approaches, wherever possible, should 
follow those set out in EMPA-KIDNEY’s main DAP (SOP11; EDMS#6290). 
4 
PARTICIPANT FLOW & BASELINE CHARACTERISTICS  
A CONSORT diagram will show participant flow and will include both the within trial and PTFU periods. 
It will count (by arm) the numbers of participants who: 
 
Were randomized 


Page 4 of 7 
EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
 
Completed the within trial period of follow-up (with numbers who withdrew consent or 
were lost to follow-up)  
 
Were eligible for PTFU (i.e. survived and completed final follow-up) 
 
Entered PTFU (with reasons for exclusion [i.e. did not provide optional consent or the 
site was not included]) 
 
Were lost to follow-up or withdrew consent during PTFU 
 
Were analysed (Note: all analyses follow the principle of intention-to-treat and will 
therefore include all participants)   
Median follow-up among survivors will be calculated for the entire follow-up period, and separately for 
its two components (i.e. the within-trial and PTFU periods). Baseline characteristics of the participants 
who did not enter PTFU (e.g. due to non-provision of consent or exclusion of the site) will be provided 
alongside the baseline characteristics for the overall trial and those that did enter PTFU, using the 
categories set out in the main DAP. 
5 
USE OF SGLT-2 INHIBITORS BY TIME 
SGLT-2 inhibitor use will be estimated by year of follow-up, with SGLT-2 inhibitor use defined as a 
record of taking an open-label SGLT-2 inhibitor, or reporting taking at least 80% of study treatment 
(during the within trial period only). A separate estimate of “average” use over the within-trial and 
relevant PTFU periods of follow-up will be provided. Supplementary analyses using a similar approach 
will provide information on RAS inhibitor and MRA use over time. 
6 
RANDOMIZED ASSESSMENTS 
All primary, secondary and tertiary assessments will follow the principle of intention-to-treat and will 
consider the entire follow-up period (i.e. will combine the within trial and PTFU periods). 
 
Hypotheses 
For statistical tests (other than tests for heterogeneity or trend), the null hypothesis will be that the effect 
of allocation to empagliflozin on the parameter of interest in the target population is the same as the 
effect of allocation to placebo for the entire follow-up period which includes both within trial and PTFU 
periods combined (and hence the alternative hypothesis will be that the effect of allocation to 
empagliflozin is not the same as the effect of allocation to placebo for the entire follow-up period). 
 
Primary randomized assessment 
The primary assessment will be the effect of allocation to empagliflozin on the time to the first EMPA-
KIDNEY primary composite outcome event of kidney disease progression or cardiovascular death for the 
entire follow-up period. Whether the effect of allocation to empagliflozin versus placebo on the primary 
outcome differs by year since randomization will be explored enabling interpretation of PTFU results in 
the context of the changing use of SGLT-2 inhibitors with time. 


Page 5 of 7 
EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
The EMPA-KIDNEY main Protocol (EDM#5434) and main DAP (SOP11; EDMS#6290) provide full 
details of the definitions for the trial’s primary composite outcome and its components, which were 
based on central eGFR measurements wherever possible. As central samples are not being collected 
during PTFU, all eGFR-based assessments for the PTFU period will necessarily be relative to the local 
eGFR measurement at randomization (or the measurement shortly before, if unavailable at 
randomization).1 For the primary PTFU assessment, the main results of the trial’s primary outcome from 
the within trial period will be carried over,2 including the eGFR-based outcomes (i.e. any eGFR-based 
outcome recorded at the within trial period’s Final Follow-up Visit without a confirmatory result will still 
be accepted as “sustained” despite the availability of eGFR measurements in the PTFU period). A 
sensitivity analysis using only local eGFR measurements collected throughout the entire follow-up 
period will be conducted and this analysis will not differentiate the within versus PTFU periods (i.e. in 
this sensitivity analysis, a locally-measured eGFR recorded at the last PTFU will be designated as the 
“last scheduled visit” for the purposes of “sustained” definitions). 
 
Secondary randomized assessments
The key secondary assessments for the entire follow-up period (i.e. the within trial plus PTFU periods 
combined) are time to first occurrence of: 
a) 
Kidney disease progression; and 
b) 
Death from any cause or end-stage kidney disease (ESKD) 
The other secondary outcome for the entire follow-up period is time to first occurrence of ESKD (with 
detail of the other components of kidney disease progression presented for completeness).  
 
Tertiary randomized assessments 
6.4.1 
Mortality-based outcomes 
The tertiary outcomes for the entire follow-up period are time to death from any cause and, separately, 
death from cardiovascular and non-cardiovascular causes. 
6.4.2 
Subgroup analyses of the primary PTFU assessment
The primary assessment will be assessed among subgroups of participants based on data recorded at 
baseline. These will focus on four subgroups: the three key subgroups of interest by: (a) diabetes status, 
(b) baseline eGFR, and (c) baseline urinary albumin-to-creatinine ratio, plus (d) by primary kidney disease 
(using definitions specified in the main DAP). 
1 Local eGFR measurements are considered to be sufficiently reliable for PTFU assessments as sensitivity 
analyses for the within trial primary outcome analysis and eGFR slope analyses using these local records provided 
similar results to central sample based analyses. Results of EMPA-KIDNEY’s primary outcome and tertiary eGFR 
slope-based outcome re-analysed using only local (rather than central) eGFR results will be provided as 
supplementary materials for the main PTFU publication, if not already published in another peer reviewed 
manuscript.
2 Any data errors may be subject to data changes leading to minor differences between publications (which will be 
explained in footnotes, if necessary).


Page 6 of 7 
EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
 
Exploratory eGFR-based analyses 
The acute reversible dips in eGFR on commencing an SGLT-2 inhibitor make eGFR slope analyses 
more complex. The PTFU period will start with systematic discontinuation of study treatment (including 
“rebounds” of acute dips) among those allocated to the empagliflozin group followed by non-systematic 
initiation of SGLT-2 inhibitors in participants in both groups. In addition, there will be considerable 
between-person variation in the number of years from randomization to the end of the trial period (i.e. 
the ‘within-trial’ period will vary between participants) so the impact of these eGFR rebounds on mean 
eGFR in each group will average across a distribution of times since randomization. Consequently, 
eGFR slope analyses will be problematic to model and interpret. eGFR-based analyses by time will 
therefore all be exploratory with sensitivity analyses used to assess the robustness of findings. The key 
eGFR-based explorations will involve mixed model repeated measures (MMRM) approaches to 
estimate mean eGFR at each follow-up time point throughout the entire follow-up period and will 
emphasize results from local laboratory measurements. This will enable characterisation of the nature 
of any PTFU eGFR rebounds and dips that may occur, as well as the nature of the subsequent rates of 
change in eGFR. The MMRM model will be calculated overall and in the 4 subgroups described in 
section 6.4.2.  
7 
STATISTICAL METHODOLOGY 
7.1 
Methods of analysis 
Cox proportional hazards regression adjusted for the variables specified in the protocol for the 
minimization algorithm (age, sex, prior diabetes, eGFR, urinary albumin-to-creatinine ratio, and region) 
will be used to estimate the hazard ratio associated with allocation to empagliflozin versus placebo (with 
the Wald chi-square statistic used to both test significance and generate an asymptotic 95% confidence 
interval).(1) Any ties will be handled using Breslow’s method. If any regression models fail to converge, 
the approaches set out in the main DAP will be followed.  
Kaplan-Meier estimates for the time to each of the primary and secondary assessments will also be 
calculated. Plots will include indicators of median within-trial and entire follow-up durations. To explore 
whether the effect of allocation to empagliflozin versus placebo on the primary outcome differs over 
time, follow-up time will be split into categories by year since randomization and the significance of the 
time x treatment allocation interaction will be assessed. 
In addition to the pre-specified comparisons, other post-hoc analyses may be performed with due 
allowance for their exploratory and, perhaps, data-dependent nature. For example, how well estimates 
from eGFR-slope analyses using the methods specified in the DAP visually fit with MMRM estimates of 
eGFR by time will be possible. 
 
Subgroup analyses and tests for heterogeneity 
Tests for heterogeneity of effects observed in subgroups will follow the methods set out in the main 
DAP. Interpretation of results will take into account the number of statistical tests performed. 


Page 7 of 7 
EMPA-KIDNEY PTFU Data Analysis Plan (EDMS 7987) 
 
Handling of missing and incomplete data 
Missing eGFR values will be handled as detailed below. Participants with missing values relevant to 
subgroup analyses will be included in the subgroup containing the median value. 
7.3.1 
Handling of missing central eGFR values 
Methods will follow the approaches from the main DAP, with the exception of when local eGFR 
measurements are used in preference to central samples in the relevant analyses (e.g. section 6.2 and 
6.5). eGFR will be estimated using the same CKD-EPI formula as the main DAP analyses,(2) and will 
use the DAP defined follow-up windows and the principles of the algorithm to define sustained. If 
multiple local eGFR measurements are available in any one follow-up window, then the eGFR closest 
to the ideal follow-up day will be used to define the eGFR for that particularly window. If there are two 
eGFRs recorded at the last follow-up, the last of these eGFRs will be included in analyses, and will be 
included irrespective of whether or not it is the eGFR closest to the ideal follow-up day. This may result 
in two eGFRs in the last follow-up window.  
 
Censoring schema for time-to-event endpoints 
7.4.1 
Date of censoring for intention-to-treat analyses 
It is the aim at each follow-up to ascertain all components of the primary outcome. Censoring dates for 
those who withdraw consent or who are lost to follow-up will be derived from information collected at 
their most recent follow-up before consent withdrawal or loss to follow-up. For those that did not consent 
to PTFU, the censoring will be the same as their within trial date. Otherwise, the censoring date will be 
the date of death or the date of the last follow-up (using the date of last known to be alive). Note that all 
participants will contribute to the primary outcome irrespective of whether post-trial eGFRs were 
available, with participants censored for the eGFR-based components of outcomes at the point local 
eGFR measurements are unavailable (e.g. participants remain at risk of the ESKD and cardiovascular 
death components of the primary composite outcome even in the absence of post-trial eGFR 
measurements). 
8 
REFERENCES 
1. 
Cox DR. Regression Models and Life-Tables. J R Stat Soc B. 1972;34(2):187-+. 
2. 
Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, 3rd, Feldman HI, et al. A new 
equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-12. 

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SAP_007.pdf: 
           
 
                        
Page 1   
BCM substudy Data Analysis Plan (EDMS 7635) 
 
 
 
EMPA-KIDNEY Body Composition Monitor Substudy 
Data Analysis Plan (EDMS 7635) 
 
Version History 
 
Version Description 
Authors 
1.0 
First released version 
Created by: Kaitlin J. Mayne, Natalie Staplin, Richard Haynes & William G. 
Herrington (JAN-MAR2022) 
Reviewed by Rebecca Sardell, Will Stevens, Karl Wallendszus, Jonathan 
Emberson, John Nolan, Dani Trinca, David Keane, Simon Davies, Rejive 
Dayanandan, Akiko Omata, Parminder Judge, Ryonfa Lee, Patrick Mark, 
Jennifer Lees, Vladimir Cejka, Christoph Wanner (MAR2022) & Colin Baigent 
(APR2022) 
Review by Steering Committee (18MAY2022) 
Released for use by William G. Herrington (08JUN2022) 
1.1 
Revision to Appendix 8.1: 
Definition of a valid BCM 
measurement 
Addition of Appendices 8.4 
and 8.5.  
Revised by: Kaitlin J. Mayne, David Keane, & William G, Herrington (18OCT-
16NOV2022) 
Released for use by William G. Herrington (17NOV2022) 
 
This is a controlled document. Distribution and approval is to be managed using the Electronic 
Document Management System.  
 
 


           
 
                        
Page 2   
BCM substudy Data Analysis Plan (EDMS 7635) 
TABLE OF CONTENTS 
 
Contents 
1 
RELEVANT PROCEDURAL DOCUMENTS ................................................................... 3 
2 
ABBREVIATIONS .......................................................................................................... 3 
3 
INTRODUCTION ........................................................................................................... 4 
4 
KEY FLUID OVERLOAD DEFINITIONS ........................................................................ 5 
5 
BASELINE CHARACTERISTICS ................................................................................... 6 
6 
DEFINITIONS OF KEY RANDOMIZED ASSESSMENTS .............................................. 8 
6.1 
Hypotheses ............................................................................................................. 8 
6.2 
Primary randomized assessment ............................................................................ 8 
6.3 
Key secondary randomized assessment ................................................................. 9 
6.4 
Other secondary randomized assessment .............................................................. 9 
6.5 
Tertiary randomized assessments including subgroup analyses ............................. 9 
6.6 
Additional exploratory analyses............................................................................. 10 
7 
STATISTICAL METHODOLOGY ................................................................................. 11 
7.1 
Handling of missing and extreme values ............................................................... 11 
7.2 
Methods of analysis .............................................................................................. 11 
7.2.1 
Primary randomized assessment ................................................................... 11 
7.2.2  
Assessment for key secondary randomized assessment ............................... 12 
7.2.3 
Other secondary randomized assessment ..................................................... 12 
7.2.4 
Tertiary randomized assessments including subgroup analyses .................... 12 
8 
APPENDIX: DEFINITION OF VALID BCM MEASUREMENTS AND DATA HANDLING 
CONSIDERATIONS ............................................................................................................ 13 
8.1 
Definition of a valid BCM measurement ................................................................ 13 
8.2 
Handling multiple BCM measurements ................................................................. 14 
8.2.1  
Multiple valid BCM measurements at the same visit ...................................... 14 
8.2.2 
Multiple valid BCM measurements within a Follow-up window ....................... 14 
8.2.3 
Multiple measurements at different visits on a single BCM card ..................... 14 
8.3 
Data processing: BCM variables ........................................................................... 15 
8.4 
Criteria for rejecting BCM measurements by Cole-Cole plot visual inspection ....... 16 
8.5 
Sensitivity analyses ............................................................................................... 17 
REFERENCES ................................................................................................................... 18 
 
 
 


           
 
                        
Page 3   
BCM substudy Data Analysis Plan (EDMS 7635) 
1 
RELEVANT PROCEDURAL DOCUMENTS 
 
Document title 
EDMS# 
EMPA-KIDNEY Protocol 
5434 
EMPA-KIDNEY BCM Substudy Protocol Supplement 
6251 
EMPA-KIDNEY Data Analysis Plan (SOP11) 
6290 
EMPA-KIDNEY BCM datacard download IOP 
6433 
EMPA-KIDNEY Leeds BCM Card Data Transfer for Outcome 
Derivation 
7248 
EMPA-KIDNEY BCM kit leaflet 
6240 
2 
ABBREVIATIONS 
 
Abbreviation 
Definition 
ACR 
Albumin-to-creatinine ratio 
ATM 
Adipose tissue mass 
BCM 
Body composition monitor 
BMI 
Body mass index 
CKD-EPI 
Chronic Kidney Disease Epidemiology Collaboration 
DPP-4 
Dipeptidyl peptidase-4 
ECW 
Extracellular water 
EDMS 
Electronic document management system 
eGFR 
Estimated glomerular filtration rate 
FTI 
Fat tissue index 
GLP-1  
Glucagon-like peptide-1 
HbA1c 
Glycosylated haemoglobin 
ICW 
Intracellular water 
LTI 
Lean tissue index 
LTM 
Lean tissue mass 
MMRM 
Mixed model repeated measures 
NT-proBNP 
N-terminus prohormone of brain natriuretic peptide 
RAS 
Renin-angiotensin system 
SOP 
Standard operating procedure 
TBW 
Total body water 
 
 


           
 
                        
Page 4   
BCM substudy Data Analysis Plan (EDMS 7635) 
3 
INTRODUCTION 
This document provides a Data Analysis Plan for the EMPA-KIDNEY substudy, which has 
measured body composition of a subset of approximately 650 EMPA-KIDNEY participants 
recruited from the UK and Germany using bioimpedenace spectroscopy on a body 
composition monitor (BCM). An outline BCM data analysis plan was provided in the BCM 
substudy’s Protocol Supplement (EDMS#6251). The purpose of this BCM Data Analysis Plan 
is to define, before unblinding of the treatment allocation, detail of pre-specified randomized 
analyses to be presented in initial publication(s) of the substudy. The nature of all analyses 
(randomized or observational) including those related to subsequent publications and 
exploratory analyses cannot be specified in detail but, where appropriate, a general analytical 
approach is set out. Approaches, wherever possible, will follow those set out in EMPA-
KIDNEY’s main data analysis plan (SOP11; EDMS#6290). 
 
Note: this pre-specified Data Analysis Plan re-orders the priority of some of the assessments 
set out in the BCM substudy Protocol Supplement (EDMS#6251). Certain assessments have 
been moved from secondary to tertiary assessments, and a new key secondary assessment 
introduced. This follows a more detailed review of data whilst compiling this plan. This pre-
specified Data Analysis Plan therefore supersedes the proposed assessments set out in the 
Protocol Supplement and prevails in the event of any discrepancies between the two 
documents. In addition to the pre-specified comparisons, other post-hoc analyses may be 
performed with due allowance for their exploratory and, perhaps, data-dependent nature. 
 
 
 
 


           
 
                        
Page 5   
BCM substudy Data Analysis Plan (EDMS 7635) 
4 
KEY FLUID OVERLOAD DEFINITIONS  
There is no standard nomenclature for BCM-derived fluid overload parameters in existing 
literature, with a range of terminology and threshold values to infer clinical significance 
employed. We have used the following approach to report the EMPA-KIDNEY BCM substudy. 
 
Terminology 
Definition 
Fluid Overload 
Overhydration in litres, computed as the difference between expected 
(based upon weight and body composition) versus measured 
extracellular water (ECW) volume (1), with positive values 
representing excess fluid.  
Fluid Overload = ECWmeasured - ECWexpected. 
Relative Fluid Overload 
Overhydration index* relative to measured ECW volume, expressed as 
a percentage (2).  
Relative Fluid Overload = Fluid Overload ÷ ECWmeasured. 
Clinically 
Significant        
Fluid Overload 
Moderate 
Relative Fluid Overload >7% to ≤15% [where 7% reflects the 90th 
percentile in a healthy reference population and is approximately 
equivalent to absolute Fluid Overload of +1.1L (3)]. 
Severe 
Relative Fluid Overload >15% [which represents the highest quartile in 
a haemodialysis reference population (1, 2); approximately equivalent 
to absolute Fluid Overload of +2.5L (2-5)].  
 
*Although scientific literature has used the term “overhydration index” to refer to both absolute Fluid 
Overload in litres and Relative Fluid Overload (6, 7), we consider it to most accurately describe 
overhydration indexed to ECW. 
 
 
 


           
 
                        
Page 6   
BCM substudy Data Analysis Plan (EDMS 7635) 
5 
BASELINE CHARACTERISTICS 
In order to assess balance of baseline characteristics between randomized arms of BCM 
substudy, the following variables recorded at Randomization (or at Screening) will be 
presented for each of the empagliflozin and placebo groups. All participants with at least one 
valid BCM measurement will be included, with missing baseline BCM values imputed using 
methods set out in section 7.1.  
 
Note that these are a subset of the characteristics pre-specified in the main Data Analysis 
Plan (SOP11; EDMS#6290) plus other measures of anthropometry and BCM measurement 
variables. Categories will be consistent with those from the main trial publications or subgroup 
analyses: 
 
a. History of prior disease:  
i. 
Diabetes mellitus (presence vs absence);  
ii. Self-reported heart failure (presence vs absence); 
iii. Primary renal diagnosis (diabetic kidney disease, hypertensive/renovascular 
disease, glomerular disease, other  or unknown 
0F1) 
b. Patient characteristics; 
i. 
Age (continuous and categorised: <60; ≥60 <70; ≥70 years); 
ii. Sex (male vs female); 
iii. Race (White, Black/African American, South Asian, Southeast Asian, Mixed or 
Other); 
iv. Smoking status (ever smoked regularly at Randomization, yes vs no); 
v. Weight in kg*; 
vi. Body mass index (BMI) (continuous and categorised: <25; ≥25 <30; ≥30 
kg/m2); 
vii. Waist-to-hip ratio*; 
viii. Extracelllular water (ECW) in litres*; 
ix. Intracellular water (ICW) in litres*; 
x. Fluid Overload in litres*;  
xi. Relative Fluid Overload (%)*; 
xii. Clinically Significant Fluid Overload (%, presence vs absence)*; 
- 
Moderate 
 
1 Other includes tubulointerstitial disease, familial/hereditary nephropathies, other systemic disorders 
and miscellaneous renal disorders. Glomerular disease is subcategorised as follows: focal segmental 
glomerulosclerosis, IgA nephropathy, membranous nephropathy, minimal change disease and other 
glomerular disease. 


           
 
                        
Page 7   
BCM substudy Data Analysis Plan (EDMS 7635) 
- 
Severe (see section 4 for definitions)  
xiii. Lean tissue index (LTI) (lean tissue mass [LTM] indexed to height) *; 
xiv. Fat tissue index (FTI) (adipose tissue mass [ATM] indexed to height) *; 
xv. Systolic blood pressure (continuous and categorised: <130; ≥130 <145; ≥145 
mmHg);  
xvi. Diastolic blood pressure (continuous and categorised: <75; ≥75 <85; ≥85 
mmHg); 
c. Laboratory values at Randomization:  
a. CKD-EPI estimated glomerular filtration rate (eGFR) (continuous and 
categorised: <30, ≥30 <45, ≥45 mL/min/1.73m2 estimated from central 
enzymatic creatinine [or local creatinine where central value unavailable]) 
b. Urinary albumin:creatinine ratio (ACR): (continuous and categorised: <30, ≥30 
≤300, >300 mg/g) 
c. Glycosylated haemoglobin (HbA1c) (continuous and categorised: <39 
[normoglycaemia], ≥39<48 [pre-diabetes], ≥48<75 [well-controlled diabetes], 
≥75 [poor glycaemic control] mmol/mol, or missing 
d. N-terminus prohormone of brain natriuretic peptide (NT-proBNP) (continuous 
and categorised: <110, ≥110 <330, ≥330 ng/L) 
e. Haematocrit (continuous and categorised: <37%; ≥37% <41%; ≥41%) 
d. Medication use at randomization:  
i. 
RAS inhibition (yes vs no);  
ii. Diuretics (yes vs no, and analyses by type [loop vs thiazide vs mineralocorticoid 
receptor antagonist vs other potassium-sparing]. 
iii. Antidiabetic medications (yes vs no, and analyses by type [biguanide vs 
sulphonylurea vs insulin vs DPP-4 inhibitor vs GLP-1 agonist vs other] 
 
* continuous and categorized into approximate thirds of the distribution. 
 
In general, baseline characteristics presented in publications will include all those listed above, 
with those provided in main versus subsidiary tables selected based upon relevance to the 
publication. For continuous variables, mean (standard deviation) will be presented unless the 
variable has a skewed distribution, in which case median (interquartile range) will be used. 
For all categorical variables, the number and percentage of participants in the category will be 
presented. All possible categories will be displayed, zero-filled where necessary, the category 
‘missing’ will only be displayed (e.g. in footnotes) if there are actually missing values.  
 
 
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
6 
DEFINITIONS OF KEY RANDOMIZED ASSESSMENTS 
BCM measurements were specified to be performed at Randomization, 2 and 18 months of 
Follow-up Visits (EDMS#6251). At these visits, weight, waist circumference, and hip 
circumference were measured together with blood and urine for central analysis and storage. 
The COVID-19 pandemic caused a substantial proportion of face-to-face Follow-up Visits to 
be delayed, however BCM measurements were permitted at later attended Follow-up Visit 
appointments, as outlined in the table below. Unless otherwise specified, all analyses will 
involve an intention-to-treat comparison among all randomized participants with at least one 
valid BCM measurement during Follow-up of the effects of allocation to empagliflozin versus 
placebo during the scheduled treatment period (i.e. all participants will be included irrespective 
of whether they take none, some or all of their allocated treatment) (8-10). Handling of missing 
valid BCM measurements is described in section 7.1. 
 
Scheduled Follow-up Visits relative to the Randomization Visit date 
Trial visit 
number 
Follow-up month 
Follow-up period  
Ideal Follow-up day 
1 
2 
≥30, <400 days 
60 days 
4 
18 
≥400 
days, 
until 
Final 
Follow-up*  
540 days 
* Assume <680 days for maximum window for purposes of calculating weighting. 
6.1 
Hypotheses 
For all statistical tests (other than tests for heterogeneity or trend), the null hypothesis will be 
that the effect of allocation to empagliflozin on the parameter of interest (e.g. Fluid Overload) 
in the target population is the same as the effect of allocation to placebo (and hence the 
alternative hypothesis will be that the effect of allocation to empagliflozin is not the same as 
the effect of allocation to placebo). 
 
6.2 
Primary randomized assessment 
The primary assessment will be the effect of allocation to empagliflozin on mean absolute 
Fluid Overload in litres. Effects on Relative Fluid Overload (overhydration indexed to ECW, 
expressed as a percentage) will be presented alongside. Effects will be averaged over the two 
Follow-up time points (with weights proportional to the amount of time between visits, see 
section 7.2.1), adjusted for Randomization Fluid Overload values. The details of analysis 
methods for the primary assessment are described in section 7.2.1. 
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
6.3 
Key secondary randomized assessment 
The key secondary composite outcome combines clinical outcome data with BCM 
measurements. Important data on fluid overload captured by BCM measurements is missed 
when remote Follow-up visits are necessary (e.g. as a result of the COVID-19 pandemic) or 
after death, so the composite outcome serves to capture all recorded data on fluid overload 
and its clinical consequences (whether measured by BCM or reflected in reported adverse 
events). The key secondary assessment is time-to-first development or worsening of Clinically 
Significant Fluid Overload. The composite outcome is defined as: 
• Death from Heart Failure; 
• Hospitalization for Heart Failure (as defined for the main trial analyses in SOP11; 
EDMS#6290); or 
• Development of moderate Clinically Significant Fluid Overload (defined as >7% to 
≤15% Relative Fluid Overload) among those without any Clinically Significant Fluid 
Overload at baseline; or 
• 
Development of severe Clinically Significant Fluid Overload (defined as >15% 
Relative Fluid Overload) among those without this outcome at baseline.  
The analysis method is described in section 7.2.2. 
 
6.4 
Other secondary randomized assessment 
The other secondary assessment is to test whether the effects of empagliflozin 10mg versus 
matching placebo on Fluid Overload vary with time – in addition to the primary randomized 
assessment, analyses will be presented for the separate early (2-month) versus late (18-
month) time points. The analysis method is described in section 7.2.3. 
 
6.5 
Tertiary randomized assessments including subgroup analyses 
Tertiary assessments include: 
i. Whether any effects of empagliflozin 10mg versus matching placebo are modified by 
baseline factors listed in section 5 for the primary assessment (absolute Fluid Overload). 
Subgroups based on sex, diabetes status, NT-proBNP, and eGFR will be the key subgroups 
and will be emphasised in presentation and interpretation. The sensitivity of subgroup 
assessments to indexing to ECW will be assessed by repeating subgroup analyses for the 
outcome of Relative Fluid Overload.  
 
ii. The effects of empagliflozin 10mg versus matching placebo overall, and also early versus 
later during follow-up on: 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
a. 
Extracellular water (ECW) 
b. 
Intracellular water (ICW) 
c. 
Lean tissue index (LTI) (lean tissue mass [LTM] indexed to height)  
d. 
Fat tissue index (FTI) (adipose tissue mass [ATM] indexed to height) 
e. 
Body weight 
f. 
BMI 
g. 
Waist circumference 
h. 
Hip circumference 
i. 
Waist-to-hip ratio 
 
iii. The effects of empagliflozin 10mg versus matching placebo on the four separate 
components of the key secondary outcome of development or worsening of Clinically 
Significant Fluid Overload. 
 
iv. The effects of empagliflozin 10mg versus matching placebo on regression of Clinically 
Significant Fluid Overload from Severe (>15%) to Moderate (>7%); Severe to normal (≤7%); 
or Moderate to normal.  
 
The analysis method for tertiary assessments is described in section 7.2.4. 
 
6.6 
Additional exploratory analyses 
Additional exploratory analyses are planned however these are beyond the scope of this 
DAP and will be described in detail elsewhere.  
 
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
7 
STATISTICAL METHODOLOGY 
7.1 
Handling of missing and extreme values  
Participants with a missing baseline BCM measurement will still be included in analyses if 
subsequent BCM measurements are obtained within the 2- and/or 18-month Follow-up 
windows. Missing baseline BCM measurements will be imputed with the average observed 
value (in both treatment groups combined). Sensitivity analyses will be performed limited to 
participants with complete baseline BCM data. Participants with missing baseline values 
relevant to subgroup analyses will be included in the subgroup containing the average value 
(or the most frequent category for a binary variable). Missing Follow-up BCM measurements 
including Fluid Overload at 2 and 18 months will be handled in the mixed model repeated 
measures (MMRM) approach (as outlined in section 7.2.1).  
 
7.2 
Methods of analysis 
7.2.1 Primary randomized assessment 
Absolute Fluid Overload in litres will be analysed as a continuous variable. Extreme outliers 
(defined as >2 standard deviations from the mean) will be reviewed prior to unblinding to 
assess data quality and plausibility (see Appendix section 8.1). These analyses will be 
completed before any randomized comparisons are conducted. Differences in Fluid Overload 
between treatment groups will be assessed using a mixed model repeated measures (MMRM) 
approach adjusted for the elements included in the minimization algorithm which determined 
treatment allocation (age, sex, prior diabetes, eGFR, and urinary ACR [but not region as the 
BCM substudy was only conducted in Europe]). 
 
The primary assessment will focus on a weighted average of the values at the two Follow-up 
time points with weighting based on the relative size of each Follow-up window as set out in 
section 6. As the first Follow-up window (2-month Follow-up) is 370 days (days 30-400 post-
Randomization) and the second window (18-month Follow-up) assumed to be 280 days (days 
400-680 post-Randomization), this effectively weights information at the first Follow-up visits 
as 55% compared to 45% at the second. This is appropriate as we hypothesise that there will 
be a greater effect of empagliflozin versus placebo on Fluid Overload at 2 months versus 18 
months as the effect of empagliflozin on Fluid Overload is expected to develop rapidly and 
diminish over time. Additionally, changes to other medication which can influence fluid balance 
may occur over time. Time will be included in the model as a categorical variable to avoid 
assuming a linear association between treatment allocation and Fluid Overload over time. The 
model will include fixed, categorical effects of treatment allocation, treatment-by-time 
interaction, and the prognostic variables used in the minimization algorithm (in the same 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
categories used in the minimization process) along with continuous effects of baseline 
(randomization) measurements and baseline-by-time interaction. The within-person error 
correlations will be assumed to be unstructured.  
 
7.2.2  Assessment for key secondary randomized assessment 
Time-to-first event analyses will use adjusted Cox regression. The general statistical methods 
and approaches to subgroup analyses are set out in the main Data Analysis Plan (SOP11; 
EDMS#6290). Follow-up for the clinical components of the composite outcome will be 
censored according to the main Data Analysis Plan. Follow-up for the BCM-derived 
components of the development or worsening of Fluid Overload outcomes (see section 4 for 
definitions) will be censored on the day after the last valid BCM measurement (but these 
individuals may remain at risk of clinical outcomes) or at death/withdrawal of consent. 
 
7.2.3 Other secondary randomized assessment   
The effect of treatment allocation on Fluid Overload separately at 2 and 18 months (see 
section 6.4) will be analysed using the same MMRM approach outlined in 7.2.1. 
 
7.2.4 Tertiary randomized assessments including subgroup analyses 
The same MMRM approach outlined in section 7.2.1 will be used for tertiary assessments (i) 
and (ii) as described in section 6.5. Tertiary assessment (i) is an analysis of the primary 
outcome by subgroup. Subgroup analysis will be performed by fitting relevant interaction terms 
for subgroups in the MMRM model with the aim of assessing whether the proportional effects 
in specific subgroups are statistically different from the overall effect. Interpretation will take 
into account the number of subgroups assessed as well as biological rationale. Tertiary 
assessment (ii) will use the same MMRM approach as for the primary assessment (section 
7.2.1). Tertiary assessments (iii) and (iv) which analyse effects of treatment allocation on the 
components of the composite key secondary outcome and regression of Clinically Significant 
Fluid Overload will be analysed according to the same time-to-event approach outlined in 
section 7.2.2.  
 
Further technical documentation to accompany this Data Analysis Plan may also be added as 
an appendix, if additional methodological details for the approaches described in section 7 are 
found to be required.  
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
8 
APPENDIX: DEFINITION OF VALID BCM MEASUREMENTS AND DATA 
HANDLING CONSIDERATIONS 
 
8.1 
Definition of a valid BCM measurement 
To be included in analyses, an EMPA-KIDNEY participant must have at least one valid BCM 
measurement during Follow-up and been allocated to empagliflozin 10mg or matching 
placebo. To be included in analyses, each BCM measurement must have a corresponding 
weight measurement recorded at the same visit, from which BCM parameters can be derived 
according to the procedure set out in EDMS#7248. 
 
Validity of BCM measurements will be assessed, prior to unblinding. Measurements with an 
absolute Fluid Overload value more negative than -5 litres will be excluded due to 
implausibility1F1. Measurements with a Q value2F2 of <80 (site staff were trained to repeat BCM 
measurements if the Q value was <80; EDMS#6240) will be identified for visual inspection of 
the associated Cole-Cole plot3F3 to assess data quality and determine inclusion in analyses. 
Two observers blind to treatment allocation will independently assess Cole-Cole plots by 
visual inspection, applying pre-specified criteria (outlined in section 8.4), with any differences 
resolved by consensus discussion. 
 
Information on completeness of valid BCM data at each visit (i.e. number of participants with 
at least one valid BCM measurement at each visit, no valid BCM measurement but at least 
one invalid measure, or no BCM measurement) will be presented in the substudy CONSORT 
flow diagram. Statistical comparisons by treatment will be presented for the following 
parameters: 
• 
The distribution of Q values for measurements included in the main comparison and 
sensitivity analyses 
• 
The distribution of time-to-measurements from Randomization for each Follow-up 
window. 
 
1 In pilot work, Cole-Cole plots were reviewed for all measurements with absolute Fluid Overload values 
>2 standard deviations from the mean in a preliminary dataset to inform this cut-off. Values more 
negative than -5 litres were consistently associated with poor quality Cole-Cole plots. Conversely, 
outlying positive values were found to consistently have good quality Cole-Cole plots (and are 
considered plausible results). 
2 The Q score is an assessment of data quality generated by the BCM where 100 is a perfect Q value. 
In pilot work, a random subset of 50 measurements with a Q score ≥80 were selected for Cole-Cole 
plot review. Q scores above this threshold were confirmed to be a reliable indicator of good data quality 
in the cohort. 
3 The Cole-Cole plot generated by the BCM device fits a curve to the measured impedance data and 
defines the extracellular and intracellular resistances upon which all body composition data are based. 
Visual inspection of Cole-Cole plots identifies artefact within the impedance data. 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
8.2 
Handling multiple BCM measurements 
8.2.1  Multiple valid BCM measurements at the same visit 
In all analyses, if more than one valid BCM measurement is available at a single Follow-up 
visit (i.e. date), the measurement with the highest Q value will be used and additional 
measurements ignored. In the situation where >1 valid measurements are obtained with an 
identical Q value, the first measurement will be used.  
 
8.2.2 Multiple valid BCM measurements within a Follow-up window 
In all analyses, if valid BCM measurements are made on more than one day within a Follow-
up period, then the valid BCM measurement made on the day nearest the ideal follow-up day 
will be used and other BCM measurement excluded (see section 6 for Follow-up days). In the 
situation where >1 valid BCM measurements are obtained within the Follow-up window on 
dates which are equidistant from the ideal Follow-up date, a mean value will be calculated and 
used in analyses. This is considered a more scientifically robust approach in this unique 
situation due to the hypothesised interaction of time in the association between treatment 
allocation and Fluid Overload which means that selecting one or other equidistant 
measurement on the basis of Q values could introduce bias.  
 
8.2.3 Multiple measurements at different visits on a single BCM card 
Where data for two separate visits is recorded on a single BCM card, valid BCM results will 
be derived for the separate visits, wherever possible. 
 
 
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
8.3 
Data processing: BCM variables  
The BCM provides measurement of: 
• 
Extracellular water (ECW) resistance (denoted as Re) 
• 
Intracellular water (ICW) resistance (denoted as Ri) 
 
BCM data are downloaded to study-specific laptops in a .pat file format and imported into a 
Microsoft Excel™ spreadsheet according to the procedure set out in EDMS#7248.  
 
The following data are extracted from the analysis database to allow processing of the BCM 
data: 
• 
Age, recorded in whole years at the time of each BCM measurement 
• 
Weight, measured in kilograms, at the time of each BCM measurement 
• 
Height, measured in centimetres, at Randomization 
• 
Sex, recorded as male or female, at Randomization 
along with Re and Ri reported by the BCM  
 
Standard formulae will be applied to methodology described by Moissl and Chamney et al (11, 
12) 4F1 to derive the following: 
• 
Body mass index (BMI) in kg/m2 using height and weight 
• 
Extracellular water (ECW) in litres  
• 
Intracellular water (ICW) in litres  
• 
Total body water (TBW) in litres, by addition of ECW and ICW values 
• 
Absolute Fluid Overload in litres 
• 
Relative Fluid Overload (indexed to ECW), expressed as % 
• 
Lean tissue index (LTI) 
• 
Fat tissue index (FTI) 
 
 
 
 
1 Methods will use different coefficients to those available in published the current literature 
(coefficients which have been shared with permission). 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
8.4 
Criteria for rejecting BCM measurements by Cole-Cole plot visual inspection 
 
The two diagrams below provide a basic interpretation of the Cole-Cole plot: 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
When manually reviewing Cole-Cole plots generated by the BCM for quality assurance, the 
following rule will be used to classify measurements as having poor data quality. 
 
KEY CRITERION: In the opinion of the observer blind to treatment allocation, a good quality 
Cole-Cole plot should have the basic structure of a parabola, ignoring any artefacts at the high 
and low frequency end, and the plotted blue curve should closely fit the raw data red. 
Examples of good (“pass”) and poor (“fail”) quality bioimpedance data are provided below: 
 
 
 
 
 
                 
 
              
 
 
 
Note: review of the Cole-Cole plot is not affected by the height or width of the plot, length of 
either end of a parabola, nor its position in the plot region.  
 
 
 
Characteristic frequency (highest reactance) 
Low frequency 
impedances 
High frequency 
impedances 
Resistance 
Reactance 
Direction of increasing 
fluid overload 
Direction of increasing 
fluid depletion 
Resistance 
Reactance 
Parabola with good fit 
of plotted curve 
against raw data 
Ignoring artefact at high 
frequency, acceptable 
parabola with good fit  
Raw data is not 
parabolic in shape & 
consequently poor fit 
Unacceptable fit of 
plotted curve against 
raw data 
Fail 
 
 
 
 
Pass 
 
 
 
 
Fail 
 
 
 
 
Pass 
 
 
 
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
8.5 
Sensitivity analyses 
 
Data quality assessment outlined in section 8.1 will be used to determine data inclusion in the 
primary analysis. Sensitivity analyses will also be conducted to assess the impact of the data 
quality assessments on the effects of empagliflozin versus placebo on the primary randomized 
assessment. These include analyses: 
1. Of all single BCM measurements, irrespective of quality assessment or outlying values 
(i.e. the complete “unreviewed” set) 
2. Restricted to single BCM measurements with a Q value ≥80 (i.e. a stricter criterion 
than the primary approach) 
The criteria outlined in section 8.1 are thought to represent the optimal data quality 
assessment procedure to determine inclusion in the primary analysis and these sensitivity 
analyses represent the two alternative most extreme approaches.  
 
 
 


           
 
                        
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BCM substudy Data Analysis Plan (EDMS 7635) 
REFERENCES 
1. 
Wabel P, Moissl U, Chamney P, Jirka T, Machek P, Ponce P, et al. Towards improved 
cardiovascular management: the necessity of combining blood pressure and fluid overload. 
Nephrol Dial Transplant. 2008;23(9):2965-71. 
2. 
Wizemann V, Wabel P, Chamney P, Zaluska W, Moissl U, Rode C, et al. The mortality 
risk of overhydration in haemodialysis patients. Nephrol Dial Transplant. 2009;24(5):1574-9. 
3. 
Van Biesen W, Williams JD, Covic AC, Fan S, Claes K, Lichodziejewska-Niemierko M, 
et al. Fluid status in peritoneal dialysis patients: the European Body Composition Monitoring 
(EuroBCM) study cohort. PLoS One. 2011;6(2):e17148. 
4. 
Zoccali C, Moissl U, Chazot C, Mallamaci F, Tripepi G, Arkossy O, et al. Chronic Fluid 
Overload and Mortality in ESRD. J Am Soc Nephrol. 2017;28(8):2491-7. 
5. 
Dekker MJ, Marcelli D, Canaud BJ, Carioni P, Wang Y, Grassmann A, et al. Impact of 
fluid status and inflammation and their interaction on survival: a study in an international 
hemodialysis patient cohort. Kidney Int. 2017;91(5):1214-23. 
6. 
Tabinor M, Elphick E, Dudson M, Kwok CS, Lambie M, Davies SJ. Bioimpedance-
defined overhydration predicts survival in end stage kidney failure (ESKF): systematic review 
and subgroup meta-analysis. Sci Rep. 2018;8(1):4441. 
7. 
O'Lone EL, Visser A, Finney H, Fan SL. Clinical significance of multi-frequency 
bioimpedance spectroscopy in peritoneal dialysis patients: independent predictor of patient 
survival. Nephrol Dial Transplant. 2014;29(7):1430-7. 
8. 
Peto R, Peto J. Asymptotically Efficient Rank Invariant Test Procedures. 
1972;135(2):185-207. 
9. 
Peto R, Pike MC, Armitage P, Breslow NE, Cox DR, Howard SV, et al. Design and 
analysis of randomized clinical trials requiring prolonged observation of each patient. I. 
Introduction and design. Br J Cancer. 1976;34(6):585-612. 
10. 
Peto R, Pike MC, Armitage P, Breslow NE, Cox DR, Howard SV, et al. Design and 
analysis of randomized clinical trials requiring prolonged observation of each patient. II. 
analysis and examples. Br J Cancer. 1977;35(1):1-39. 
11. 
Moissl UM, Wabel P, Chamney PW, Bosaeus I, Levin NW, Bosy-Westphal A, et al. 
Body fluid volume determination via body composition spectroscopy in health and disease. 
Physiol Meas. 2006;27(9):921-33. 
12. 
Chamney PW, Wabel P, Moissl UM, Müller MJ, Bosy-Westphal A, Korth O, et al. A 
whole-body model to distinguish excess fluid from the hydration of major body tissues. Am J 
Clin Nutr. 2007;85(1):80-9. 
 
 

Prot_006.pdf: 
                                                                                      
 
 
EMPA-KIDNEY Body composition measurement substudy justification and design 
V1.0 – 02-MAR-2019   
Page  1 of 6 
 
 
EMPA-KIDNEY Body Composition Measurement Substudy 
 
Study Title: 
A multicentre international randomized parallel group double-blind placebo-
controlled clinical trial of EMPAgliflozin once daily to assess cardio-renal 
outcomes in patients with chronic KIDNEY disease  
Sponsor protocol number: 1245-0137 
Protocol identifier: 
 
CTSUEMPA-KIDNEY1.4 2018-04-25 
EudraCT number:     
2017-002971-24 
 
Summary 
This document provides the rationale and design of an EMPA-KIDNEY substudy to measure body 
composition in a subset of the 5000 EMPA-KIDNEY participants using bioimpedenace 
spectroscopy. The substudy does not alter the main protocol in any respect. 
 
Background 
In the EMPA-REG OUTCOME trial, empagliflozin 10-25mg was shown to reduce the composite 
outcome of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke by 
14% compared to placebo (hazard ratio [HR] 0.86, 0.74-0.99) in 7020 people with type 2 diabetes 
mellitus (T2DM) and prior atherosclerotic cardiovascular disease.1 This effect was in large part the 
result of a highly significant 38% (HR 0.62, 0.49-0.77) reduction in cardiovascular death. The pre-
specified secondary outcome of hospitalization for heart failure was reduced by 35% (HR 0.65, 0.50-
0.85).1 Exploration of EMPA-REG OUTCOME data has suggested that the increase in haematocrit 
caused by empagliflozin, a possible surrogate for reductions in plasma volume, was the 
intermediate clinical parameter with the largest mediating effect on the reduction in cardiovascular 
death.2 These observations may have particular relevance in people with chronic kidney disease 
(CKD) who have disturbed salt and water homeostasis which may cause chronic fluid overload 
which in turn contributes to the observed excess of structural heart disease and heart failure.3  
 
In EMPA-REG OUTCOME, allocation to empagliflozin led to a sustained loss of weight (of about 
2Kg from a mean of 86Kg) and a 2cm reduction in waist circumference (from a mean of 105cm).1 
How much of this weight change reflected reduction in total body water versus adipose tissue is 
unknown. A previous trial suggested that, after 2 years, weight loss resulting from SGLT-2 inhibition 
in people with T2DM appears almost completely attributable to reduced adipose tissue (measured 
using dual energy X-ray absorptiometry).5 Lower kidney function substantially reduces glycosuric 
effects of SGLT-2 inhibition, and so reduced calorie loss at lower levels of kidney function may 


                                                                                      
 
 
EMPA-KIDNEY Body composition measurement substudy justification and design 
V1.0 – 02-MAR-2019   
Page  2 of 6 
 
attenuate any loss of adipose tissue. However, no attenuation of the weight-lowering effects of 
SGLT-2 inhibition was identified in those with CKD compared to those without (within the range of 
kidney function studied to date).6-8 Furthermore, meta-analysis of three large placebo-controlled 
trials suggests effects of SGLT-2 inhibition on heart failure are at least as large among those with 
reduced kidney function.9 Part of the preserved effect of SGLT-2 inhibition on body weight and heart 
failure in CKD may therefore result from reductions in excess extracellular water (ECW) being 
preserved in those with CKD, despite attenuated effects on glycosuria. This raises a hypothesis that 
the effects of empagliflozin on excess ECW and fat levels may be different in people with different 
levels of kidney function.  
 
Figure 1: Effect of SGLT-2 inhibition versus placebo on hospitalization for heart failure, by baseline 
kidney function (meta-analysis EMPA-REG OUTCOME, CANVAS and DECLARE) 9 
 
Bioimpedance spectroscopy can assess different resistance patterns in the body which are affected 
by the amount of water present. Low frequency current exclusively passes extracellularly, whereas 
high frequencies can pass through all body water compartments. Comparing spectroscopy readings 
over a range of frequencies it is possible to derive total body water in Litres and separately the 
volume of ECW. From such measurements it is also possible to estimate normally hydrated adipose 
tissue and lean tissue mass, from which an index referred to as "Fluid Overload" (or overhydration) 
can be algorithmically calculated.10 Sustained "Fluid Overload" measured by bioimpedance 
spectroscopy has been associated with increased risk of mortality among people on dialysis,4 and 
some dialysis units are now using bioimpedance spectroscopy measurements clinically to guide 
patients’ fluid management and dialysis prescription. 
 
At each Follow-up Visit, EMPA-KIDNEY participants will have their weight measured and central 
plasma/serum blood samples collected. At Randomization, 2 & 18 months and Final Follow-up Visit, 
they will also have a measure of waist and hip circumference. A substudy using bioimpedance-


                                                                                      
 
 
EMPA-KIDNEY Body composition measurement substudy justification and design 
V1.0 – 02-MAR-2019   
Page  3 of 6 
 
based body composition measurements will ensure uncertainty about the effects of empagliflozin on 
ECW, adipose tissue and particularly "Fluid Overload" will be assessed in a CKD population. 
 
Aims 
The primary aim of this substudy is to use bioimpedance spectroscopy to assess, in a subset of 
EMPA-KIDNEY participants, the effect of empagliflozin 10mg versus matching placebo on "Fluid 
Overload" at the 2 month and 18 month Follow-up Visits. 
 
Secondary aims are to use bioimpedance spectroscopy to assess: 
1. Whether any effects of empagliflozin 10mg versus matching placebo on "Fluid Overload" are 
modified by baseline factors, in particular by level of kidney function, glycosylated haemoglobin, 
body mass index, NT-proBNP, age, sex, RAS inhibitor use, and different diuretics 
2. The effects of empagliflozin 10mg versus matching placebo early and later during follow-up on: 
o ECW 
o Intracellular water (ICW) 
o Adipose tissue mass indexed to weight (i.e. %) 
o Lean tissue mass indexed to weight (i.e. %) 
Exploratory aims are to: 
 
Assess if changes in ECW, ICW, % adipose tissue mass, % lean tissue mass and "Fluid 
Overload" correlate with changes in blood pressure and relevant other biomarkers. 
 
Sample size estimates 
The study will start a vanguard phase in a small number of sites in which bioimpedance 
spectroscopy will be performed at Randomization, 2 months and 18 months of Follow-up Visits. This 
vanguard phase will be expanded to other sites once feasiblity of adding a bioimpedance 
spectroscopy measurement is demonstrated. Feasbility will be based on feedback from the 
participating sites, successful completion of the other protocol-specified procedures and logistical 
considerations. It is estimated that at least 400 (of the 5000) EMPA-KIDNEY participants with follow-
up bioimpedance spectroscopy measurements will provide ample power (>90%, 2p=0.05) to detect 
at least a ±300mL difference in "Fluid Overload" (reference range in healthy adults is ± 1100mL with 
a standard deviation of 900mL) based on an independent 2-sided t-test (Table 1).  
 
Table 1: Sample size calculations for a study with Randomization Visit measurements 
Outcome 
Effect size Standard deviation Required sample size 
"Fluid Overload" (ref range: ±1.1L) 
±300mL 
900mL 
382 


                                                                                      
 
 
EMPA-KIDNEY Body composition measurement substudy justification and design 
V1.0 – 02-MAR-2019   
Page  4 of 6 
 
Note: An estimate of the correlation between successive bioimpedance spectroscopy 
measurements would be required to calculate the reduction in sample size that could be achieved 
by using ANCOVA analyses, but no such longitudinal data has yet been collected in a CKD 
population.  
        
If a bioimpedance spectroscopy measurement at the Randomization Visit is shown to be infeasible, 
the substudy will be modifed to exclude the measurement at the Randomization Visit and only be 
performed at the relatively less busy phases of the study (i.e. measurements will be restricted to the 
2 and 18 month Follow-up Visits). In this design, the sample size would need to increase to 850. 
This is because the absence of a bioimpedance spectroscopy measurement at the Randomization 
Visit means any imbalances in "Fluid Overload" between treatment arms at baseline cannot be 
corrected for. These imbalances could result in either the treatment effect being overestimated or a 
smaller than expected difference in mean "Fluid Overload" at follow-up. However, with a sample 
size of 850, the probability of large baseline imbalances is small, making it unlikely that the 
treatment effect would be overstated by more than 100mL (Table 2). With a sample size of 850, 
there would be sufficient power to detect a reduced difference in mean "Fluid Overload" of ± 200 mL 
at follow-up. This calculation is based on an independent 2-sided t-test using data from a healthy 
population (Note: sample size estimates differ little if dialysis population data are used). 
 
Table 2: Sample size calculations for a study without Randomization Visit measurements 
 
Data Analysis Plan  
The primary analysis will estimate the differences in "Fluid Overload" between treatment groups 
across all time points, regardless of whether a participant received all, some or none of their 
allocated treatment (i.e. intention-to-treat analyses). Secondary outcomes include ECW, ICW, % 
adipose tissue mass, and % lean tissue mass“. Differences in "Fluid Overload” and the secondary 
outcomes between treatment groups overall, and separately at 2 and 18 months, will be calculated 
using linear regression adjusted (or stratified) for the elements included in the minimization 
Sample size 
Assumed 
possible baseline 
imbalance in 
Fluid Overload 
(mL) 
Probability of a 
baseline 
imbalance at 
least this size due 
to chance  
(1-sided) 
Difference between 
groups at follow-up 
(mL) after subtracting 
possible baseline 
imbalance from 
assumed treatment 
effect of 300 mL 
Power to detect 
reduced difference in 
follow-up values at 
2p=0.05 
850 
 
0 
50 
 
Not applicable 
12.6% 
 
300 
250 
 
>99% 
98% 
 
100 
1.1% 
200 
90% 
 
150 
0.03% 
150 
68% 
 
200 
0.0002% 
100 
37% 


                                                                                      
 
 
EMPA-KIDNEY Body composition measurement substudy justification and design 
V1.0 – 02-MAR-2019   
Page  5 of 6 
 
algorithm. The primary analysis will focus on a weighted average of the values at the two time points 
(with weights proportional to the amount of time between visits). Missing measurements will be 
imputed. Results from the imputed analyses will be compared with those from equivalent “complete-
case” analyses, but primary emphasis will be placed on the results after multiple imputation. More 
complete details of statistical methods, including definitions of subgroups, methods of imputation, 
approaches to adjustments and weighting of averages will be set out in a separate full Data Analysis 
Plan which will be consistent with the main study Data Analysis Plan.  
 
Flowchart of Substudy Activities 
 
INVITATION 
 Invite potential participants shortly before or at the time of the Randomization Visit 
 Written informed consent is sought from willing individuals at the first visit when a bioimpedance 
spectroscopy measurement is offered 
RANDOMIZATION VISIT AND AT 2 & 18 MONTHS OF FOLLOW-UP 
 A bioimpedance spectroscopy measurement is added to the protocol-specified study follow-up 
visit procedures 
 
Design 
Eligibility: In selected regions, EMPA-KIDNEY Local Clinical Centres (LCCs) with a Fresenius 
Medical Care Body Composition Monitor (BCM) machine will be invited to join this optional 
substudy. All those participants at these LCCs who have yet to attend the relevant scheduled study 
visit are eligible for invitation. There are no exclusion criteria. 
 
Invitation and methods: Potential participants will be invited to join this substudy at before or around 
the time of their Randomization Visit. At the relevant visit, clinic staff will explain the substudy to 
potential participants using the Participant Information Leaflet and Consent Form. Consenting 
participants will have a measure of bioimpedance made in addition to the protocol-specified follow-
up procedures. Bioimpedance measurements take about 2 minutes to record and pose no risk to 
health (although it is conceivable the 4 self-adhesive pads could rarely cause a skin reaction).  
 
Body Composition Measurement 
Training materials on how to perform Body Composition 
Measurements will be provided. The measurement requires 


                                                                                      
 
 
EMPA-KIDNEY Body composition measurement substudy justification and design 
V1.0 – 02-MAR-2019   
Page  6 of 6 
 
four disposable self-adhesive electrode pads (2x on a wrist and the other 2x on an ankle) to be 
attached to a portable machine whilst a participant is lying supine. Bioimpedance spectroscopy 
readings are made automatically across about 50 frequencies over a range of 5-1000 kHz. The 
measurements take about 2 minutes to make. Data are then automatically transferrable onto a 
Storage Card which is linked securely to the participant by means of a unique Storage Card ID 
entered onto the relevant study visit form on trial’s web-based data entry system (i.e. Storage Cards 
containing results are pseudonymised). The Storage Card will be stored securely before being 
transferred securely to the Central Coordinating Office in Oxford for downloading into the study 
database. Data may be transferred securely to specialists in bioimpedance for Quality Control 
review. 
 
References 
1. 
Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J 
Med. 2015;373(22):2117-2128. 
2. 
Inzucchi SE, Zinman B, Fitchett D, et al. How Does Empagliflozin Reduce Cardiovascular Mortality? Insights From a Mediation 
Analysis of the EMPA-REG OUTCOME Trial. Diabetes Care. 2018;41(2):356-363. 
3. 
Bui AL, Horwich TB, Fonarow GC. Epidemiology and risk profile of heart failure. Nat Rev Cardiol. 2011;8(1):30-41. 
4. 
Zoccali C, Moissl U, Chazot C, et al. Chronic Fluid Overload and Mortality in ESRD. J Am Soc Nephrol. 2017;28(8):2491-2497. 
5. 
Ridderstrale M, Andersen KR, Zeller C, et al. Comparison of empagliflozin and glimepiride as add-on to metformin in patients 
with type 2 diabetes: a 104-week randomised, active-controlled, double-blind, phase 3 trial. Lancet Diabetes Endocrinol. 
2014;2(9):691-700. 
6. 
Petrykiv S, Sjostrom CD, Greasley PJ, Xu J, Persson F, Heerspink HJL. Differential Effects of Dapagliflozin on Cardiovascular 
Risk Factors at Varying Degrees of Renal Function. Clin J Am Soc Nephrol. 2017;12(5):751-759. 
7. 
Kohan DE, Fioretto P, Tang W, List JF. Long-term study of patients with type 2 diabetes and moderate renal impairment shows 
that dapagliflozin reduces weight and blood pressure but does not improve glycemic control. Kidney Int. 2014;85(4):962-971. 
8. 
Cherney DZI, Cooper ME, Tikkanen I, et al. Pooled analysis of Phase III trials indicate contrasting influences of renal function 
on blood pressure, body weight, and HbA1c reductions with empagliflozin. Kidney Int. 2018;93(1):231-244. 
9. 
Zelniker TA, Wiviott SD, Raz I, et al. SGLT2 inhibitors for primary and secondary prevention of cardiovascular and renal 
outcomes in type 2 diabetes: a systematic review and meta-analysis of cardiovascular outcome trials. Lancet. 
2019;393(10166):31-39. 
10. 
Wabel P, Chamney P, Moissl U, Jirka T. Importance of whole-body bioimpedance spectroscopy for the management of fluid 
balance. Blood Purif. 2009;27(1):75-80. 
11. 
Moissl U, Arias-Guillen M, Wabel P, et al. Bioimpedance-guided fluid management in hemodialysis patients. Clin J Am Soc 
Nephrol. 2013;8(9):1575-1582. 
 

Prot_000.pdf: 
 
Page 1 of 42 
EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
EuDRACT: 2017-002971-24 
 
EMPA-KIDNEY Trial Protocol 
 
A multicentre international randomized parallel group double-
blind placebo-controlled clinical trial of EMPAgliflozin once 
daily to assess cardio-renal outcomes in patients with 
chronic KIDNEY disease 
 
 
Does inhibition of sodium-glucose co-transporter-2 with empagliflozin 
prevent kidney disease progression and cardiovascular death in 
patients with chronic kidney disease? 
 
Selective inhibition of sodium-glucose co-transporter-2 (SGLT-2) with empagliflozin causes 
urinary glucose excretion and reduces hyperglycaemia, weight, plasma circulating volume 
and blood pressure. This has been shown to translate safely into reduced clinical risk from 
cardiovascular disease (particularly heart failure and cardiovascular death) in people with 
type 2 diabetes (T2D) and established cardiovascular disease. SGLT-2 inhibition with 
empagliflozin also reduces albuminuria and slows the annual decline in estimated 
glomerular filtration rate in people with T2D who still have preserved kidney function. The 
kidney effects may result from increased sodium delivery to the kidney’s macula densa, 
which in turn causes glomerular afferent arteriolar vasoconstriction and reduced 
intraglomerular pressure. Raised intraglomerular pressure is believed to be central to the 
“final common pathway” of disease progression in chronic kidney disease (CKD). Since 
SGLT-2 inhibition with empagliflozin also causes glycosuria and acute haemodynamic 
changes in kidney function in people without diabetes, empagliflozin may also be 
nephroprotective in conditions without ambient hyperglycaemia, which collectively account 
for 50 to 70% of patients with CKD worldwide. Patients with established CKD are at 
substantial risk of progressing to end-stage kidney disease despite the use of medical 
therapies, including renin-angiotensin system inhibition, so identifying new treatments to 
delay progression is a priority. Moreover, patients with CKD are at high risk of cardiovascular 
death and heart failure, which may also be reduced by empagliflozin. 
 
A streamlined international trial 
 
This randomized trial will compare empagliflozin 10 mg once daily versus matching placebo, 
given on top of standard of care, in around 6000 participants with established CKD, with or 
without diagnosed diabetes mellitus, who are being treated (where tolerated) with an 
appropriate dose of a renin-angiotensin system inhibitor. The study is event-driven, and will 
continue until the required number of primary outcomes has occurred. Follow-up will allow 
reliable assessment of the effects of empagliflozin on kidney disease progression or 
cardiovascular mortality, and other clinical outcomes. The study design is streamlined: extra 
work for collaborating doctors and hospitals will be kept to a minimum, and only essential 
information will be collected. The trial is focused on readily identifiable and important clinical 
outcomes. Participant reported information recorded by participant interview directly into 
bespoke computer systems and centrally measured creatinine are the main means of data 
collection. 
 
Central Coordinating Office (CCO), 
 
 
Tel: 
 E-mail: 
  




 
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EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
EuDRACT: 2017-002971-24 
3.4.1 
Final check of eligibility and compliance before randomization ................................................... 28 
3.4.1.1 Collection of blood and urine samples .................................................................................... 28 
3.4.2 
Random allocation of study treatment ......................................................................................... 28 
3.5 FOLLOW-UP VISITS (2 AND 6 MONTHS AND THEN 6-MONTHLY) ..................................................... 29 
3.5.1 
Recording adverse events and adherence to study treatment .................................................... 29 
3.5.2 
Collection of blood and urine samples ......................................................................................... 29 
3.5.3 
Issuing study treatment and arranging further appointments....................................................... 30 
3.5.4 
Follow-up for randomized participants not attending study clinics ............................................... 30 
3.5.5 
Monitoring of women of child bearing potential ........................................................................... 30 
3.5.6 
Monitoring of people with diabetes mellitus ................................................................................. 30 
3.5.7 
Local Lead Investigator supervision ............................................................................................ 31 
3.6 CENTRAL MONITORING OF PARTICIPANT SAFETY, EARLY RECALL VISITS AND MODIFYING STUDY 
TREATMENT ............................................................................................................................. 31 
3.6.1 
Early Recall Visits ........................................................................................................................ 31 
3.6.2 
Monitoring liver function, potassium, creatinine and AESIs ......................................................... 31 
3.6.3 
Modifying study treatment ........................................................................................................... 31 
3.6.4 
Unblinding of study treatment ...................................................................................................... 32 
3.6.5 
Withdrawal of consent ................................................................................................................. 32 
3.7 CONFIRMATION AND VERIFICATION OF STUDY OUTCOMES (“ADJUDICATION”) .............................. 32 
3.8 CITED REFERENCES ................................................................................................................. 33 
4.1 APPENDIX 1: ORGANISATIONAL STRUCTURE AND RESPONSIBILITIES FOR STUDY DESIGN AND 
CONDUCT ................................................................................................................................ 37 
4.2 APPENDIX 2: VISIT SCHEDULE AND PROCEDURES ....................................................................... 40 
4.2.1 
Clinic procedures ......................................................................................................................... 40 
4.3 APPENDIX 3: STUDY ADDRESSES .............................................................................................. 41 
5.1 VERSION HISTORY.................................................................................................................... 42 


 
Page 4 of 42 
EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
EuDRACT: 2017-002971-24 
TRIAL SYNOPSIS 
 
Trial title 
A multicentre international randomized parallel group double-blind placebo-controlled 
clinical trial of EMPAgliflozin once daily to assess cardio-renal outcomes in patients 
with chronic KIDNEY disease  
Short and lay title 
EMPA-KIDNEY (The study of heart and kidney protection with empagliflozin) 
Clinical phase  
III 
Trial design 
Randomized double-blind placebo-controlled trial 
Responsibilities 
The study was initiated by the University of Oxford and developed in a collaboration 
with Boehringer Ingelheim, which has provided funding for the trial. Boehringer 
Ingelheim, the sponsor of this trial, has delegated responsibility for the conduct, 
analysis and reporting of the trial to the University of Oxford. 
Boehringer Ingelheim ID 
1245-0137 
ClinicalTrials.gov 
NCT03594110 
EudraCT number 
2017-002971-24 
Trial participants 
Eligibility criteria: 
1. Aged ≥18 years* at Screening; and 
2. Chronic kidney disease (CKD) at risk of kidney disease progression;† 
3. A local investigator judges that the participant neither requires empagliflozin 
(or any other SGLT-2 or SGLT-1/2 inhibitor), nor that such treatment is 
definitely inappropriate; and 
4. No exclusion criteria apply 
Participants will be treated with appropriate doses of renin-angiotensin system (RAS)-
inhibition, unless such treatment is either not tolerated or not indicated. No patient 
currently being treated with empagliflozin (or other SGLT-2 or SGLT-1/2 inhibitor) 
should be taken off this therapy to meet the eligibility criteria. Throughout the study, 
the care of participants will remain the responsibility of their local doctors who will be 
asked to ensure individualized standard of care, including management of 
cardiovascular risk factors and other existing comorbidities (e.g. hypertension, 
diabetes etc.). This should be conducted in the context of prevailing local, national or 
international guidance. 
Planned sample size 
Approximately 6000 participants, including at least one-third with diabetes, one-third 
without diabetes, and up to one-third with a CKD-EPI estimated glomerular filtration 
rate (eGFR) ≥45 and <90 mL/min/1.73m2 at Screening 
Placebo Run-in 
8-12 weeks 
Treatment duration 
Event driven: the trial will continue until at least 1070 participants have experienced a 
first primary outcome after randomization  
Primary outcome 
 
Time to first occurrence of: 
 
Kidney disease progression (end-stage kidney disease‡, a sustained eGFR <10 
mL/min/1.73m², renal death, or a sustained ≥40% decline in eGFR from 
randomization) or  
 
Cardiovascular death 
Secondary outcomes 
Key secondary outcomes: 
 
Time to first hospitalization for heart failure or cardiovascular death  
 
Time to occurrences of all-cause hospitalization (first and recurrent combined) 
 
Time to death from any cause 
Other secondary outcomes: 
 
Time to kidney disease progression 
 
Time to cardiovascular death 
 
Time to cardiovascular death or end-stage kidney disease 
Medicinal Product 
Oral empagliflozin 10 mg 
Formulation, dose, route 
of administration 
Run-in: placebo film-coated tablet once daily (single-blind) for oral administration; 
From randomization: empagliflozin 10 mg film-coated tablet once daily versus 
matching placebo film-coated tablet once daily (double-blind) for oral administration 
* Or “full age” as required by local regulations (e.g. 20 years in Japan)  
† Either (i) estimated glomerular filtration rate (eGFR) ≥20, <45 mL/min/1.73m2; or (ii) eGFR ≥45, <90 
mL/min/1.73m2 with urine albumin:creatinine ratio ≥200 mg/g 
‡ End-stage kidney disease is defined as the initiation of maintenance dialysis or receipt of a kidney transplant 




 
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EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
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1.1 DOES INHIBITION OF SODIUM-GLUCOSE CO-TRANSPORTER-2 (SGLT-2) WITH EMPAGLIFLOZIN 
PREVENT KIDNEY DISEASE PROGRESSION OR CARDIOVASCULAR DEATH IN PATIENTS WITH 
CHRONIC KIDNEY DISEASE (CKD)? 
 
1.1.1 Substantial cardiovascular risk exists for CKD patients despite statin-based 
therapy and antihypertensive therapy 
In high-income countries, the prevalence of CKD is about 10% and is likely to increase as 
average population age rises and diabetes mellitus becomes more prevalent.1, 2 
Cardiovascular risk increases progressively as kidney function declines.3, 4 There is 
evidence that lowering low-density lipoprotein cholesterol and blood pressure in people with 
CKD reduces cardiovascular risk,5, 6 but substantial residual risk remains and no other 
treatments have been shown to reduce cardiovascular risk in this group of patients.  
 
A key feature of cardiovascular disease in CKD is presence of structural heart pathologies 
(e.g. left ventricular hypertrophy and/or dilatation) and heart failure (which may be 
accompanied by coronary heart disease). At least half of patients with advanced CKD (i.e. 
stages 4-5) have abnormal cardiac structure on echocardiography,7,8 increasing to over 80% 
by the time dialysis is initiated.8  
 
1.1.2 Empagliflozin reduces the risk of cardiovascular death in people with type 2 
diabetes and established cardiovascular disease 
Selective inhibition of SGLT-2 causes increased urinary glucose and transiently increased 
sodium excretion. This is associated with reductions in weight and blood pressure as well 
as haemoglobin glycation (HbA1c). Among 7020 patients with type 2 diabetes mellitus (T2D) 
and established cardiovascular disease in the EMPA-REG OUTCOME trial, empagliflozin 
reduced the primary cardiovascular composite outcome (death from cardiovascular causes, 
nonfatal myocardial infarction, or nonfatal stroke) by 14% compared to placebo (hazard ratio 
[HR] 0.86, 95% confidence interval [CI] 0.74-0.99). This was driven by a significant reduction 
in cardiovascular death (HR 0.62, 95% CI 0.49-0.77, nominal p<0.0001). A pre-specified 
secondary outcome of hospitalization for heart failure was reduced by 35% (HR 0.65, 95% 
CI 0.50-0.85).9 
 
The EMPA-REG OUTCOME trial was conducted in participants with relatively preserved 
kidney function (>90% had a baseline estimated glomerular filtration rate [eGFR] >45 
mL/min/1.73m2), and it is unclear whether empagliflozin can prevent cardiac disease in 
patients with more severe kidney impairment.  
 
1.1.3 Substantial risk of kidney disease progression in people with CKD despite 
inhibition of the renin-angiotensin system 
CKD is often a progressive condition, with proteinuria representing a significant risk factor 
for a more rapid decline in kidney function.10 Although patients with early CKD are more 
likely to die before they reach end-stage kidney disease (ESKD), the avoidance of ESKD is 
still highly desirable due to its adverse effects on quality of life and the substantial costs of 
dialysis and transplantation to healthcare providers. Inhibition of the renin-angiotensin 
system (RAS) with angiotensin-converting enzyme inhibitors (ACEi) or angiotensin receptor 
blockers (ARB) reduces albuminuria and slows the rate of progression in proteinuric 
nephropathies, particularly in diabetic kidney disease.11-13 However, a substantial residual 
risk of ESKD remains. Although combination therapy (i.e. ACEi plus ARB) was initially 
thought to be a promising approach, such combined regimens do not delay kidney disease 
progression and may cause hyperkalaemia or acute kidney injury.14 There is therefore a 




 
Page 8 of 42 
EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
EuDRACT: 2017-002971-24 
reabsorption, thereby increasing distal sodium delivery to the macula densa, which has been 
shown to activate a tubulo-glomerular feedback leading to afferent arteriolar 
vasoconstriction, thereby reducing intraglomerular pressure and urinary albumin excretion. 
 
Empagliflozin has also been shown to have a pharmacological effect in people without 
diabetes. In healthy volunteers, empagliflozin 10 mg daily resulted in approximately 50 g/day 
glycosuria, and an initial acute decrease in GFR (an indicator of reduced intraglomerular 
pressure) has been shown to occur in overweight but otherwise healthy volunteers 
(unpublished data, BI clinical trial report 1245.66). Taken together, these observations 
suggest that empagliflozin has haemodynamic effects in the kidney in the absence of 
elevated blood glucose.  
 
It is therefore reasonable to hypothesize that empagliflozin may have beneficial effects on 
kidney disease progression and cardiovascular risk among those with CKD, irrespective of 
the presence of diabetes. Worldwide, the proportion of patients with CKD who have diabetes 
ranges from about 30 to 50% so, if empagliflozin has beneficial effects on kidney and 
cardiovascular outcomes in CKD, then its use in patients with CKD but without diabetes 
would increase the potential population who might benefit from this drug by 2-3 times.20, 21  
 
1.1.5 The safety of empagliflozin has been established in people with type 2 diabetes  
The empagliflozin clinical development programme has randomized >15,000 trial 
participants to date. About 550 healthy volunteers have been exposed to empagliflozin (up 
to 800 mg in a single dose and up to 50 mg in multiple dosing), with good tolerability. 
Approximately 8500 patients with T2D have been treated with empagliflozin in clinical 
studies, of which more than half have been treated for a year or more.22-30 In all these 
studies, empagliflozin was well tolerated. In the EMPA-REG OUTCOME trial, which had a 
median follow-up of 3.1 years, the frequency of serious adverse events (SAEs) and adverse 
events that led to discontinuation of study treatment among patients allocated empagliflozin 
was no higher than that among those allocated placebo.9, 15 There was no significant 
increase in the frequency of hypoglycaemia with empagliflozin, except when used in 
combination with a sulphonylurea or basal dose insulin.31 Electrolytes were not significantly 
different among those allocated to empagliflozin or placebo.31 Compared to placebo, there 
was an increased frequency of mycotic genital infections. By contrast with the increased risk 
of bone fracture and lower-limb amputation observed with another SGLT-2 inhibitor, 
canagliflozin,32 there was no such adverse safety signal observed when over 12,000 patients 
with T2D from placebo-controlled empagliflozin clinical trials (including EMPA-REG 
OUTCOME) were analysed together.31 Further safety analyses from EMPA-REG 
OUTCOME showed that the adverse event profile of empagliflozin in patients who had 
impaired kidney function at baseline (i.e. eGFR <60 mL/min/1.73m2), a potentially vulnerable 
population, was consistent with that reported in the overall trial population.15 In summary, 
the EMPA-KIDNEY trial aims to assess whether empagliflozin reduces the risk of kidney 
disease progression or cardiovascular death in people with CKD, irrespective of whether 
they have diabetes, and whether the benefits of treatment outweigh any adverse effects.  




 
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EuDRACT: 2017-002971-24 
albumin:creatinine ratio (both based on local laboratory results at screening), and region.33 
The algorithm includes a stochastic element (treatment is assigned to the arm determined 
by the minimization algorithm with a probability of 0.9 and by a random number generator 
with a probability of 0.1). Given the stochastic element of the randomization, re-
randomization methods for the analysis are not considered necessary and only traditional 
methods of analysis are planned. Randomized participants will be issued with a 7-month 
supply of study treatment consisting of empagliflozin 10 mg or matching placebo. One tablet 
is to be taken daily with or without food. To ensure a dose interval of about 24 hours, the 
medication should ideally be taken at approximately the same time every day. 
2.3 DATA ANALYSIS PLAN 
 
2.3.1 Main and subsidiary assessments 
2.3.1.1 Primary assessment 
The primary assessment will involve an intention-to-treat comparison among all randomized 
participants, using a Cox model adjusting for each of the minimization variables (see above), 
of the effects of allocation to empagliflozin versus placebo on the time to the first occurrence 
of: 
 
(i) 
Kidney disease progression (defined as ESKD, a sustained decline in eGFR to <10 
mL/min/1.73m2, renal death, or a sustained decline of ≥40% in eGFR from 
randomization); or  
(ii) 
Cardiovascular death. 
 
ESKD is defined as the initiation of maintenance dialysis or receipt of a kidney transplant.  
 
To ensure bias is not introduced by differences between treatment arms in the extent to 
which extra eGFR measurements are made outside of scheduled follow-up visits, the term 
‘sustained’ in respect of a decline in eGFR (to <10 mL/min/1.73m2, or of ≥40% from baseline) 
is that it is either (a) measured at two consecutive scheduled study follow-up visits; or (b) 
measured at the last scheduled study follow-up visit or the last scheduled visit before death 
(or withdrawal of consent). 
 
2.3.1.2 Secondary assessments 
If the primary outcome is statistically significant (either at the interim or final analysis), the 
key secondary outcomes will then be tested. The secondary assessments will involve 
intention-to-treat comparisons among all randomized participants of the effects of allocation 
to empagliflozin versus placebo during the scheduled treatment period on: 
 
(i) 
Key secondary outcomes: 
a) 
Time to first hospitalization for heart failure or cardiovascular death; 
b) 
Time to occurrences of all-cause hospitalizations (first and recurrent 
combined); 
c) 
Time to death from any cause. 
 
 


 
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EuDRACT: 2017-002971-24 
(ii) 
Other secondary outcomes: 
a) 
Time to first occurrence of kidney disease progression; 
b) 
Time to cardiovascular death; 
c) 
Time to cardiovascular death or ESKD. 
 
In testing the key secondary outcomes, their p-values will be corrected for multiple testing 
using the Hochberg “step-up” procedure that controls the familywise error rate. Other 
secondary outcomes will be assessed without adjustment for multiplicity at a nominal level 
of α = 0.05 (two-sided). 


 
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EuDRACT: 2017-002971-24 
2.3.2 Safety, biochemical and exploratory assessments 
2.3.2.1 Safety assessments 
Safety assessments will involve intention-to-treat among all randomized participants and, 
where appropriate, on-treatment analyses of the effects of allocation to empagliflozin versus 
placebo during the scheduled treatment period on: 
 
(i) 
SAEs due to: 
(a) Urinary tract infection, overall and separately by sex; 
(b) Genital infection, overall and separately by sex; 
(c) Hyperkalaemia; 
(d) Acute kidney injury; 
(e) Dehydration; 
 
(ii) 
AEs of Special Interest (AESIs): 
(a) Liver injury, both overall and separately by cause (defined as ALT or AST ≥5x 
Upper Limit of Normal [ULN] or the combination of ALT or AST ≥3x ULN with 
bilirubin ≥2x ULN; measured in the same blood sample at study follow-up or early 
recall visits; see Section 3.5.2); 
(b) Ketoacidosis, both overall and, separately, by baseline diabetes status; 
(c) Lower limb amputations (overall and by level); 
 
(iii) 
Other AEs relevant to the study question: 
(a) Bone fractures, both overall and separately by site and aetiology (i.e. 
distinguishing those resulting from high and low impact trauma); 
(b) Severe hypoglycaemia (defined as low blood sugar causing severe cognitive 
impairment which requires assistance from another person for recovery);  
(c) Symptomatic dehydration (defined as whether or not a participant has 
experienced symptoms they attribute to dehydration, such as feeling faint or 
fainting); 
 
(iv) 
Hospitalization by specific causes†; 
 
(v) 
SAEs both overall and, separately, by category†; 
 
(vi) 
Discontinuation of study treatment overall and by various causes (including SAEs†, 
non-serious adverse events†, and other reasons);  
 
† based on Medical Dictionary for Drug Regulatory Activities (MedDRA) System Organ Class 
classification 


 
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EuDRACT: 2017-002971-24 
 
(vii) 
Changes in weight and systolic and diastolic blood pressure from baseline. 
 
2.3.2.4 Health economic assessments 
The study results may, if appropriate, be used to conduct health economic assessments 
regarding the use of empagliflozin. An analysis plan will be pre-specified if any such 
analyses are considered worthwhile. 
 
2.3.3 Statistical analysis 
A full Data Analysis Plan will be finalised prior to any unblinding of study results. Briefly, all 
participants randomized to empagliflozin will be compared with all participants randomized 
to placebo, regardless of whether a participant received all, some or none of their allocated 
treatment (i.e. intention-to-treat analyses). A participant may contribute to more than one 
assessment if they have events of more than one type (e.g. hospitalization for heart failure 
followed by ESKD). For the time-to-event analyses survival analytic methods will be used to 
evaluate the time to the first event during the entire study period. For each categorical 
outcome, Cox proportional hazards regression adjusted for the prognostic variables used in 
the minimization algorithm (age, sex, prior diabetes, eGFR, urinary albumin:creatinine ratio, 
and region) will be used to estimate the hazard ratio comparing all those allocated active 
empagliflozin with all those allocated placebo. Estimates of the hazard ratio will be shown 
with 95% confidence intervals, and Kaplan-Meier estimates for the time to each of the 
primary and secondary outcomes will also be plotted. For the secondary outcome of all-
cause hospitalization, the analysis will examine all events (i.e. not just the first event in each 
participant). 




 
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The safety profile of empagliflozin has been well-studied in previous trials.9, 15, 22-31 
Therefore, in line with regulatory guidance,35 collection of safety data will be streamlined.  
 
2.5.1.1.1 Non-serious adverse events 
Non-serious AEs will only be recorded if they: 
(a) Lead to discontinuation of study treatment; or  
(b) Are one of the following: 
 Bone fracture (with additional information recorded about fracture site and aetiology 
[i.e. distinguishing those resulting from high and low impact]) 
 Severe hypoglycaemia (as defined in Section 2.3.2.1) 
 Episodes of gout 
 Symptomatic dehydration (as defined in Section 2.3.2.1) 
 An Adverse Event of Special Interest (AESI; see Section 2.5.1.1.2) 
 Events that could lead to amputation (which include diagnosis or treatment for 
peripheral arterial disease, peripheral neuropathy, diabetic foot ulcer, and lower limb 
infection or gangrene). 
 
2.5.1.1.2 Adverse Events of Special Interest (AESI) 
The following AEs will be recorded regardless of whether they fulfil the criteria for a SAE: 
 Liver injury  
 Ketoacidosis 
 Lower limb amputations (overall and by level). 
 
All new AESIs will be reviewed each working day by 
 (
) 
clinicians and relevant additional details sought promptly (see Section 3.6.2). Detailed 
reports on AESIs will be provided by the 
 to Boehringer Ingelheim at regular intervals. 
 
2.5.1.1.3 Serious Adverse Events (SAEs) 
SAEs are defined as those adverse events that: 
 Result in death 
 Are life-threatening 
 Require inpatient hospitalization or prolongation of existing hospitalization; 
 Result in persistent or significant disability or incapacity 
 Result in congenital anomaly or birth defect 
 Are important medical events in the opinion of a responsible Local Investigator (i.e. 
not life-threatening or resulting in hospitalization, but may jeopardise the participant 
or require intervention to prevent one or other of the outcomes listed above).  
 
For the purposes of this trial, certain pre-specified Preferred Terms (e.g. “agranulocytosis”, 
“interstitial lung disease”), and all cancers will always be considered Seriousa.  
 
Pregnancy will not be considered an AE in this trial, but must be reported promptly (within 
24 hours) to the Regional Co-ordinating Centre (RCC) or 
 and then followed up using 
Pregnancy Monitoring Forms. 
 
2.5.1.2 Recording and review of relevant AEs by LCC staff 
All relevant AEs (as defined in Section 2.5.1.1) reported by participants at each study visit 
interview will be recorded and assessed by trained LCC clinic staff (usually the LCC 
Research Coordinator) directly on the study computer-based data entry system (see Section 
                                            
a In accordance with the European Medicines Agency initiative on Important Medical Events.  
Note: New cancer diagnosis and recurrence of pre-existing cancer should all be recorded. 


 
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2.6.3), regardless of whether the participant continues to take study treatment or not. If the 
study team become aware of SAEs or AESIs between study visits, they are requested to 
report them within 24 hours. If LCC clinic staff cannot access the computer-based data entry 
system, they must contact their RCC to report the AE within that timeframe. After completion 
of the trial, investigators do not need to actively monitor participants, but could report SSARs 
or related AESIs through telephone contact to the RCC or 
 
 
The electronic SAE form will capture the following information for all SAEs: 
 Unique study identification number of the participant 
 Unique SAE form identification number 
 The time and date that the SAE form is completed 
 The source of the report (e.g. participant, relative, study nurse, Local Investigator, or 
other doctor) 
 A description of the event: Event descriptions will be recorded by the trained clinic 
staff using MedDRA Preferred Terms. If an appropriate term cannot be identified, 
advice can be sought from the Local Investigator or a 
 study clinician, or the 
description can be recorded as free-text and subsequently coded by 
 study 
clinician, blind to study treatment allocation 
 The reason for believing the AE to be serious (i.e. resulted in death, life-threatening, 
hospitalisation, disabling, congenital anomaly in offspring, other important medical 
event) 
 The date the event started 
 The place where the event was diagnosed or managed (e.g. hospital inpatient, 
hospital outpatient, participant’s home) 
 The name of the place where the event was diagnosed or managed (if appropriate) 
 Number of nights spent in hospital (if applicable) 
 The outcome (ongoing, recovered, death, unknown) 
 Whether the event is thought likely to be due to study treatment. In making this 
assessment, there should be consideration, based on the available information, of 
the pharmacology of the drug and drug class, probability of an alternative cause, the 
timing of the reaction with respect to study drug, the response to withdrawal of the 
study drug, and (where appropriate) the response to subsequent re-challenge or dose 
change. 
 
Such detailed information will also be collected for all AESIs. 
 
The electronic non-serious AE form will capture the following information: 
 
Unique study identification number of the participant 
 
Unique AE form identification number 
 
The time and date that the AE form is completed 
 
A description of the event (as describe above) 
 
The date the event started 
 
The outcome (ongoing, recovered, unknown) 
 
Whether the event is thought likely to be due to study treatment (as above). 
 
Local Investigators are required to review all AEs recorded by those LCC Research Co-
ordinators who have been delegated the task of recording AEs.   
 


 
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2.5.1.3 Collection of Additional Information for Suspected Serious Adverse 
Reactions (SSARs) by 
 
Any SAE that is considered, with reasonable possibility, to be due to study treatment by 
either Local Investigators, appropriately delegated LCC clinic staff or 
 study clinicians 
(or Boehringer Ingelheim staff), is potentially a SSAR. The 
study clinician will obtain 
standard information, including participant study number, identity of reporting person, 
description of event, and reason for attribution to study drug. All such reports will then be 
forwarded urgently to a 
 Clinical Coordinator (or their delegated 
 study clinician 
deputy), who will review the evidence for seriousness and relatedness (in discussion with 
the LLI if necessary), and seek any additional information required (including relevant 
information relating to medical history and treatment both prior to and following 
randomization, and prior to/at the time of onset of the SSAR).  
 
2.5.1.4 Expedited reporting of SUSARs and exemptions from expedited reporting 
SSARs that are unexpected according to the Investigator’s Brochure are subject to 
expedited reporting.36, 37 However, in line with recommendations by regulatory authorities, 
anticipated events that either are efficacy endpoints, consequences of the underlying 
disease or are events common in the study population will be exempted from expedited 
reporting in order to protect trial integrity and because based on a single case it is not 
possible to conclude that there is a reasonable possibility that the investigational drug 
caused the event.36, 38 Such events that are exempted from expedited reporting to health 
authorities in this trial are listed below. 
1. Efficacy endpoints: 
 Kidney disease progression (i.e. ESKD) 
 Myocardial infarction 
 Stroke and transient ischaemic attack 
 Heart failure 
 CV death 
 New-onset diabetes mellitus. 
 
2. Common CKD-related eventsb: 
 Acute-on-chronic kidney failure 
 Dialysis and dialysis access related events and complications 
 Bone fractures and parathyroid-related events. 
 
Any SSARs that are considered not exempt will be reported promptly by the 
 to 
Boehringer Ingelheim, and Boehringer Ingelheim will make an assessment of whether the 
event is “expected” or not (based on the latest version of the empagliflozin Investigator 
Brochure). Any SSAR that is unexpected will be considered a potential Suspected 
Unexpected Serious Adverse Reaction (SUSAR) and will be unblinded by a member of the 
 clinical staff with such privilege. 
 
All SUSARs will be reported to relevant regulatory authorities, to the Chair of the Data 
Monitoring Committee (DMC) and, as required, to ethics committees and Institutional 
Review Boards and investigators in an expedited manner in accordance with regulatory 
requirements. 
 
                                            
b The relevant MedDRA Preferred Terms which are exempt are specified in the Adverse Event Reporting 
SOP. 


 
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2.5.2 Interim analyses: role of the independent Data Monitoring Committee 
2.5.2.1 Regular unblinded analyses by the DMC 
The DMC will assess participant safety and the progress of the trial through review of 
unblinded data at specified intervals, and recommend to the Steering Committee and 
Boehringer Ingelheim whether to continue, modify, or stop the trial. Measures are in place 
to ensure blinding of Boehringer Ingelheim, University of Oxford, the Steering Committee 
and all other trial staff and participants. The tasks and responsibilities of the DMC will be 
specified in the DMC charter. The DMC will maintain written records of all its meetings. 
The DMC will request analyses at a frequency relevant to the stage of the study (typically at 
6-12 monthly intervals, with a Chair’s review every 3-6 months) or in response to emerging 
data from other trials. These unblinded analyses of all SAEs and other study outcomes (both 
overall and in key subgroups, including by region) and all expected SSARs will be supplied 
in strict confidence by a statistician not otherwise involved in the trial.  
 
The DMC would be expected to advise the Steering Committee if clear evidence emerged 
of an adverse effect on all-cause mortality (at least 2 standard deviations) or if, in the view 
of the DMC, there was other compelling evidence of hazard that seemed likely to outweigh 
any potential benefit. 
 
Unless advised by the DMC in response to clear evidence of hazard, the Steering 
Committee, collaborators, participants, representatives of the Boehringer Ingelheim, and all 
study staff will remain blind to these results until the end of the study. The DMC is 
independent of the University of Oxford and Boehringer Ingelheim. 
 
2.5.2.2 Early stopping for benefit 
In addition, the DMC may review a single formal interim efficacy analysis once 150 
participants have experienced a first ESKD event (by which time it is expected that 
approximately 60% of all first primary outcomes will have occurred). Full details of the 
stopping guidelines at this interim analysis, including the alpha spent at this analysis and 
the alpha remaining for the final analysis, will be provided in the DMC Charter. Separate 
alpha-spending functions will be used for the testing of the primary and key secondary 
outcomes to control the type I error rate across two analysis time-points, and a gatekeeping 
approach followed by the Hochberg procedure will be used to control the type I error rate 
across multiple endpoints. 
 
Briefly, in order for the DMC to recommend that the trial is stopped early for benefit at this 
formal interim analysis, both of the following conditions must be met: 
 
(1) a reduction in the primary outcome with the Hwang-Shih-DeCani alpha-spending function 
(=-8) used to define the required two-sided p-value and its corresponding critical Cox 
hazard ratio; and (2) a reduction in the secondary composite outcome of time to 
cardiovascular death or ESKD to at least the same critical Cox hazard ratio as observed in 
the primary outcome, but with the proviso that the p-value is constrained to be < 0.05. For 
example, for the scenario when 60% of the first primary outcomes (i.e. 642 first primary 
outcomes) have occurred at the time of the interim analysis, this would equate to stopping 
criteria of: (i) a two-sided p-value <0.002 with a critical Cox hazard ratio <0.78 for the primary 
outcome; and (ii) a critical Cox hazard ratio of <0.78 and a two-sided p-value <0.05 for the 
secondary outcome of time to cardiovascular death or ESKD [with 400 such events and a 
critical Cox hazard ratio of <0.78 a p-value of <0.014 would be observed]. Note the 
secondary outcome of time to cardiovascular death or ESKD is not part of the prospectively 
defined hypothesis testing strategy but is included as an additional stopping criterion to 




 
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potential to have) a substantial impact on the protection of the study participants or the 
reliability of the study results (with full details provided in a Quality Assurance Systems 
SOP). 
 
Throughout the study, the 
 will centrally monitor performance against the predefined 
critical-to-quality factors. This process will predominantly be quantitative in nature and 
remedial actions will be determined based on the detection of deviations and totality of the 
evidence.  
 
The relevant RCC and/or the 
 will arrange monitoring visits to LCCs as considered 
appropriate based on perceived training needs and the results of central process monitoring 
and statistical monitoring of study data (i.e. monitoring visits will be spaced by several 
months). The purpose of such visits will be to ensure that the study is conducted according 
to the protocol, ICH-GCP, and the applicable regulatory requirements, and by helping LCC 
clinic staff to resolve any local issues with the study and by providing additional focused 
training where necessary. Particular attention will be given to the effectiveness of strategies 
to recruit appropriate participants, the consenting process, the completeness of follow-up, 
the maintenance of participant compliance with the study treatments (which will be assessed 
by participant self-report), the reporting of study outcomes and reportable AEs (see Section 
2.5.1), and collection of relevant supporting documentation to support the adjudication 
process (see Section 3.7). With the exception of local laboratory results (where a random 
subset will be assessed), no routine source data review and verification will take place as 
such data are obtained directly from participants (or occasionally from relatives or doctors) 
by interview. Where possible, monitoring visits will include observation of a participant’s 
study visit. A report of each monitoring visit will be prepared by the study monitor and 
provided to LCC, RCC and 
 staff (including the Head of Monitoring) for review, and filed 
appropriately. Copies of these reports will be supplied to Boehringer Ingelheim on request. 
With prior arrangement, representatives of Boehringer Ingelheim may attend monitoring 
visits. Details of monitoring are provided in an On-Site Monitoring SOP. 
 
2.6.2 Supply of study treatment 
Study treatments will be manufactured, packaged, labelled and delivered to each LCC or 
RCC by Boehringer Ingelheim (or their subcontractor) under the direction of the 
 and 
according to Good Manufacturing Practices. An inventory of study drug supplies will be 
maintained on the study computer-based system and monitored at the 
. LCC Local 
Investigators will be responsible for making appropriate arrangements for the storage and 
issuing of study treatments, and for the disposal of unused study drug in accordance with 
study SOPs. 
 
2.6.3 Data management 
All data in the study will be processed electronically using a set of custom-written 
applications developed to meet the requirements of the protocol and to comply with 21 CFR 
Part 11 and other relevant regulatory, legal and information security requirements. The LCC 
staff (usually the LCC Research Coordinator) will use bespoke web-based applications for 
local study management and to enter participant data (including study visit forms and AE 
information) directly into the database. These source data will be held in central databases 
located both at the 
 and at an independent third party where it will remain under the 
control of the Local Investigators (i.e. no paper case report forms exist). Any data queries 
reported by LCCs to the 
or RCC (as per regional arrangements) during the study will 
be recorded onto the computer-based study management system. Data queries will be 
reviewed and managed by the 
 in accordance with an Internal Operating Procedure, 


 
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with data changes only made to pre-defined critical-to-quality data points. Clear electronic 
documentation will be maintained so the original data entry is not obscured and there is an 
audit trail for each entered data error and data change. 
 
RCC and 
 staff will use the suite of administration applications on the computer-based 
system to manage LCCs and study participants, including central clinical supervision (review 
of AEs and laboratory results) by the 
, management of follow-up and compliance, 
tracking of samples for central analysis, collection of supporting documentation for relevant 
events, and clinical outcome adjudication. 
 
All data accesses will require a unique username and password, and any changes to data 
will require the user to enter their username and password as an electronic signature. Staff 
will have access restricted to only the functionality and data that are appropriate to their role 
in the study. 
  
2.6.4 Biological sample assay, transport and storage 
2.6.4.1 Local analysis of eligibility and safety bloods 
Local laboratories will be used in all LCC study clinics for eligibility checks at the Screening 
visit (urine albumin:creatinine ratio [or protein:creatinine ratio, according to local practice], 
and blood creatinine plus liver transaminases [AST or ALT]), at the Randomization visit 
(blood creatinine, potassium, liver transaminases, bilirubin and haematocrit) and for clinical 
safety oversight at each follow-up visit (including blood creatinine, potassium and liver 
transaminases with bilirubin; see Section 4.2.1).  
 
Haematocrit, haemoglobin, phosphate, sodium and corrected calcium will also be measured 
locally at 18 months of follow-up in a subset of about 20% (e.g. UK participants) of the 
surviving population.  
 
2.6.4.2 Central assessment of samples collected at the randomization visit and 
during follow-up 
Samples of both blood and urine are to be collected from all participants at the 
Randomization visit for central analysis and storage, including subsequent DNA extraction 
(subject to relevant consent, see Section 2.6.4.3) at a central ISO 17025 accredited 
laboratory. Central samples will not be used to assess eligibility. Further samples of both 
blood and urine are to be collected from all participants at the 2 month, 18 month (i.e. the 
approximate study midpoint) and Final Follow-up visits. Blood will be collected for central 
analysis of creatinine at the time of every scheduled Follow-up visit (see Section 4.2.1). 
RCCs will supply LCC staff with kits to collect these blood and urine samples. Blood is to be 
kept cool before centrifugation, separation into bar-coded cryovials, and storage at below -
18°C within a day of the study clinic visit. Samples are to be transferred to below -40°C 
within 4 weeks. At appropriate intervals, samples will be collected from the LCCs (by the 
RCC or 
) and transferred to the central laboratory for analysis (see Section 4.2.1) and 
for long-term frozen storage. Full details of sample collection, transport, storage and analysis 
are provided in a separate SOP.  
 
2.6.4.3 Consent approval for unspecified analyses on blood and urine samples 
Sample tubes will be labelled with a unique Sample ID which will be linked to the participant 
and the study visit using the study computer-based data entry system (i.e. samples will be 
pseudonymised). Outside the study clinic, staff involved in the transport, storage and 
analysis of these samples will have no means of linking tubes to an identifiable participant. 
Consent for protocol-specified analyses will be included in the main consent form. In 
addition, all participants will be asked if they would provide Supplementary Consent to allow 


 
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samples that have been collected for central laboratory analyses to be retained and used 
for unspecified analyses in the future. Similarly, Supplementary Consent will be sought to 
permit genetic material in the blood samples to be analysed. In all cases, participants will be 
free to opt in or out of any part of the Supplementary Consent without affecting their eligibility 
for the trial. 
 
2.6.5 Administrative details 
2.6.5.1 Source documents and archiving 
Source documents for the study constitute the clinic visit records held in the study main 
database, results of protocol-mandated local laboratory blood and urine analyses, the 
additional information obtained on reported adverse events that are relevant to the outcome 
measures (see Section 3.7), death certificates, and drug supply records. These will be 
retained for at least 25 years from the completion of the study. Boehringer Ingelheim and 
regulatory agencies will have the right to commission a confidential audit of such records in 
the 
, RCCs, and LCCs provided this does not result in unblinding while the study is in 
progress. 
 
2.6.5.2 Funding 
This study was initiated by 
 University of Oxford and developed as an academic 
collaboration with clinical scientists at Boehringer Ingelheim. Boehringer Ingelheim is the 
sponsor, and will perform regulatory submissions and interactions. It will also provide 
funding and packaged study medication (empagliflozin and matching placebo) for the study. 
Boehringer Ingelheim has delegated other roles to the University of Oxford, which is 
responsible for leading the trial scientifically and methodologically worldwide, including its 
conduct and statistical analysis. It is intended that the study will be conducted in the US in 
collaboration with independent scientists from the 
 
. Data will be collected and analysed independently from the source of funding. 
 
2.6.5.3 Indemnity 
Boehringer Ingelheim will, at all times, indemnify the study investigators and study staff from 
claims that may be made against them for any injury sustained by a study participant as a 
consequence of participation in the study in accordance with this protocol. The indemnity 
will be outlined in detail in the agreements between the 
, RCCs and LCCs (and in a 
letter from Boehringer Ingelheim). 
 
2.6.5.4 End of the within-trial period 
When the minimum number of required study outcomes has accrued (see Section 2.4.1.2), 
or the DMC advises the trial should be stopped early, participants will be invited to Final 
Follow-up visits. This visit may occur earlier than their planned next 6-monthly visit. The end 
of the trial is then defined as the latest of the following two dates: 7 days after the last 
participant’s Final Follow-up visit, or the date of the last 4-week post-Final Follow-up blood 
draw. 
 
2.6.5.5 Publications and reports 
The Steering Committee (which includes representatives from University of Oxford, 
 
 and Boehringer Ingelheim, as well as other individuals with relevant expertise) 
will be responsible for drafting the primary manuscript from the study and will establish a 
publication plan for secondary and supplementary analyses. In general, papers initiated by 
the Steering Committee (including the primary manuscript) will be written in the name of the 
Collaborative Group, with individual investigators named personally at the end of the report 
(or, to comply with journal requirements, in web-based material posted with the report). Draft 
copies of any manuscripts relating to the effects of empagliflozin from this trial will be 


 
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provided to Boehringer Ingelheim for review prior to publication but the decision to submit 
for publication will rest with the Steering Committee. 
 
The Steering Committee will also institute a process by which proposals for additional 
publications (including from clinician scientists within Boehringer Ingelheim seeking to 
further evaluate the benefit-risk profile of empagliflozin and from independent external 
researchers) are considered by the Steering Committee before they begin. The Steering 
Committee will facilitate the use of the study data and approval will not be unreasonably 
withheld. However, the Steering Committee will need to be satisfied that any proposed 
publication is of high quality, honours the commitments made to the study participants in the 
consent documentation and ethical approvals, and is compliant with relevant legal and 
regulatory requirements (e.g. relating to data protection and privacy). The Steering 
Committee will have the right to review and comment on any draft manuscripts prior to 
publication. 
 
2.6.5.6 Substudies 
Proposals for substudies must be approved by the Steering Committee before they begin. 
In considering such proposals, the Steering Committee will need to be satisfied that the 
proposed substudy is of a high quality, and that it will not compromise the main study in any 
way (e.g. by reducing the recruitment rate or compliance with study treatment or overuse of 
stored biological samples). 
 




 
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3.1 ELIGIBILITY FOR THE STUDY 
 
Consenting individuals are eligible for randomization if: 
(i) 
Age is ≥18 yearsc at Screening; 
(ii) 
There is evidence of chronic kidney disease at risk of kidney disease progression 
(see Section 3.1.1); 
(iii) 
A local Investigator judges that the participant neither requires empagliflozin (or 
any other SGLT-2 or SGLT-1/2 inhibitor), nor that such treatment is inappropriate; 
and 
(iv) 
None of the exclusion criteria apply (see Section 3.1.2). 
 
Participants will be treated with appropriate doses of single agent RAS-inhibition with either 
ACEi or ARB unless such treatment is either not tolerated or not indicated (see Section 
3.3.4).  
 
No potential participant currently being treated with empagliflozin (or other SGLT-2 or SGLT-
1/2 inhibitor) should be taken off this therapy to meet the eligibility criteria. 
 
3.1.1 Inclusion criteria 
Evidence of progressive CKD at risk of kidney disease progression is defined on the basis 
of local laboratory results recorded at least 3 months before and at the time of the Screening 
visit, and requires that: 
(a) CKD-EPI eGFR ≥20 <45 mL/min/1.73m²; or 
(b) CKD-EPI eGFR ≥45 <90 mL/min/1.73m2 with urinary albumin:creatinine ratio 
≥200 mg/g (or protein:creatinine ratio ≥300 mg/g)  
 
Note: the number of participants with or without diabetes mellitus (of any type) will be at 
least one-third of each, and the number of participants with an eGFR >45 mL/min/1.73m2 
limited to about one-third. The Steering Committee will monitor these proportions and will 
limit recruitment of particular categories of participant in whom sufficient numbers have 
already been screened or randomized. 
 
3.1.2 Exclusion criteria 
None of the following must be fulfilled: 
(i) 
Currently receiving SGLT-2 or SGLT-1/2 inhibitord; 
(ii) 
Diabetes mellitus type 2 and prior atherosclerotic cardiovascular diseasee with an 
eGFR >60 mL/min/1.73m2 at Screening; 
(iii) 
Receiving combined ACEi and ARBf treatmentd; 
(iv) 
Maintenance dialysis, functioning kidney transplant, or scheduled living donor 
transplantd; 
(v) 
Polycystic kidney disease; 
(vi) 
Previous or scheduled bariatric surgery; 
(vii) 
Ketoacidosis in the past 5 years; 
(viii) 
Symptomatic hypotensiond, or systolic blood pressure <90 or >180 mmHg at 
Screening; 
(ix) 
ALT or AST >3x ULN at Screening; 
(x) 
Hypersensitivity to empagliflozin or other SGLT-2 inhibitor; 
                                            
c Or “full age” as required by local regulation (e.g. 20 years in Japan).  
d Based on self-reports at Screening and Randomization visits. 
e Myocardial infarction, angina, stroke or peripheral arterial disease (including lower limb amputation) 
f Or renin-inhibitor combined with ACEi or ARB. 


 
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(xi) 
Any intravenous immunosuppression therapy in last 3 months; or anyone currently 
on >45 mg prednisolone (or equivalent)d;  
(xii) 
Use of an investigational medicinal product in the 30 days prior to Screening visit; 
(xiii) 
Known to be poorly compliant with clinic visits or prescribed medicationd; 
(xiv) 
Medical history that might limit the individual’s ability to take trial treatments for the 
duration of the study (e.g. severe respiratory disease; history of cancer or evidence 
of spread within last 4 years, other than non-melanoma skin cancer; or recent history 
of alcohol or substance misuse)d; 
(xv) 
Current pregnancy, lactation or women of childbearing potential (WOCBP), unless 
using highly-effective contraceptiong; 
(xvi) 
Type 1 diabetes mellitus. 
 
In addition, individuals will be excluded at the Randomization visit if the participant: 
(i) 
Does not adhere to Run-in treatment; 
(ii) 
Is no longer willing to be randomized and followed for at least 3 years; 
(iii) 
Is considered by a local investigator not to be suitable for randomization (see Section 
3.3.4); or 
(iv) 
Experiences ketoacidosis, heart attack, stroke, or hospitalization for heart failure, or 
hospitalization for urinary tract infection or acute kidney injury during Run-in. 
 
Note that individuals who do not fulfil one or more inclusion criteria, or who fulfil one or more 
exclusion criteria, may be re-screened and later become eligible.  
 
3.2 
 IDENTIFICATION AND INVITATION 
3.2.1 Identification and invitation of potentially eligible participants 
Extensive pre-screening efforts will be made to identify large numbers of potential 
participants at each LCC. The exact methods will vary by centre and by country, and in all 
cases will be subject to appropriate institutional review board approval and compliance with 
data privacy regulations. In general, potentially eligible participants (based on age, blood 
and urine results) will be identified from clinical records (including electronic health care 
records) and contacted to seek their provisional agreement to attend a Screening visit. 
Potential participants will be given information about the study. 
 
3.3 SCREENING VISIT AND PRE-RANDOMIZATION RUN-IN 
3.3.1 Assessment of relevant medical history and eligibility 
LCC clinic staff will recheck basic inclusion criteria are met (e.g. age and the blood/urine 
results used to identify potential participants) then take written informed consent. 
 
3.3.2 Written consent 
Individuals who appear initially to be eligible will have the study explained to them by the 
clinic staff, using the Participant Information Leaflet and Consent Form as a basis for 
discussion. Where relevant, supplementary Consent will also be sought (see Section 
2.6.4.3). Each individual will have an opportunity to initiate discussion, and have time to think 
about their participation in the study, perhaps after discussing it with their family or a local 
doctor. Individuals who choose to do this will be asked to attend a repeat Screening visit 
                                            
d Based on self-reports at Screening and Randomization visits. 
g Highly effective methods of contraception include implants, injectables, combined oral contraceptives (the 
participant must have been on a stable dose for at least 3 months prior to entering the trial), intrauterine device, 
vasectomised partner, or true sexual abstinence (when this is the preferred and usual lifestyle of the patient 
and does not include periodic abstinence [e.g. calendar, ovulation, symptothermal or post-ovulation methods]). 
Use of such methods must be maintained throughout the trial and for 7 days after the end of the trial. 


 
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within a few weeks. Attendees will be discouraged from participating if it is thought unlikely 
that they would be willing and able to continue attending Follow-up visits for at least 3 years.  
 
3.3.3 Confirmation of eligibility and collection of blood and urine samples 
After providing written consent, blood/urine test results will be recorded. Other medical 
history (including primary renal diagnosis and other co-morbidity), non-study medication, 
blood pressure and other factors pertinent to eligibility will be obtained directly from 
participants (rather than from hospital record review) and recorded directly into the 
Screening Form. These inclusion and exclusion criteria will be checked with the assistance 
of the study computer-based system.  
 
A non-fasting blood sample will be taken for local analysis of creatinine and liver 
transaminases (AST or ALT), and a urine sample will be taken for local analysis of urinary 
albumin:creatinine ratio (or, if albuminuria measurement unavailable in local laboratory, 
protein:creatinine ratio). The LCC clinic staff will issue a 15 week supply of placebo tablets 
to eligible participants. 
 
WOCBP, defined as women less than 55 years of age unless surgically sterile or with history 
of a postmenopausal state, will be requested to use highly effective methods of 
contraception. A pregnancy test will be offered if, after questioning about recent menses and 
regularity of menstrual cycle, pregnancy is considered reasonably possible (or if a 
pregnancy test is required by local regulation). 
 
Participants with diabetes will be educated about the risks of diabetic ketoacidosis and the 
actions they should take if they suspect it, and will be provided with a specific information 
card (see Section 3.5.6). 
 
An appointment will be made for the Randomization visit in 8-12 weeks. The participant’s 
doctor(s) will be informed that the participant has entered Run-in. 
 
Following the Screening visit, the locally analysed blood and urine results will be recorded 
onto the study computer-based system, which will provide another assessment of eligibility 
(see Section 3.1). If these results indicate that the participant is not eligible for the trial, they 
may be repeated once if in the opinion of a Local Investigator they were spurious, otherwise 
the participant will be withdrawn from the Run-in period and asked to stop and return all 
placebo Run-in medication. 
 
3.3.4 Review of eligibility and renin-angiotensin system inhibition by a Local 
Investigator 
During Run-in, the LLI (or authorised delegate) will be given a description of the participant’s 
medical history (including primary renal diagnosis), single agent RAS-inhibition treatment 
and blood and urine results all based on the Screening visit, and asked to indicate whether, 
in their view, these results (or any other factor) make the participant unsuitable for entry into 
the randomized phase of the study. Additionally, participants should be randomized only if 
a Local Investigator judges that the participant does not require empagliflozin (or any other 
SGLT-2 or SGLT-1/2 inhibitor), and neither is such treatment inappropriate. No patient 
currently being treated with empagliflozin (or other SGLT-2 or SGLT-1/2 inhibitor) should be 
taken off this therapy to meet the eligibility criteria. 
 
For eligible participants, the LLI (or authorized and medically qualified delegate) will also be 
asked to confirm that the participant is prescribed, in their opinion, an appropriate dose of 


 
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single agent RAS-inhibition (i.e. ACEi or ARB, but not both). Those participants for whom 
RAS inhibition is not considered indicated (e.g. due to concomitant medication or co-
morbidity), or who cannot tolerate RAS inhibition, will still be eligible to enter the trial, but the 
reason for not using RAS-inhibition will be documented. Those participants who, in the 
opinion of the LLI, need to start RAS inhibition or are not on an appropriate dose will be 
excluded from the study (but may be rescreened later, e.g. once established on an 
appropriate dose). 
 
Additionally, throughout the study, the care of participants will remain the responsibility of 
their local doctors, who are asked to ensure appropriate and individualized care. This 
includes appropriate management of risk of kidney disease progression, risk of 
cardiovascular disease, and other conditions which are common in CKD (such as mineral-
bone disorder, renal anaemia, metabolic acidosis). Modifiable risk factors include but are 
not limited to glycaemic control in participants with diabetes, blood pressure control, and 
treatment of dyslipidaemia. It is advised that this is conducted in the context of prevailing 
local, national or international guidance. 
 
3.4 
 RANDOMIZATION VISIT (0 MONTHS) 
3.4.1 Final check of eligibility and compliance before randomization 
For individuals who attend their Randomization Clinic appointment, study eligibility will be 
confirmed (see Section 3.1). The participant will also be asked if they have experienced any 
SAE or significant problems during the Run-in period. Information on other relevant factors 
will also be collected, such as prior history of urosepsis, heart failure and New York Heart 
Association (NYHA) functional classification, history of peripheral neuropathy, diabetic foot 
ulcer, lower limb infection or gangrene, smoking history and alcohol intake, and an 
assessment of health related quality of life is to be made (using the EQ5D-5L questionnaire). 
Details of all non-study treatments will be sought, compliance with Run-in treatment 
checked, and consent information checked. Blood pressure, height, weight, and hip and 
waist circumference will be measured. The participant’s willingness to take study medication 
and attend follow-up visits for at least 3 years will be confirmed. Details will be recorded 
directly onto the Randomization Form on the study computer-based system (which is 
designed to obtain complete information, assess eligibility, and to prompt appropriate 
actions). 
 
3.4.1.1 Collection of blood and urine samples 
Eligible participants will have a blood sample taken for local measurement of creatinine, 
potassium, liver function (ALT or AST, and bilirubin), and haemoglobin/haematocrit. Blood 
and urine samples will also be processed in preparation for subsequent transportation to the 
central laboratory (see Section 2.6.4). 
 
3.4.2 Random allocation of study treatment 
Eligible and consenting individuals will be allocated empagliflozin or matching placebo using 
a minimized randomization program on the study computer-based system (see Section 
2.2.2).33 Participants will be allocated a numbered treatment pack containing a 7-month 
supply of one tablet daily of either active empagliflozin 10 mg or matching placebo. 
 
The numbered treatment packs will be issued to the participant by the LCC clinic staff or 
their local hospital pharmacy. An appointment for the first post-randomization Follow-up visit 
will then be made by the study staff, with guidance from the study computer-based system. 
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Following the Randomization visit, the locally analysed blood results will be recorded onto 
the study computer-based system by the LCC. 
 
3.5 
 FOLLOW-UP VISITS (2 AND 6 MONTHS AND THEN 6-MONTHLY) 
3.5.1 Recording adverse events and adherence to study treatment 
Following randomization, all participants are scheduled to attend Follow-up visits at 2 and 6 
months, and then 6-monthly until the end of the study. 
 
At each visit, details of all hospital admissions and any other SAEs will be sought from 
participants, and questions will specifically be asked about SAEs due to urinary tract 
infection, genital infection, hyperkalaemia, acute kidney injury and dehydration. Information 
about new-onset of diabetes, gout, AESIs (i.e. liver injury, ketoacidosis and lower limb 
amputation), bone fractures, severe hypoglycaemia and symptomatic dehydration will also 
be recorded. The source of the information/data is the report from the participant (or where 
unavailable a relative or other doctor) entered directly into the electronic case report form. 
In this study, paper or electronic hospital notes are not routinely reviewed to identify AEs. 
Any SAE considered to be due to study treatment (i.e. a possible SSAR) is to be discussed 
as soon as possible with a RCC/
 study clinician in order that additional information can 
be collected (see Section 2.5.1.3).  
 
Key changes to non-study medication will be sought, and adherence to study treatment will 
be reviewed. Adherence will be assessed and documented by LCC clinic staff at every study 
visit by asking participants about missed doses and visual inspection of remaining tablets (a 
pill count will not be performed). The amount of study treatment taken since the last visit will 
be estimated and recorded as “most”, “some” or “little/none” (with further guidance on these 
categories provided in the LCC Clinic Manual). The LCC clinic staff will discuss any reasons 
for non-adherence with the participant (and with their LLI or with 
clinical staff if 
necessary) and encourage the participant to take study treatment regularly whenever 
appropriate. For participants who discontinue study treatment, the reason for doing so will 
be sought.  
 
Blood pressure and weight will be measured at each Follow-up visit. At the 18 month and 
the Final Follow-up visit, hip and waist circumference will be measured and health related 
quality of life (using EQ5D-5L questionnaire) will be assessed. Details are to be recorded 
directly onto the electronic Follow-up form on the study computer-based system.  
 
Local Research Co-ordinators will be trained to ask participants to report any relevant AEs 
(related or not) occurring up to 7 days after their Final Follow-Up Visit directly to LCC clinic 
staff. 
 
3.5.2 Collection of blood and urine samples 
At each Follow-up visit, a non-fasting blood sample will be taken for local analysis for 
creatinine, potassium and liver function (ALT or AST, and bilirubin). Results are ideally 
entered onto the computer-based system within 2 working days. At 18 months of follow-up, 
a 20% subset of participants (e.g. UK participants) will also have haematocrit, haemoglobin, 
phosphate, sodium and corrected calcium measured locally.  
 
Four weeks after the Final Follow-up visit, a subset of about 20% of participants (who have 
not started dialysis or have a functioning kidney transplant) will provide a further non-fasting 
blood sample for local analysis of creatinine (known as the 4-week post-Final Follow-up 
blood draw) and a urine sample for local analysis of urine albumin and creatinine.  


 
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At each scheduled follow-up visit a central blood sample will be collected. At the 2 and 18 
month and Final Follow-up visits, urine samples will also be collected (see Section 2.6.4.2).  
 
3.5.3 Issuing study treatment and arranging further appointments 
Provided continuing study treatment remains appropriate, participants will be given a further 
7-month supply of their randomly allocated study treatment (empagliflozin 10 mg or 
matching placebo), and any previously allocated treatment will be retrieved (except at the 
2-month visit). An appointment will then be made for their next scheduled Follow-up visit. 
 
3.5.4 Follow-up for randomized participants not attending study clinics 
Follow-up information is to be collected from all study participants, irrespective of whether 
they continue to take study treatment, usually at routine Follow-up clinic visits, unless they 
withdraw consent (see Section 3.6.5). If, however, a participant becomes unwilling or unable 
to attend study clinic visits then LCC staff will telephone the participant (or, where 
appropriate, their relative or carer) at the time of each of their scheduled Follow-up 
appointments and complete the necessary Follow-up form on the study computer-based 
system. If monitoring of blood is no longer possible (e.g. because the participant no longer 
attends clinic visits and no other means of measuring creatinine/liver function can be 
arranged), then the participant will be asked to discontinue all study treatment and advised 
to see a local doctor. All efforts will be made to continue to follow-up such participants (as 
described above), and those being followed by telephone or other remote method will be 
encouraged to provide blood samples for central analysis at relevant time points. If this is 
not possible, then LCC or RCC staff will attempt to check a participant’s progress by 
interview or direct correspondence with the participant’s own local doctors or (where 
appropriate consent and approvals are in place) by reviewing available information on 
routine healthcare systems (including local blood result systems) and registries. (In the UK, 
for example, there are registries for treated ESKD, hospital admissions, cancers, and 
deaths.) Such information could also be used for long-term follow-up, alongside participant 
questionnaires administered by telephone, mail or electronically.  
 
3.5.5 Monitoring of women of child bearing potential 
Animal studies show that empagliflozin crosses the placenta during late gestation to a very 
limited extent, but it is considered preferable to avoid its use during pregnancy. WOCBP will 
therefore have to agree to use highly effective methods of contraception during the trial. At 
each visit, a pregnancy test will be offered if, after questioning about recent menses and 
regularity of menstrual cycle, pregnancy is considered reasonably possible (or if a 
pregnancy test is required by local regulation). LCC clinic staff will also reinforce the need 
for highly effective contraception at each visit. If a participant becomes pregnant during the 
trial, the trial medication will be stopped and the participant will be followed up until birth or 
termination of the pregnancy (see further details for reporting of pregnancy in Section 
2.5.1.1). 
 
3.5.6 Monitoring of people with diabetes mellitus 
LCC clinic staff will receive training on the specific risk of ketoacidosis (which can present 
with lower than anticipated blood glucose levels in people with diabetes treated with SGLT-
2 inhibitors) and will be asked to provide additional written information about ketoacidosis to 
participants with diabetes (e.g. a trial information card). Testing equipment and materials to 
detect blood ketones will be available to people with type 1 diabetes before Randomization. 
 


 
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3.5.7 Local Lead Investigator supervision 
LLI will meet regularly with the other LCC staff to review study progress, the delegation of 
duties log and approve listings of reported adverse events. The RCC or 
 will be 
contacted if adverse event information needs to be refined. 
  
3.6 CENTRAL MONITORING OF PARTICIPANT SAFETY, EARLY RECALL VISITS AND MODIFYING 
STUDY TREATMENT 
 
3.6.1 Early Recall Visits 
An Early Recall visit may be arranged for any participant who requires review outside their 
planned visit schedule. Examples of circumstances where this may be necessary include 
the assessment of abnormal values in safety blood results from routine Follow-up visits, or 
if symptoms of liver disease (e.g. icterus) develop between scheduled Follow-up visits, or 
an extra visit is required a few weeks after the Randomization Visit (e.g. if requested by local 
regulators or Local Investigator). As at routine study visits, the results of blood tests 
performed at Early Recall visits will be entered by LCC clinic staff into the study computer-
based system (which is designed to prompt appropriate actions) and these results will be 
monitored centrally by clinical staff at the 
and RCCs in accordance with the study 
procedures.  
 
3.6.2 Monitoring liver function, potassium, creatinine and AESIs 
 study clinicians will be responsible for reviewing local results on liver function, 
potassium and creatinine, and all reports of AESIs. They will advise on the need for (and 
timing of) Early Recall visits and whether study treatment should be stopped or restarted. In 
so doing, 
study clinicians will collaborate with the LLI and other LCC clinic staff (or 
RCC in certain regions), as necessary, and will generally initiate contact if there have been 
results that fulfil the definition of liver injury or a 50% increase in creatinine since the 
preceding Follow-up visit. Management strategies include ascertainment of a more detailed 
clinical picture, additional investigations, more frequent study visits, or a lower threshold for 
stopping study treatment. 
 
3.6.3 Modifying study treatment 
If adverse events occur that are believed to be due to empagliflozin, including significant 
elevation of liver transaminases, the study treatments may be temporarily or permanently 
discontinued. The following events are also sufficient reason to discontinue the study 
empagliflozin or placebo: 
 
 SAE considered likely to be due to the study treatment (i.e. SSAR, see Section 
2.5.1.3) 
 Kidney transplantation 
 New reason to prescribe empagliflozin or another SGLT-2 or SGLT-1/2 inhibitor (e.g. 
a local doctor of the opinion that it should be included as part of the current standard 
of care for prevention of cardiovascular events); or new reason not to use an SGLT-
2 inhibitor (e.g. local doctors may choose to stop study treatment on initiation of 
maintenance dialysis or after ketoacidosis) 
 Pregnancy or suspected pregnancy 
 At the request of the participant or their doctors (for whatever reason) or any other 
situation where continuing study treatment is not considered to be in the participant’s 
best interests by their own doctors or the study clinical team (including cessation of 
use of reliable contraception in WOCBP or use of high potency immunosuppression). 


 
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Whenever possible, the study computer-based system will prompt LCC clinic staff to 
consider whether there are specific reasons to discontinue or to restart study treatment (if 
appropriate, i.e. if reasons for discontinuation do not exist any longer). 
 study clinicians 
will provide advice if required. 
 
3.6.4 Unblinding of study treatment 
There are two main situations in which unblinding of the treatment allocation (empagliflozin 
or placebo) for an individual participant may be warranted: 
 
 When knowledge of the treatment allocation could materially influence the immediate 
medical management (e.g. after overdose) 
 When unblinding is necessary as part of Safety Reporting (see Section 2.5.1.4). 
 
Urgent unblinding is available by contacting a 
 study clinician on a 24-hour basis via 
the 
 Freefone telephone service. For the avoidance of doubt, if an investigator or local 
doctor requests the unblinded treatment allocation, it will be provided. All unblinding 
episodes are logged within the study computer-based system. 
 
3.6.5 Withdrawal of consent 
Participants may decide that they no longer wish to take study treatment or are no longer 
willing to attend study visits. LCCs may be able to help participants overcome problems 
associated with personal circumstances (e.g. provide transport support to attend clinics). 
These decisions are not considered to be withdrawals of consent, and appropriate 
procedures for dealing with them are described elsewhere in this protocol (e.g. for 
discontinuation of study treatment see Section 3.6.3 and for alternative methods of follow-
up see Section 3.5.4). However, participants are free to withdraw consent for some or all 
aspects of the study at any time. In order to ensure that relevant safeguards are put in place 
to maintain the individual’s safety (e.g. if an important safety issue comes to light that might 
affect a participant who has previously withdrawn from the study) and to prevent a breach 
of the individual’s decision to withdraw (e.g. to prevent re-invitation of an individual who had 
previously withdrawn consent), the decision to withdraw should ideally be put in writing and 
a copy maintained at the LCC (with key data items being recorded on the study computer-
based system). This written information should specify which aspect(s) of the study consent 
is being withdrawn: for example, direct contact from study staff; collection of information from 
a relative or friend; collection of information from local doctors or routine data sources; or 
the storage and analysis of samples for protocol-specified future unspecified assays. (In 
accordance with regulatory guidance, data that have already been collected and 
incorporated into the study database, including the results of laboratory assays, will continue 
to be processed.) 
 
3.7 CONFIRMATION AND VERIFICATION OF STUDY OUTCOMES (“ADJUDICATION”)  
 
Outcomes (and components) purely based on laboratory values (e.g. sustained ≥40% 
decline in eGFR,) will not be adjudicated and analyses will emphasize the results of 
measurements made at central laboratories. Wherever possible, eGFR will be calculated 
using centrally measured serum creatinine (with local results substituted if central results 
are unavailable). eGFR will be calculated using the CKD-EPI creatinine formula.40 
 
Receipt of a kidney transplant or initiation of maintenance dialysis will also not be 
adjudicated. Instead, LCC reports will be cross-checked by the 
 with information at 


 
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subsequent follow-up visits or (where available) with additional medical information collected 
for adjudication of deaths.  
 
Additional medical information will be sought for AEs that undergo adjudication. In general, 
these will be limited to all deaths and events initially reported as hospitalization for heart 
failure, myocardial infarction, stroke, liver injury, ketoacidosis, lower limb amputation and 
acute kidney injury. Other events may be added to the adjudication list if considered 
necessary to ensure a reliable assessment of the clinical effects (and particularly safety) of 
empagliflozin. Most hospitalizations will not be adjudicated and so analyses of 
hospitalizations will mainly be based on LCC reports. 
 
Relevant information needed for adjudication may come from the records held at the LCCs 
and other hospitals, from participant’s own doctors, or from electronic sources and registries. 
In some cases it may be necessary to obtain information that predates randomization into 
the study. A central panel of clinicians based at, or overseen by, the 
 will provide the 
adjudication. Review, processing and adjudication of AEs will be conducted in accordance 
with the study SOPs and will be blinded to study treatment allocation (empagliflozin or 
placebo). The relevant SOP will detail a quality control process where the first events 
adjudicated by each adjudicator and a random subsample thereafter (about 5%) will be 
reviewed by a second adjudicator (blind to original adjudication). 
 
3.8 
CITED REFERENCES 
 
1. 
Levey AS, Coresh J. Chronic kidney disease. Lancet 2012; 379(9811): 165-80. 
2. 
Stevens PE, O'Donoghue DJ, de Lusignan S, et al. Chronic kidney disease 
management in the United Kingdom: NEOERICA project results. Kidney Int 2007; 72(1): 92-
9. 
3. 
Matsushita K, van der Velde M, Astor BC, et al. Association of estimated glomerular 
filtration rate and albuminuria with all-cause and cardiovascular mortality in general 
population cohorts: a collaborative meta-analysis. Lancet 2010; 375(9731): 2073-81. 
4. 
Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and 
the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004; 351(13): 
1296-305. 
5. 
Cholesterol Treatment Trialists Collaboration. Impact of renal function on the effects 
of LDL cholesterol lowering with statin-based regimens: a meta-analysis of individual 
participant data from 28 randomised trials. The lancet Diabetes & endocrinology 2016; 4(10): 
829-39. 
6. 
Ninomiya T, Perkovic V, Turnbull F, et al. Blood pressure lowering and major 
cardiovascular events in people with and without chronic kidney disease: meta-analysis of 
randomised controlled trials. BMJ 2013; 347: f5680. 
7. 
Park M, Hsu CY, Li Y, et al. Associations between kidney function and subclinical 
cardiac abnormalities in CKD. J Am Soc Nephrol 2012; 23(10): 1725-34. 
8. 
Foley RN, Parfrey PS, Kent GM, Harnett JD, Murray DC, Barre PE. Long-term 
evolution of cardiomyopathy in dialysis patients. Kidney Int 1998; 54(5): 1720-5. 
9. 
Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, Cardiovascular Outcomes, and 
Mortality in Type 2 Diabetes. N Engl J Med 2015; 373(22): 2117-28. 


 
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10. 
Fox CS, Matsushita K, Woodward M, et al. Associations of kidney disease measures 
with mortality and end-stage renal disease in individuals with and without diabetes: a meta-
analysis. Lancet 2012; 380(9854): 1662-73. 
11. 
Jafar TH, Schmid CH, Landa M, et al. Angiotensin-converting enzyme inhibitors and 
progression of nondiabetic renal disease. A meta-analysis of patient-level data. Ann Intern 
Med 2001; 135(2): 73-87. 
12. 
Lewis EJ, Hunsicker LG, Clarke WR, et al. Renoprotective effect of the angiotensin-
receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl 
J Med 2001; 345(12): 851-60. 
13. 
Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and 
cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 
2001; 345(12): 861-9. 
14. 
Fried LF, Emanuele N, Zhang JH, et al. Combined angiotensin inhibition for the 
treatment of diabetic nephropathy. N Engl J Med 2013; 369(20): 1892-903. 
15. 
Wanner C, Inzucchi SE, Lachin JM, et al. Empagliflozin and Progression of Kidney 
Disease in Type 2 Diabetes. N Engl J Med 2016; 375(4): 323-34. 
16. 
Schnaper HW. Remnant nephron physiology and the progression of chronic kidney 
disease. Pediatric nephrology 2014; 29(2): 193-202. 
17. 
Ruggenenti P, Porrini EL, Gaspari F, et al. Glomerular hyperfiltration and renal 
disease progression in type 2 diabetes. Diabetes Care 2012; 35(10): 2061-8. 
18. 
Tonneijck L, Muskiet MH, Smits MM, et al. Glomerular Hyperfiltration in Diabetes: 
Mechanisms, Clinical Significance, and Treatment. J Am Soc Nephrol 2017; 28(4): 1023-
39. 
19. 
Haynes R, Staplin N, Emberson J, et al. Evaluating the contribution of the cause of 
kidney disease to prognosis in CKD: results from the Study of Heart and Renal Protection 
(SHARP). Am J Kidney Dis 2014; 64(1): 40-8. 
20. 
Jha V, Garcia-Garcia G, Iseki K, et al. Chronic kidney disease: global dimension and 
perspectives. Lancet 2013; 382(9888): 260-72. 
21. 
USRDS. International Comparison. 2014 Annual Data Report: Atlas of End-Stage 
Renal Disease in the United States. , National Institutes of Health, National Institute of 
Diabetes and Digestive and Kidney Diseases, Bethesda, MD. 2014; 2. 
22. 
Ridderstrale M, Andersen KR, Zeller C, et al. Comparison of empagliflozin and 
glimepiride as add-on to metformin in patients with type 2 diabetes: a 104-week randomised, 
active-controlled, double-blind, phase 3 trial. The lancet Diabetes & endocrinology 2014; 
2(9): 691-700. 
23. 
Haring HU, Merker L, Seewaldt-Becker E, et al. Empagliflozin as add-on to metformin 
in patients with type 2 diabetes: a 24-week, randomized, double-blind, placebo-controlled 
trial. Diabetes Care 2014; 37(6): 1650-9. 


 
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24. 
Haring HU, Merker L, Seewaldt-Becker E, et al. Empagliflozin as add-on to metformin 
plus sulfonylurea in patients with type 2 diabetes: a 24-week, randomized, double-blind, 
placebo-controlled trial. Diabetes Care 2013; 36(11): 3396-404. 
25. 
Kovacs CS, Seshiah V, Swallow R, et al. Empagliflozin improves glycaemic and 
weight control as add-on therapy to pioglitazone or pioglitazone plus metformin in patients 
with type 2 diabetes: a 24-week, randomized, placebo-controlled trial. Diabetes Obes Metab 
2014; 16(2): 147-58. 
26. 
Roden M, Weng J, Eilbracht J, et al. Empagliflozin monotherapy with sitagliptin as an 
active comparator in patients with type 2 diabetes: a randomised, double-blind, placebo-
controlled, phase 3 trial. The lancet Diabetes & endocrinology 2013; 1(3): 208-19. 
27. 
Rosenstock J, Jelaska A, Frappin G, et al. Improved glucose control with weight loss, 
lower insulin doses, and no increased hypoglycemia with empagliflozin added to titrated 
multiple daily injections of insulin in obese inadequately controlled type 2 diabetes. Diabetes 
care 2014; 37(7): 1815-23. 
28. 
Rosenstock J, Jelaska A, Zeller C, et al. Impact of empagliflozin added on to basal 
insulin in type 2 diabetes inadequately controlled on basal insulin: a 78-week randomized, 
double-blind, placebo-controlled trial. Diabetes Obes Metab 2015; 17(10): 936-48. 
29. 
Tikkanen I, Narko K, Zeller C, et al. Empagliflozin reduces blood pressure in patients 
with type 2 diabetes and hypertension. Diabetes Care 2015; 38(3): 420-8. 
30. 
Barnett AH, Mithal A, Manassie J, et al. Efficacy and safety of empagliflozin added to 
existing antidiabetes treatment in patients with type 2 diabetes and chronic kidney disease: 
a randomised, double-blind, placebo-controlled trial. The lancet Diabetes & endocrinology 
2014; 2(5): 369-84. 
31. 
Kohler S, Zeller C, Iliev H, Kaspers S. Safety and Tolerability of Empagliflozin in 
Patients with Type 2 Diabetes: Pooled Analysis of Phase I-III Clinical Trials. Advances in 
therapy 2017; 34(7): 1707-26. 
32. 
Neal B, Perkovic V, Mahaffey KW, et al. Canagliflozin and Cardiovascular and Renal 
Events in Type 2 Diabetes. N Engl J Med 2017; 377(7): 644-57. 
33. 
Pocock SJ, Simon R. Sequential treatment assignment with balancing for prognostic 
factors in the controlled clinical trial. Biometrics 1975; 31(1): 103-15. 
34. 
Peto R, Pike MC, Armitage P, et al. Design and analysis of randomized clinical trials 
requiring prolonged observation of each patient. II. analysis and examples. Br J Cancer 
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35. 
U.S. Department of Health and Human Services Food and Drug Administration. 
Guidance for Industry Determining the Extent of Safety Data Collection Needed in Late 
Stage Premarket and Postapproval Clinical Investigations. 2015. 
36. 
U.S. Department of Health and Human Services Food and Drug Administration. 
Guidance for Industry. Safety Assessment for IND Reporting. Dec 2015. 
37. 
ICH Harmonised tripartite guideline  Clinical safety data management: definitions and 
standards for expedited reporting E2A. Oct 1994. 


 
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38. 
Risk proportionate approaches in clinical trials. Recommendations of the expert 
group on clinical trials for the implementation of Regulation (EU) No 536/2014 on clinical 
trials on medicinal products for human use. Apr 2017. 
39. 
Meeker-O'Connell A, Glessner C, Behm M, et al. Enhancing clinical evidence by 
proactively building quality into clinical trials. Clinical trials 2016; 13(4): 439-44. 
40. 
Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular 
filtration rate. Ann Intern Med 2009; 150(9): 604-12. 


 
 
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4.1 APPENDIX 1: ORGANISATIONAL STRUCTURE AND RESPONSIBILITIES FOR STUDY DESIGN AND 
CONDUCT 
 
Boehringer Ingelheim 
Boehringer Ingelheim has delegated certain responsibilities to the independent Principal 
Investigators and 
 at the University of Oxford, and to the Steering Committee. 
Boehringer Ingelheim remains fully responsible for: 
 
 Provision of study funding 
 Provision and distribution (but not allocation) of manufactured and labelled study drug 
 Regulatory submissions and interactions (with support from the Principal 
Investigators) 
 Auditing of investigational sites, facilities, study setup, study processes, etc. as per 
the Audit Plan. 
 
Responsibility for oversight of the quality and integrity of the trial data remains with 
Boehringer Ingelheim. 
 
Principal Investigators 
The Principal Investigators have overall responsibility for: 
 
 Design of the study (in collaboration with Boehringer Ingelheim) 
 Preparation of the Protocol and subsequent revisions 
 Managing the 
  
 Development of computer-based systems and study SOPs.  
 
Steering Committee 
The Steering Committee is responsible for: 
 
 Agreeing the Data Analysis Plans  
 Reviewing progress of the study and, if necessary, suggesting and agreeing changes 
to the Protocol 
 Reviewing new scientific evidence that may be of relevance 
 Drafting, review and approval of study main publication(s) 
 Review and approval of proposals for subsequent analyses and publications 
 Approval of substudy proposals  
 Reviewing study quality and risk management approaches, and ensuring that the 
focus is always on issues that have (or the potential to have) a substantial impact on 
the safety of the study participants or the reliability of the study results 
 Monitoring participant characteristics and limiting recruitment of particular categories 
of participant when sufficient numbers have already entered the trial. 
 
Data Monitoring Committee 
The independent Data Monitoring Committee is responsible for: 
 
 Reviewing unblinded interim data according to the schedule outlined in the Protocol 
 Advising the Steering Committee if, in their view, the randomized data provide 
evidence that may warrant early termination of all or part of the study for either 
efficacy or safety 


 
Page 38 of 42 
EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
EuDRACT: 2017-002971-24 
 Review of the formal interim analyses (see Section 2.5.2.2). 
 
Central Coordinating Office 
The 
 is responsible for the overall coordination of the Study, including: 
 
 Study planning and organisation of Steering Committee meetings 
 Agreement of each regional recruitment plan (including countries, number of LCCs, 
number of participants, and timelines) 
 Contractual issues with RCCs and budget administration 
 Co-ordination of Ethics Committee applications 
 Supporting Boehringer Ingelheim in their interactions with regulatory authorities and 
other outside agencies as appropriate 
 Design, implementation and maintenance of computer-based systems for the study 
(including 
/RCC computer-based system for administration and study computer-
based system for direct data entry) 
 Provision of study materials to RCCs and LCCs, and provision of IT support to RCCs 
 Monitoring of drug supply in liaison with Boehringer Ingelheim (who will be 
responsible for drug distribution to each LCC) 
 Central laboratory assay and long-term storage of blood and urine samples 
 Monitoring of overall progress of the study, with a focus on critical-to-quality factors 
 Clinical safety monitoring, including reporting of SSARs to the Chair of the Data 
Monitoring Committee and to Boehringer Ingelheim 
 Responding to technical, medical, data and administrative queries from the RCCs 
 Manage data queries and data changes (with a clear audit trail) 
 Management of outcome adjudication 
 Liaison with the Data Monitoring Committee. 
 
Regional Coordinating Centres 
Each RCC is responsible, under the direction of its Regional Coordinator, for: 
 
 Identification of potential LCCs and agreement of their recruitment plans (including 
number of participants and timelines) 
 Contractual issues with LCCs and regional budget administration 
 Obtaining any central Ethics Committee approval (where appropriate) and assisting 
LCCs with local Ethics Committee applications  
 Training of LCC staff and assistants 
 Distribution of study materials to LCCs 
 Responding to technical, medical and administrative queries from the LCCs 
 Perform LCC on-site monitoring visits by trained study monitors 
 “Process” monitoring of LCCs by responding to regular or occasional reports on 
regional progress prepared by the 
 
 Ensuring appropriate follow-up of abnormal safety blood results 
 Collection and initial processing of relevant documentation to confirm reported events 
in line with study SOPs  
 Collection and short-term storage of blood and urine samples from LCCs, and 
subsequent transport of them to the 
  
 Organisation of meetings of collaborators within the region 
 Entering data entry errors reported by LCCs 
 Supporting Boehringer Ingelheim in their interactions with regulatory authorities as 
appropriate 


 
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EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
EuDRACT: 2017-002971-24 
 Ensuring that trial-related activities are performed according to local regulations. 
 
Local Clinical Centres 
The LCC lead investigator and LCC staff are responsible for: 
 
 Meeting regularly as a team to review study progress locally, the delegation of duties 
log and for Local Investigators to review and approve listings of locally reported 
adverse events (i.e. provide LLI oversight) 
 Obtaining local Ethics Committee approval were necessary (aided by the RCC) 
 Obtaining local management approval where necessary 
 Performing trial-related activities according to local regulations 
 Provision of adequate clinic space and access to appropriate systems for the 
identification of potentially eligible individuals 
 Conducting clinic procedures: managing and distributing study drugs (in conjunction, 
if required, with the hospital pharmacy), and maintaining relevant study equipment in 
accordance with the Protocol and SOPs 
 Ensuring adequate local laboratory facilities for safety monitoring and, if necessary, 
processing and temporarily storing samples for central analysis 
 Reviewing Screening Form data, confirm appropriate dose of RAS-inhibition (where 
relevant), confirm no reasons to prescribe or not prescribe empagliflozin (or other 
SGLT-2 or SGLT-1/-2 inhibitor), and approving participants for randomization (Local 
Investigators only) 
 Providing individualized care, including management of cardiovascular risk factors 
and other existing comorbidities (e.g. hypertension, diabetes) according to relevant 
guidelines 
 Dealing with routine enquiries from participants and their families in collaboration with 
the RCC where necessary 
 Obtaining clinical information when requested to confirm potential primary and 
secondary, tertiary and safety study outcomes 
 Informing the RCC or 
 of any possible data entry errors. 
 


 
 
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EMPAKIDNEY1.4 2018-04-25 
 
 
 
 
 
 
 
 
 
 
 
 
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4.2 APPENDIX 2: VISIT SCHEDULE AND PROCEDURES 
4.2.1 Clinic procedures 
 
 
Task
Activity
Registration
Screening
Randomization
- 12 to -8 weeks
0 months
2 months
6 months
6 monthly visits
Final visit**
Demographics
Record contact details
X
check
check
check
check
check
check
Relevant medical history (incl. inclusion criteria & an dose of RAS inhibitor)
X
X
Exclusion criteria (incl. relevant non-study medication)
X
X
Other information (smoking, alcohol)
X
Use of non-study medication
X
X
X
X
X
X
Consent
Obtain consent
X
Confirm consent
X
Safety & outcomes reporting
Adverse events (incl. Suspected Serious Adverse Reactions)
X
X
X
X
X
Self-reported compliance
X
X
X
X
X
Reasons for stopping study treatment (incl. SAEs, non-serious adverse events, other reasons)
X
X
X
X
X
Remote follow-up using routine data sources and/or participant surveys*
(X)*
(X)*
(X)*
(X)*
Quality of life (by EQ5D-5L)
X
18 month only
X
Physical measurements
Blood pressure
X
X
X
X
X
X
Height
X
Weight
X
X
X
X
X
Hip & waist circumference
X
18 month only
X
Local laboratory assessments
Creatinine and liver function tests (transaminases and bilirubin)
X
X
X
X
X
X**
Potassium
X
X
X
X
X
Haematocrit, haemoglobin
X (all)
18 month only (in about a 20% subset)
Sodium, corrected calcium, phosphate (in about a 20% subset)
18 month only
Urinary albumin and creatinine
X
Pregnancy test***
X
X
X
X
X
X
Central sample collection
Blood samples for central analysis of creatinine & storage****
X
X
X
X
X
Urine for central analysis of albumin & creatinine, and storage
X
X
18 month only
X
Issue placebo
X
Randomize eligible & willing participants
X
Issue randomized treatment (empagliflozin 10 mg or placebo; 210 day supply)
X
X
X
Retrieve unused treatment
X
X
X
X
Create appointment
X
X
X
X
X
X
Provide advice
X
X
X
X
X
X
*** If pregnancy reasonably possible as indicated by participant's history (or if required by local regulation)
In-trial follow-up
* Remote follow-up may be used for some participants who are unwilling or unable to attend study visits, and for all surviving participants for several years after the final visit; ** Additional local blood creatinine 
**** NT-pro BNP measured at 0 months and HbA1c measured at 0, 2, 18 months and final visit.
and urine albumin:creatinine ratio measurement 4 weeks after final follow-up (~20% subset). Final follow-up timing is determined by the Steering Committee in response to numbers of events & DMC recommendations.
Medical history & eligibility 
 assessment
Randomization & study treatment
 handling
Appointment management 
& advice
 




 
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EMPAKIDNEY2.0 2020-01-13 
 
 
 
 
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5.1 VERSION HISTORY 
 
EDMS #5434 
 
Version 
Version date 
Summary 
1.0 
8th January 2018 
Version 1.0 finalized 
1.1 
8th January 2018 
Footnote update 
1.2 
25th January 2018 
Formal interim analysis update 
1.3 
26th March 2018 
Update following MHRA review 
1.4 
25th April 2018 
Update following FDA review of formal interim analysis 
2.0 
13th January 2020 
Recruitment target increase to 6000 participants;  
exclusion of further participation from people with type 1 
diabetes after introduction of a cap; clarification on the 
subdivisions of cardiovascular death; reducing tertiary 
subgroup analyses solely to the primary outcome and 
highlighting the subgroups of key interest; section 3.1.2 
exclusion criterion (ix) modified; substituting local 
creatinine results when central creatinine results are 
missing; and clarification in table 4.2.1 that Hb/Hct is 
measured in all participants at randomization (to be 
consistent with the protocol text in section 3.4.1.1) 
 
 
 

SAP_001.pdf: 
 
TRIAL STATISTICAL ANALYSIS PLAN
c31460805-04
BI Trial No.:
1245.137
Title:
EMPA-KIDNEY: A multicentre international randomized parallel 
group double-blind placebo-controlled clinical trial of 
EMPAgliflozin once daily to assess cardio-renal outcomes in 
patients with chronic KIDNEY disease
Including Protocol Amendment 1 <1245.137>-protocol-version-
02 [c31394601] 
Investigational
Product:
Empagliflozin, BI 10773
Responsible trial 
statistician:
Phone: 
Date of statistical 
analysis plan:
15 JUL 2022 SIGNED
Version:
4
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! 2022 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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LIST OF TABLES
Table 6.1: 1
Endpoint REP period for assigning to on-treatment period .............................15
Table 6.7: 1
Time windows for post-baseline follow-up visits ............................................21
Table 10: 1
History table .....................................................................................................51


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2.
LIST OF ABBREVIATIONS
Term
Definition / description
AE
Adverse Event
AESI
Adverse Event of Special Interest
ALT
Alanine aminotransferase
ANCOVA
Analysis of Covariance
AST
Aspartate aminotransferase
BI
Boehringer Ingelheim
BIcMQ
Boehringer Ingelheim customised MedDRA Query
BMI
Body Mass Index
CKD-EPI
Chronic Kidney Disease Epidemiology Collaboration
COVID-19
Coronavirus Disease 2019
CTP
Clinical Trial Protocol
CTR
Clinical Trial Report
CV
Cardiovascular
DBP
Diastolic Blood Pressure
DKA
Diabetic ketoacidosis
DM
Diabetes Mellitus
DMC
Data Monitoring Committee
eGFR
estimated Glomerular Filtration Rate
EMA
European Medicines Agency
EoT
End-of-Text
ESKD
End Stage Kidney Disease
HbA1c
Haemoglobin A1c
HHF
Hospitalisation for Heart Failure
HLGT
High Level Group Term
HLT
High Level Term
HR
Hazard Ratio
ICH
International Conference on Harmonisation
iPD
Important Protocol Deviation
ITT
Intention-to-treat
KDIGO
Kidney Disease Improving Global Outcomes
KM
Kaplan-Meier


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Term
Definition / description
Max
Maximum
MedDRA
Medical Dictionary for Regulatory Activities
MI
Myocardial Infarction
Min
Minimum
MMRM
Mixed Model Repeated Measures
NT-proBNP
N-terminal pro B-type natriuretic peptide
OC-AD
Observed Case-All Data
OC-OT
Observed Case-On Treatment
PT
Preferred Term
Q1
Lower quartile
Q3
Upper quartile
RAS
Renin-angiotensin System
REP
Residual Effect Period
RS
Randomised Set
RS&I
Random Slope and Intercept
SAE
Serious Adverse Event
SAS
Statistical Analysis System
SBP
Systolic Blood Pressure
SCR
Screened Set
SD
Standard Deviation
SI
International System of Units
SMQ
Standardised MedDRA Query
SOC
System Organ Class
SOP
Standard Operating Procedure
TS
Treated Set
UACR
Urine Albumin Creatinine Ratio
UK
United Kingdom
UTI
Urinary Tract Infection


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3.
INTRODUCTION
As per the International Conference on Harmonisation (ICH) E9 guidance (1), the purpose of 
this document is to provide a more technical and detailed elaboration of the principal features 
of the analysis described in the protocol, and to include detailed procedures for executing the 
statistical analysis of the primary and secondary variables and other data.
This regulatory TSAP predefines the statistical approaches to be used for regulatory authority 
submissions. It assumes familiarity with the Clinical Trial Protocol (CTP), including Protocol 
Amendments. In particular, the TSAP is based on the planned analysis specification as written 
in CTP Sections 2.3 “Data Analysis Plan” and 2.4 “Sample Size and Predicted Number of 
Events”. Therefore, TSAP readers may consult the CTP for more background information on 
the study, e.g., on study objectives, study design and population, treatments, definition of 
measurements and variables, planning of sample size, randomisation.
Note, an earlier publication Data Analysis Plan (Standard Operating Procedure [SOP] 11) (2)
was agreed by the Steering Committee for the trial, detailing the pre-specified analyses for 
presentation in the primary publication(s). Therefore, this regulatory TSAP replicates all the 
analyses from the primary publication(s) as pre-specified in SOP11 and, in addition, specifies 
a series of additional exploratory analyses/summaries to aid future potential regulatory 
submissions. The analyses common to both SOP11 and this regulatory TSAP are highlighted
for ease of review.
SAS® Version 9.4 or a later version will be used for most analyses. R Version 4.0.1 (3) or a 
later version will be used where required.


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4.
CHANGES IN THE PLANNED ANALYSIS OF THE STUDY
There are no changes in this TSAP compared to the statistical methods described in the CTP. 
The following clarifications and additions have been made:
∀
In February 2022 an error in the minimization process was discovered, indicating that 
minimization by region had not been performed correctly from late 2019. For this 
reason, the actual region patients were randomised from will be used in the main 
analysis models rather than the region from the minimization process. All other factors
[age, sex, diabetes status, screening estimated glomerular filtration rate (eGFR) and 
screening urine albumin creatinine ratio (UACR)] will be fitted as planned from the 
minimization process. Note this change was made and documented prior to the Data 
Monitoring Committee (DMC) interim analysis.
∀
Standard Boehringer Ingelheim (BI) analyses of routine safety data have been 
included. Refer to Sections 7.8.1.2 and 7.8.2.2.
∀
Where considered appropriate, the potential impact of Coronavirus Disease 2019 
(COVID-19) on the trial will be assessed by producing additional summaries of 
disposition, treatment compliance, efficacy, and adverse events (AEs). The start date 
for COVID-19 having an impact on the trial will be taken as the date of a 
discontinuation of the trial medication due to COVID-19, a COVID-19 related AE or 
the COVID-19 related global BI recruitment hold (17 MAR 2020), whatever comes 
first.
∀
Circumstances for delaying or cancelling the planned interim analysis are described in
Section 9.2.


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5.
ENDPOINTS
Adjudication will be limited to all deaths and events initially reported as HHF, myocardial 
infarction (MI), stroke, liver injury, ketoacidosis, lower limb amputation, acute kidney injury
and serious genital infections. Endpoints (and components) based on laboratory values will 
not be adjudicated. Receipt of a kidney transplant or initiation of maintenance dialysis will 
also not be adjudicated. Most hospitalisations will not be adjudicated. Further details on the 
adjudication process refer to SOP 9b: EMPA-KIDNEY: Adjudication Procedures (4). Where 
applicable adjudication data will take precedence over investigator data, for endpoint 
derivations. References to ‘as adjudicated’ within this document includes fully assessed
events that have been confirmed by adjudication and provisionally assessed events that have 
not been refuted by adjudication. Other events that were not selected are not considered ‘as 
adjudicated’.
For endpoints that involve eGFR the Chronic Kidney Disease Epidemiology Collaboration 
(CKD-EPI) formula will be used. eGFR will be estimated from creatinine measured in the 
central laboratory. The exception being where a central measurement is expected but missing, 
the local creatinine value will be used, refer to Section 6.6 for further details.
Further details on the derivation of time to first occurrence endpoints are provided in Section 
6.8.
5.1
PRIMARY ENDPOINT
The primary endpoint is a composite of time to the first occurrence of:
∀
Kidney disease progression [defined as ESKD, a sustained decline in eGFR to <10 
mL/min/1.73m2, ‘as adjudicated’ renal death, or a sustained decline of ≥40% in eGFR 
from randomisation]; or
∀
Cardiovascular (CV) death (‘as adjudicated’).
ESKD is defined as the initiation of maintenance dialysis or receipt of a kidney transplant.
Dialysis will be considered as maintenance if it is required for ≥90 days or if the dialysis is 
stopped within 90 days for a reason of ‘received kidney transplant’, ‘dialysis is futile’ or 
‘subject refused dialysis’. Dialysis ongoing at the final follow-up visit or the last scheduled 
follow-up visit before death*, withdrawal of consent or loss to follow-up will also be 
considered as maintenance irrespective of duration. Where changes in dialysis modality are 
consecutive with one another durations will be summed for determining whether the 
maintenance duration has been met. Duration will be calculated as ‘Dialysis stop – Dialysis 
start + 1’.
* For deaths within 90 days of starting dialysis the adjudicator will consider whether the 
dialysis would have been required long-term or only temporarily, if temporary then the 
outcome of dialysis will be changed from ‘ongoing’ to ‘dialysis stopped for other reason’ and 
not considered as an ESKD event.
To meet the requirement for a ‘sustained’ decline in eGFR, this will be taken to mean that it is 
either:


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∀
Measured at two consecutive scheduled study follow-up visits (at least 30 days apart); 
or
∀
Measured at the final follow-up visit or the last scheduled follow-up visit before death, 
withdrawal of consent or loss to follow-up.
This ‘sustained’ rule will also apply to other endpoints defined below with these eGFR 
components. Further detail on defining ‘sustained’ eGFR declines is provided in Section 9.6.
5.2
SECONDARY ENDPOINTS
5.2.1
Key secondary endpoints
The key secondary endpoints are:
(i)
Time to the first occurrence of HHF (‘as adjudicated’) or CV death (‘as 
adjudicated’)
(ii)
Time to occurrences of all-cause hospitalisations (first and recurrent combined)
(iii)
Time to death from any cause (‘as adjudicated’)
5.2.2
Secondary endpoints
Other secondary endpoints are:
(i)
Time to the first occurrence of kidney disease progression
(ii)
Time to CV death (‘as adjudicated’)
(iii)
Time to first occurrence of CV death (‘as adjudicated’) or ESKD


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5.4
OTHER VARIABLES
Trial-specific safety endpoints
Along with routine safety endpoints (refer to Section 7.8) the following trial-specific safety 
endpoints are defined (AEs will be coded using the MedDRA, version 20.1). Details on the 
PTs used to group the AEs for the AE-based endpoints below will be documented prior to 
database lock and listed in the Clinical Trial Report (CTR):
(i)
Time to first occurrence of a serious adverse event (SAE) due to each of the 
following:
a.
Urinary tract infection (UTI)
b. Genital infection (‘as adjudicated’)
c.
Hyperkalaemia
d. Acute kidney injury (‘as adjudicated’)
e.
Dehydration
(ii)
Time to first occurrence of an AE of special interest (AESI), ‘as adjudicated’:
a.
Liver injury [defined as alanine aminotransferase (ALT) or aspartate 
aminotransferase (AST) ≥5 x upper limit of normal (ULN) or the combination 
of ALT or AST ≥3 x ULN with bilirubin ≥2xULN (in the same blood 
sample)], overall and separately by cause
b. Ketoacidosis
c.
Lower limb amputations, overall and by level (toe, forefoot, foot, below knee 
or above knee)
(iii)
Time to first occurrence of other AEs relevant to the study question:


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a.
Bone fracture, overall and separately by site (long bones or non-long bones) 
and cause (high impact trauma, low impact trauma or other causes)
b. Severe hypoglycaemia (defined as low blood sugar causing severe cognitive 
impairment which requires assistance from another person for recovery)
c.
Symptomatic dehydration (defined as whether or not a participant has 
experienced symptoms they attribute to dehydration, such as feeling faint or 
fainting)
(iv)
Time to first occurrence of hospitalisation by specific causes based on the primary 
MedDRA System Organ Class (SOC)
(v)
Time to first occurrence of SAEs, both overall and separately by primary SOC
(vi)
Discontinuation of study treatment, both overall and by reason for discontinuation 
(SAEs [overall and by primary SOC], non-serious AEs [overall and by primary 
SOC] and all other reasons including those lost to follow-up)
(vii)
Weight, systolic (SBP) and diastolic blood pressure (DBP) values at each 
scheduled visit during the follow-up period
(viii)
Local laboratory measures of potassium at each scheduled visit during the follow-
up period
(ix)
Elevations in local laboratory measures of ALT and AST as defined by the 
categories of a) ALT or AST ≥5 x ULN b) ALT or AST ≥3xULN with bilirubin 
≥2xULN (in the same blood sample)
(x)
Haematocrit, haemoglobin, sodium, corrected calcium and phosphate at 18 months 
in the subset of surviving UK patients
(xi)
Time to first occurrence of an SAE by each MedDRA HLGT (on the path to the
primary SOC), exploratory endpoint
Extent of exposure
Treatment exposure (days) will be calculated as Date of last administration of trial 
medication – Date of randomisation + 1, note date of first administration of trial medication 
is not specifically collected but assumed to be the date of randomisation. Treatment exposure 
will include time when treatment is temporarily discontinued and subsequently reintroduced.
Observational period (days) will be calculated as Date of final follow-up – Date of 
randomisation + 1. The date of the final follow-up will be the date of the final follow-up visit
if it was a direct visit or the date last known to be alive if it was an indirect visit or the date of 
death if the patient died prior to or on the day of the final follow-up visit.


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6.
GENERAL ANALYSIS DEFINITIONS
6.1
TREATMENTS
All summaries and analyses will assign patients to the treatment group that they were 
randomised to. The study has the following periods of interest:
∀
Screening/run-in period: from the day of informed consent to the day prior to 
randomisation
∀
Follow-up period: from the day of randomisation to the day of the final follow-up 
visit, split into the following:
o
On-treatment period: from the day of randomisation (note start date of study 
treatment is not specifically recorded, but assumed to be the randomisation 
date, as per protocol) to the day of permanently discontinuing study treatment 
+ a residual effect period (REP), refer to Table 6.1: 1 below
o
Post-treatment period: from the day after the on-treatment period to the day of 
the final follow-up visit (for patients continuing on study treatment up to their
final follow-up visit, no post-treatment period will exist)
∀
Post final follow-up period: from the day after the final follow-up visit to trial 
completion
There are two main data collection periods of interest for the efficacy and safety analyses:
Observed case including data after premature treatment discontinuation (OC-AD)
All data collected during the follow-up period (as defined above) will be considered. Later 
references during this document to the ‘last/final scheduled follow-up visit’ are within this 
period only. Unless stated otherwise data collected after the final follow-up visit will not be 
considered. Thus, following an intention-to-treat (ITT) analysis approach.
Observed case on-treatment (OC-OT)
Only data whilst a patient is on-treatment will be considered. The on-treatment period will 
include temporary off-treatment periods. The length of the REP depends upon the type of data 
being analysed and unless stated otherwise will be as detailed in Table 6.1: 1. Note it is 
possible for patients who permanently discontinue study treatment on or shortly prior to the 
day of the final follow-up visit to have a REP that would extend beyond the day of the final 
follow-up visit. In this instance for all trial-specific endpoints defined in Section 5, the REP 
will be truncated to ensure that the on-treatment period cannot extend beyond the day of the 
final follow-up visit. Whereas for the standard analyses of safety, described in Sections 
7.8.1.2 and 7.8.2.2, the REP will be allowed to extend beyond the day of the final follow-up 
visit, where applicable.


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Table 6.1: 1
Endpoint REP period for assigning to on-treatment period
Endpoint
Residual Effect Period
(days after study treatment stop date)
eGFR and serum creatinine
HbA1c
Weight, BPs
Hip and waist circumference
EQ5D
Other laboratory parameters
AEs
1
7
1
7
7
3
7
6.2
IMPORTANT PROTOCOL DEVIATIONS
An important protocol deviation (iPD) is one that affects the rights or safety of the study 
patients or that can potentially influence the primary outcome measures for the respective 
patients in a way that is neither negligible nor in accordance with the study objectives.
Patients with an iPD will not be excluded from any analyses, the exception being patients not 
providing informed consent, who will be excluded from all analyses.
6.3
PATIENT SETS ANALYSED
The following patient sets are defined:
∀
Screened set (SCR)
This patient set includes all patients screened for the trial and who provided informed 
consent.
∀
Randomised set (RS):
This patient set includes all randomised patients, whether treated or not.
∀
Treated set (TS):
This patient set includes all patients who were dispensed randomised study 
medication.
Table 6.3: 1 summarises which endpoints are to be analysed for which analysis sets. RS 
analyses will use data from the OC-AD period of interest, unless specified otherwise.  TS 
analyses will use data from the OC-OT period of interest, unless stated otherwise. Further 
details are provided in Section 6.1.


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6.5
POOLING OF CENTRES
This section is not applicable because centre is not included in the statistical model.
6.6
HANDLING OF MISSING DATA AND OUTLIERS
All efforts will be made to ensure patients attend all follow-up visits including the final 
follow-up visit, irrespective of whether patients are still on study treatment or not. At each 
follow-up visit, it is the aim to ascertain all components of all applicable endpoints.
For time to event endpoints, patients who are event-free but have dropped out of the trial 
prematurely (i.e. due to death, withdrawal of consent or loss to follow-up), will be censored 
according to the rules given in Section 6.8.2.
For the analysis of other endpoints, missing data will not be imputed unless detailed below. 
Note for endpoints analysed by mixed model repeated measures (MMRM) missing data will 
be handled via the methodology of MMRMs.
Missing central laboratory eGFR values
Note this section only applies to the handling of missing central laboratory eGFR for those 
efficacy endpoints that have time to a sustained decline in eGFR to <10 mL/min/1.73m2 or 
time to a sustained decline of ≥40% in eGFR included as a component.
Table 6.7: 1 provides the expected study day for scheduled follow-up visits along with time 
windows defined for the purposes of analysis. If multiple central eGFR measurements are 
available in any one scheduled follow-up visit period, then the eGFR closest to the ideal 
follow-up day will be used to define the eGFR for that particular scheduled follow-up visit 
period.
eGFR will be estimated from creatinine measured in the central laboratory wherever possible. 
However, where a central laboratory eGFR measurement is expected but missing, the local 
blood creatinine measurement closest to the planned follow-up day within the scheduled 
follow-up visit period (if one exists) will be used to estimate the eGFR instead. Where a local 
eGFR is used, percentage change in eGFR will be calculated relative to the local 
randomisation visit value. The local eGFR measurement closest to the planned follow-up day 
of the next scheduled follow-up visit period will be used to assess the definition of a sustained
decline. Using local measurements from previous scheduled follow-up visit periods for 
defining sustained declines will not be done (unless the central measurement is also missing at 
these visits). Therefore, to meet the sustained decline criteria, measurements must be from 
consecutive scheduled follow-up visit periods (at least 30 days apart) and from the same 
source (i.e. central or local). The exception being if the decline is observed at the last 
scheduled follow-up visit, in which case consecutive measurements are not required and a 
single local measurement could be used in the absence of a central one.
If the central eGFR measurement is missing at the randomisation visit, then the local 
measurement will be used.  If both the central and local measurement are missing, then the 
latest locally measured pre-randomisation value will be used. Where a local eGFR is used, 
percentage change in eGFR will be based only on post-baseline local values.


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Further detail on the handling of missing eGFR values and the derivation of sustained 
declines is provided in Section 9.6.
A sensitivity analyses for the primary endpoint will be performed solely on central laboratory 
eGFR measurements, to assess the impact of using local data when central data is missing. A 
similar sensitivity analysis will also be performed solely on local laboratory eGFR 
measurements, for completeness.
Missing information on event dates, AE onset dates and death dates
For such dates, month and year are required so only the handling of missing days is 
considered here. In general, a worst-case approach will be adopted, whereby the date will be 
assumed to have occurred as close to the date of randomisation as possible, i.e. the day of 
randomisation for dates within the same month of randomisation, or the first of the month for 
dates after the month of randomisation.
The exception will be for day of death, whereby if from other recorded dates it is known the 
patient was alive the latest of these dates will be used instead. Note during adjudication 
patients with an AE or AEs with a fatal outcome will have one AE selected as leading to the 
cause of death. The end date for this AE will be used to record the date of death and will be 
used for all applicable analyses/summaries.
In the unlikely event of the month and/or year also not being available dates will be imputed 
on a case-by-case basis and documented prior to breaking the blind.
Missing information on hospital discharge dates
This imputation is only required for the analysis of all-cause recurrent hospitalisations, when 
information on hospital duration is not provided and the corresponding AE end date (used as 
the hospital discharge date) is either partial or missing.
For these cases, if the day is missing then it will be assumed as the day that leads to the 
shortest hospital stay, i.e. the 1st of the month or the day of AE onset if the AE onset month is
the same as the AE end month. If day and month are missing and AE onset/end dates are in 
the same year then the discharge date will be assumed as the day of AE onset, otherwise if in 
different years the 1st January will be used. If the AE end date is completely missing, then the 
discharge date will be assumed as the day of AE onset.
Missing information on the treatment stop date
If only month and year are present then the day will be assumed as the last day of the month, 
unless there is evidence of an earlier date of death, in which case the date of death will be 
used.
In the unlikely event of the month and/or year also not being available dates will be imputed 
on a case-by-case basis and documented prior to breaking the blind.


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Handling of unquantifiable laboratory data
It is expected that some UACR (centrally and locally assessed) and NT-proBNP (centrally 
assessed) values may be too low to quantify, prior to any summaries of these data they will be 
imputed to a value approximately halfway between 0 and the lower limit of detection.
Some UACR (locally assessed only) values may also be too high to quantify, prior to any 
summaries of these data they will be imputed to the 95th percentile from the local baseline 
UACR values, after imputation of the too low to quantify values.
The exact values used for the imputations will be documented prior to the database lock.
Other instances of laboratory values being too low or high to quantify are expected to be seen 
rarely and if observed, likely to be unreliable. In such instances the values will be considered 
as missing for any summaries.
6.7
BASELINE, TIME WINDOWS AND CALCULATED VISITS
Baseline will be defined as the last available measurement on or prior to the day of 
randomisation (excluding any pre-screening measurements). Per protocol, study treatment 
will start on the day of randomisation and baseline assessments will be taken prior to any 
intake of study treatment.
Where post-baseline efficacy or safety measurements need to be assigned to a specific follow-
up visit, time windows around the planned visit day are defined. The midpoint between two 
scheduled visits defines the end of a time window, with the midpoint being included in the 
time window of the preceding visit, as detailed in Table 6.7: 1.
Study days will be assigned relative to the day of randomisation. The day prior to 
randomisation will be ‘Day -1’ and the day of randomisation will be ‘Day 1’. Hence, ‘Day 0’ 
will not exist.
Table 6.7: 1
Time windows for post-baseline follow-up visits
Visit number
Follow-up visit
Planned day
Time window
Start
End
1
2 months
60
2
120
2
6 months
180
121
270
3
12 months
360
271
450
4
18 months
540
451
630
+ 1*
+ 6 months*
+ 180*
+ 180*
+180*
* Subsequent visits 6-monthly, add value to previous record in respective column
For summaries and analyses presented at a visit level only one observation per time window 
will be selected, this will be the value closest to the planned day. If there are two observations 
equidistant from the planned day then the earlier observation will be used, note only dates and 


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not times of assessments will be used in these calculations. For situations where we have two 
observations recorded on the same day a worst direction approach will be used to decide on 
the observation to select, refer to Section 9.4.
An exception to the above rule will be used for the handling of data collected at the final 
follow-up visit. If the final follow-up visit occurs within the same time window as the 
preceding visit, then the data collected at the final follow-up visit will take precedence, even if 
it is furthest from the planned day.
Time window for 4-week post final follow-up visit
For summaries of 4-week post final follow-up visit data only values measured >=7 days to 
<=42 days after the final follow-up visit will be considered. The value that is closest to the 
planned day of 28 days after the final follow-up visit will be used. The same approaches as 
defined above will be used for equidistant values and observations recorded on the same day.
6.8
CALCULATION OF TIME TO FIRST OCCURRENCE ENDPOINTS
All time to first occurrence endpoints will be reported in days and calculated as follows:
∀
For patients with the event of interest, the time to event is calculated as:
<date of event> - <date of randomisation> + 1
∀
For patients without the event of interest, the time at risk is calculated as:
<date of censoring> - <date of randomisation> + 1
For patients censored on the day of randomisation who are known not to have had any follow-
up, their time at risk will be assigned as zero.
6.8.1
Date of event
For adjudicated events, the date determined by the adjudication committee will be used 
irrespective of whether this differs from the investigator reported date.
For composite outcomes, the earliest onset date of the corresponding components will be 
used. For the component of CV death or other death components, date of death will be used.
For ESKD, the earliest onset date of any episode of maintenance dialysis or kidney transplant
will be used.
If the conditions for ‘sustained’ eGFR decline are met, the date of the event (i.e. laboratory 
test date) will be the date of the earlier of the two measurements (where applicable).
For events with multiple possible episodes, the onset date of the first episode will be used 
unless noted otherwise.
For the analysis of recurrent all-cause hospitalisations, the admission date of the 
hospitalisation will be taken as the AE onset date, and the discharge date as the AE onset date 


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+ the hospital duration. If the hospital duration is missing, then the discharge date will be 
taken as the AE end date. If this date is partial or missing the rules on missing hospital 
discharge dates detailed in Section 6.6 will be followed. Hospitalisations starting prior to 
randomisation will be ignored. Patients with overlapping hospitalisation events will have such 
events collapsed into one event, an overlapping event is one where the admission date of a 
hospitalisation is prior to or on the date of discharge of an earlier hospitalisation. The 
collapsing of hospitalisation events will take the earliest admission date and the latest 
discharge date.
For the OC-AD period of interest, all events occurring during the follow-up period will be 
considered. For the OC-OT period of interest, only events occurring during the on-treatment 
period will be considered. In all cases, events occurring after the final follow-up visit will not 
be considered.
6.8.2
Date of censoring
It is the aim at each scheduled follow-up visit to ascertain all components of all endpoints 
(where data is planned to be collected), with subsequent adjudication where applicable. 
Follow-up information will be collected from all patients, irrespective of whether they 
continue to take study treatment or not, usually at the scheduled follow-up visits, unless they 
withdraw consent. If patients are unwilling/unable to attend a scheduled follow-up visit the 
necessary information will be collected indirectly (e.g. via telephone). Every effort to collect a 
central blood sample will be made for each scheduled follow-up visit, but for those known to 
be alive who do not provide a blood sample, the most recent blood results will be recorded. 
For patients who are alive with no evidence of the event being analysed at their last/final
scheduled follow-up visit the date of the visit will be used as the date of censoring. The 
exception will be if the last/final scheduled follow-up visit is an indirect visit, in which case 
the date the patient is last known to be alive with no evidence of the event being analysed will 
be used (note this is the date of the telephone call if it was with the patient).
For composite endpoints that include a sustained decline in eGFR component, the above 
censoring dates will be used even if there is no eGFR value available at their last/final 
scheduled follow-up visit. This approach is being adopted as very few patients are expected to 
have a missing eGFR value at their final scheduled follow-up visit; it also avoids over 
complicated censoring rules for different components within a composite endpoint. 
For patients that die during the follow-up period date of death can be used as a censoring date 
as long as there is no evidence of the event being analysed at the time of death. For example,
if their death was not a CV death and they had not had a HHF, they would be censored at the 
time of death for the time to first occurrence of a HHF or CV death endpoint.
The above censoring rules apply to analyses of the OC-AD period of interest. For on-
treatment (OC-OT) analyses, patients will be censored at the minimum of the OC-AD 
censoring date or the end of the on-treatment period.


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7.
PLANNED ANALYSIS
In general, the BI guideline ‘Standards for Reporting of Clinical Trials and Project 
Summaries’ (6) will be followed for the End-Of-Text (EoT) tables. In summary:
∀
The set of summary statistics for continuous data is: N / Mean / Standard Deviation 
(SD) / Minimum (Min) / lower quartile (Q1) / Median / upper quartile (Q3) / 
Maximum (Max). The geometric mean and geometric coefficient of variation will also 
be presented for summaries of parameters known to follow a log-normal distribution.
The means, SDs, medians, Q1 and Q3 will be presented to one more decimal place 
than the raw data. Minima and maxima will be presented to the same number of 
decimal places as the raw data.
∀
Tabulations of frequencies for categorical data will include all possible categories and 
will display the number of observations in a category as well as the percentage (%) 
relative to the respective treatment group (unless otherwise specified, all subjects in 
the respective subject set whether they have non-missing values or not). Percentages 
will be rounded to one decimal place. The category missing will be displayed only if 
there are actually missing values.
∀
Standard errors (SEs) and confidence intervals (CIs) will be presented where 
appropriate and to one more decimal place than the raw data. P-values will be 
presented to four decimal places.
The trial is planned to continue until a minimum of 1070 first primary endpoint events have 
occurred, at which point patients will be invited to attend their final follow-up visit, this may 
occur earlier than their planned next 6-monthly visit.
A formal interim analysis may be conducted by the DMC when a minimum of 150 first 
ESKD events have occurred. If the pre-defined stopping criteria are met, then the trial will be 
stopped early for overwhelming efficacy. Further details are provided in the CTP, the DMC 
charter and Section 9.2 of this TSAP.
7.1
DEMOGRAPHIC AND OTHER BASELINE CHARACTERISTICS
Only descriptive statistics are planned for this section of the report, based on the RS of 
patients.
7.2
CONCOMITANT DISEASES AND MEDICATION
Only descriptive statistics are planned for this section of the report, based on the RS of 
patients.
7.3
TREATMENT COMPLIANCE
Only descriptive statistics are planned for this section of the report, based on the TS of 
patients.


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Appropriate summaries of compliance before and from the start of the COVID-19 disruption 
will be produced.
7.4
PRIMARY ENDPOINT
The primary estimand of this trial is the hazard ratio (HR) of the time to first occurrence of 
kidney disease progression or CV death in the target population, for patients randomised to 
empagliflozin 10 mg relative to those randomised to placebo on top of standard care. This 
estimand will ignore any non-fatal intercurrent events and is in the hypothetical absence of 
death from any cause not included in the endpoint.
The primary analysis will be based on the RS of patients using all available data from the 
follow-up period (OC-AD), data occurring after the final follow-up visit will not be 
considered.
7.4.1
Primary analysis of the primary endpoint
The primary endpoint will be analysed using a Cox proportional hazards regression model 
with factors of treatment (empagliflozin, placebo) and each of the variables used in the 
minimization algorithm for randomisation. The randomisation factors will be fitted according 
to the same categories used in the minimization; for age (<45, ≥45 to <55, ≥55 to <65, ≥65 to 
<75, ≥75), sex (male, female), DM status (yes, no), local screening eGFR (<30, ≥30 to <45, 
≥45 to <60, ≥60 to <75 and ≥75) and local screening UACR (<20, ≥20 to <200, ≥200 to <500, 
≥500 to <1000, ≥1000). However, for region (North America, Europe, Japan, Other Asia 
[China or Malaysia]) the actual region a patient was randomised from will be fitted.
This model will be used to test the equality of the hazard rates via the Wald test for the 
treatment effect. The same model will used to estimate the HR of the treatment effect and the 
corresponding asymptotic two-sided 95% Wald CI. A HR of less than one favours 
empagliflozin. Breslow’s method for handling ties will be used.
For the interim and final analyses of the primary endpoint the Hwang-Shih-DeCani alpha-
spending function with parameter γ=-8 will be used to account for multiplicity. The required 
alpha-levels are expected to be 0.0020 and 0.0497 (two-sided) for the interim and final tests 
respectively, assuming 60% of the primary outcome events have accrued at the time of the 
interim analysis. The alpha-levels will be adjusted according to the actual proportion of 
primary outcome events observed at the interim. In addition to the 95% CIs described above, 
two-sided CIs based on the required alpha-levels will also be produced.
Cumulative incidence function (CIF) and/or Kaplan-Meier (KM) curves will also be produced 
to summarise the primary endpoint data. The number of events in each of the individual 
components that contribute to the overall number of primary composite events will also be 
summarised descriptively.
The proportional hazards assumption will be explored by plotting log (-log (survival 
function)) against the log of time by treatment group and visually inspected for parallelism. 
The interaction of treatment with log of time will be included in the primary endpoint model 
described above, as an exploratory analysis. Further, Schoenfeld residuals for each covariate 
and treatment will be plotted against time and log (time).


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7.5
SECONDARY ENDPOINTS
7.5.1
Key secondary endpoints
If statistical significance is observed for the primary endpoint, then the key secondary 
endpoints will be formally analysed via the Hochberg ‘step-up’ procedure to control the 
familywise error rate. Note for formal analysis of the key secondary endpoints at the interim 








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7.5.2
Other secondary endpoints
The other secondary endpoints defined in Section 5.2.2 will be analysed using the same 
methodology as for the primary endpoint. No formal hypothesis testing or adjustment for 
multiple testing will be performed for these endpoints, the analyses will be considered as 
supportive to the main analyses.
The analysis of all other secondary endpoints will be based on the RS of patients using all 
available data from follow-up period (OC-AD).


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7.7
EXTENT OF EXPOSURE
A standard descriptive summary of the duration of treatment exposure and the duration of the 
observational period will be produced, the former on the TS and the latter on the RS. These 
tables will also provide the sum-total of the time (in years) exposed across all patients.
Frequency tables of the number and percentage of patients belonging to the categorical ranges 
of exposure (in weeks) will also be provided. The following categories are planned but may 
be adapted: ≥0 to <8, ≥8 to <26, ≥26 to <52, ≥52 to <78, ≥78 to <104, ≥104 to <130, ≥130 to 
<156 and ≥156 weeks.


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7.8
SAFETY ANALYSIS
Where applicable, the sections below are divided into trial-specific safety endpoint analyses 
and BI/project standard analyses of routine safety data. The trial-specific safety endpoints are 
those specifically defined in the CTP and will be analysed for both the RS and TS. All 
BI/project standard analyses of routine safety data will be performed on the TS, treatment will 
be evaluated as randomised. Unless stated otherwise the RS analyses will use data from the 
OC-AD period of interest and the TS analyses will use data from the OC-OT period of 
interest. For the OC-OT analyses any REP after the final follow-up visit will not be 
considered for the trial-specific endpoints but will be considered for BI/project standard 
analyses of routine safety data. One exception will be for BI/project standard analyses of 
routine safety data that are based purely on adjudicated terms, these will also not consider the 
REP after the final follow-up visit, as adjudication is not planned for events with an onset 
after the final follow-up visit.
While tables will generally display results by randomised treatment, listings will reflect 
whether a measurement/AE occurred on- or off-treatment.
In addition to the summaries below, standard tables required for the clinical trials disclosure 
process (ClinicalTrials.gov and EudraCT) will be produced (15).
7.8.1
Adverse Events
As the safety profile of empagliflozin has been well studied in previous trials collection of 
safety data has been streamlined. Only pre-specified non-serious AEs are planned to be
collected along with all SAEs. The exception to this will be for patients entered in Japanese 
sites, where all AEs (non-serious AEs and SAEs) will be recorded. The pre-specified non-
serious AEs are:
∀
Leading to study drug discontinuation
∀
Bone fracture
∀
Severe hypoglycaemia
∀
Gout
∀
Symptomatic dehydration
∀
AESIs (ketoacidosis, lower limb amputation and liver injury)
∀
Could lead to amputation
Unless stated otherwise the AE analyses detailed below will only be based on the pre-
specified non-serious AEs and SAEs.
The focus of the AE evaluation will be based on the adjudicated terms, and these will take 
precedence over investigator-reported terms for all of the analyses and summaries described 
below. Summaries will be provided to show the results of adjudication in particular 
summarising any changes in investigator-reported AE PTs.
AEs will be coded using MedDRA 20.1.


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7.8.1.1
Analysis of trial-specific AE endpoints
The time to first occurrence of the trial-specific AE endpoints detailed in Section 5.4 will be 
analysed using the same methodology as for the primary efficacy endpoint (Section 7.4.1).
The main analysis of these endpoints will be based on the RS using all available data from 
follow-up period (OC-AD). Additional analyses on the TS using all on-treatment data (OC-
OT) will also be performed.
No formal hypothesis testing or adjustment for multiple testing will be performed for these 
endpoints, any p-values presented will be for information only.
7.8.1.2
Standard analyses of AEs
Unless otherwise specified, the analyses of AEs in this section will be descriptive in nature
and based on the TS using data from the OC-OT period of interest. All analyses of AEs will 
be based on the number of patients with AEs and not on the number of AEs.
For further details on the summarisation of AE data, please refer to (16) and (17).
The on-treatment analysis of AEs will be based on the concept of treatment emergent AEs, 
whereby all AEs occurring between first drug intake (randomisation date) up to 7 days (REP) 
after last drug intake will be assigned to the randomised treatment. All AEs occurring before 
first drug intake will be assigned to ‘screening’ and all AEs occurring after the REP will be 
assigned to ‘post-treatment’. For details on the treatment definition, see Section 6.1.
In general, AE summaries will present only on-treatment AEs (applying the 7-day REP rule); 
though there are some additional summaries described below where longer periods after 
discontinuing study treatment are considered.
7.8.1.2.1
General AE summaries
An overall summary of AEs will be presented.
The frequency of patients with AEs will be summarised by treatment, primary SOC and PT.
Incidence rates as defined in Section 7.8.1.2.5 will generally be included. Separate tables will 
be provided for patients, for each of the following:
∀
All AEs
∀
Study drug-related AEs
∀
SAEs
∀
Study drug-related SAEs
∀
AESIs (ketoacidosis, lower limb amputations and liver injury) ‘as adjudicated’
∀
AEs leading to study drug discontinuation
∀
AEs with a fatal outcome






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Serious genital infections
Frequency tables of patients with a serious genital infection event ‘as adjudicated’ will be 
produced by adjudicated primary SOC and PT. 
 
7.8.1.2.4
Specific AEs
Hepatic events
Patients with hepatic AEs (whether associated with liver injury or not) will be summarised 
based on a Standardised MedDRA Query (SMQ) based definition. From the SMQ ‘Drug 
related hepatic disorders (20000006)’ the following narrow sub-SMQs will be used:
∀
Narrow sub-SMQ Liver related investigations, signs and symptoms (20000008)
∀
Narrow sub-SMQ Cholestasis and jaundice of hepatic origin (20000009)
∀
Narrow sub-SMQ Hepatitis, non-infectious (20000010)
∀
Narrow sub-SMQ Hepatic failure, fibrosis and cirrhosis and other liver damage-related
conditions (20000013)
A table with frequencies of patients with these AEs by treatment, primary SOC and PT will 
be provided. 
. SAEs and AEs 
leading to study drug discontinuation based on the above SMQ definition will also be 
presented.
In addition to the ‘7-day on-treatment approach’, a ‘30-day on-treatment approach’ will be 
presented for all AEs based on the SMQ definition.
Events indicative of ketoacidosis
A frequency table of patients with an AE indicative of ketoacidosis will be presented by 
treatment, primary SOC and PT for terms within the narrow BI customised MedDRA Queries 
(BIcMQ) definition of diabetic ketoacidosis (DKA). For these terms, patients with SAEs and 
AEs leading to study drug discontinuation 
 will be 
presented.
Hypoglycaemic events
Patients with AEs of severe hypoglycaemia, defined as low blood sugar causing severe 
cognitive impairment, which requires assistance from another person for recovery, will be 
summarised. The summary will include the number of episodes, serious episodes and whether 
any led to study drug discontinuation.
In addition, the number of patients with an AE in the SMQ ‘Hypoglycaemia (20000226)’ 
(narrow) will be presented by primary SOC and PT. This will be repeated for SAEs and AEs 
leading to study drug discontinuation.






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date 7 days prior to a patient’s first COVID-19 AE until the end of the on-treatment period 
will be used.
A listing will be prepared presenting details of all COVID-19 AEs.
7.8.1.2.5
AE incidence rates
In addition to the frequency tabulations, time-adjusted AE analyses will be performed for all
applicable summaries.
The time at risk in patient years for the on-treatment period is derived as follows:
Patients with AE:
Time at risk (AE) in days = date of start of AE – randomisation date + 1
Patients without AE:
Time at risk (AE) in days = end date of time at risk – randomisation date + 1, where end date 
of time at risk is the minimum of date of last study drug intake + x days or date of death, if 
applicable.
The standard approach will be x=7 days, but x=30 days and ‘up to trial completion’ 
approaches will also be used.
Total AE-specific time at risk per treatment group is then derived as:
Time at risk (AE) [years] = Sum of time at risk [days] over all patients in a treatment 
group/365.25
For ‘each row of a table’ (e.g. displaying an SOC), time at risk is calculated using start of first
AE summarized for the row; e.g. for patient with AE in a specified SOC, time at risk = date of
start of AE with specified PT in this SOC – date of randomisation + 1.
The AE incidence rate per 100 patient years will then be calculated as follows:
Incidence rate per 100 patient years (pt-yrs) = 100 * number of patients with AE / time at risk
(AE) [years].
7.8.2
Laboratory data
Safety tables will not include central or local assessments of eGFR, UACR or HbA1c as these 
data are summarised in the efficacy section.
7.8.2.1
Analysis of trial-specific laboratory endpoints
The main analysis of these endpoints be based on the RS of patients using all available data 
from follow-up period (OC-AD). Additional analyses on the TS of patients using all on-
treatment data (OC-OT) will also be performed.


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Potassium
Changes from baseline in locally assessed potassium will be evaluated using a MMRM 
following the same methodology as detailed in Section 7.6.2.
Liver transaminases
A categorical summary by treatment group for each of the following categories will be 
produced:
∀
ALT or AST ≥5 x ULN
∀
ALT or AST ≥3 x ULN with bilirubin ≥2 x ULN, in the same blood sample
The effect of allocated treatment on each of the above categories will be compared using a 
chi-squared test. If any of the expected cell counts in the 2x2 contingency table are less than 
5, the Fisher’s exact test will be used instead of the chi-squared test.
Haematocrit, haemoglobin, sodium, calcium and phosphate
These parameters are only measured and collected for the UK subset of patients; haematocrit 
and haemoglobin are measured at baseline and 18 months and sodium, calcium and phosphate 
at 18 month only.
Changes from baseline to 18 months in haematocrit and haemoglobin will be compared 
between the two treatments using ANCOVA with baseline fitted as a covariate. Mean values 
at 18 months for sodium, calcium and phosphate will be compared between the two 
treatments using t-tests.
7.8.2.2
Standard analyses of laboratory data
The analyses of laboratory data will be descriptive in nature and will be based on BI standards 
(18).
Before summarising, laboratory data will be converted to conventional units. Where 
conventional units differ from the International System of Units (SI), summaries will be 
repeated.
Standard descriptive summaries will be provided by treatment group for baseline, last value 
on-treatment and changes from baseline to last value on treatment. These summaries will be 
based on converted values.
Laboratory values will be compared to their reference ranges (where available) via frequency 
tables showing the number of patients within and outside the reference range at baseline and 
for the last value on treatment. Frequency tables will also summarise the number of patients 
with potentially clinically significant abnormalities, as defined using standard BI criteria. 
These summaries will be based on converted values.
To support the analyses of liver related AEs, frequency tables showing the number of patients 
falling into each of the following categories will be produced:


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∀
ALT and/or AST ≥3 x ULN, ≥5 x ULN, ≥10 x ULN and ≥20 x ULN
∀
ALT and/or AST ≥3 x ULN with bilirubin ≥2 x ULN (in the same blood sample or 
within 30 days of the elevated liver enzyme)
A graphical display (eDISH plot) of ALT and bilirubin will also be produced. For the TS OC-
OT summaries, all liver enzyme elevations up to 30 days after study treatment discontinuation 
will be considered.
7.8.3
Vital signs
A MMRM analysis of changes in weight, SBP and DBP will performed using the 
methodology detailed in Section 7.6.2.
A descriptive summary of changes in hip and waist circumference will also be produced.
7.8.4
ECG
Not applicable for this trial.
7.8.5
Others
The effect of allocated treatment on discontinuation of study treatment, both overall and by 
reason of discontinuation [SAEs (overall and by SOC), non-serious AEs (overall and by SOC) 
and other reasons], will be compared using a chi-squared test. If any of the expected cell 
counts in the 2x2 contingency table are less than 5, the Fisher’s exact test will be used instead 
of the chi-squared test.


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8.
REFERENCES
1.
CPMP/ICH/363/96: “Statistical Principles for Clinical Trials”, ICH Guideline Topic 
E9, Note For Guidance on Statistical Principles for Clinical Trials, current version.
2.
EDMS #6290: Standard Operating Procedure 11: Data Analysis Plan, University of 
Oxford, 
3.
R Core Team (2021). R: A language and environment for statistical computing. R 
Foundation for Statistical Computing, Vienna, Austria. URL
4.
EDMS #6062: Standard Operating Procedure 9b: Adjudication Procedures (EMPA-
KIDNEY), University of Oxford, 
5.
KDIGO 2020 clinical practice guideline for diabetes management in chronic kidney 
disease, Kidney Int. 2020; 98(4) (Suppl) [P20-09106]
6.
BI-KMED-BDS-HTG-0045: “How to Guide: Standards for Reporting of Clinical Trials 
and Project Summaries”
7.
Beyersmann J, Allignol A, Schumacher M “Competing risks and multistate models with 
R”, New York: Springer (2012) [R16-3839]
8.
Jackson D, et al. “Relaxing the independent censoring assumption in the Cox 
proportional hazards model using multiple imputation”, Stats Med 33, 4681-4694 
(2014) [R21-2797]
9.
Burkoff N, et al. “Gamma imputation tutorial (Jackson 2014)”, vignette for 
InformativeCensoring R library, July 2020 [R21-2798]
10. Rogers JK, et al. “Analysis of recurrent events with an associated dropout time: 
application of the joint frailty model”, Stat Med 13, 2195-2205 (2016) [R16-2229]
11. Lu L, Liu C “Analysis of correlated recurrent and terminal events data SAS®”, NESUG 
(2008) [R20-1940]
12. Liu L, Yu Z “A likelihood reformulation method in non-normal random effects 
models”, Stats Med 27, 3105-3124 (2008) [R19-4129]
13. Rogers JK, et al. “Analysing recurrent hospitalisations in heart failure: a review of 
statistical methodology, with application to CHARM-Preserved”, Eur J Heart Fail 16, 
33-40 (2014) [R16-4909]
14. Vonesh, et al. “Mixed-effects models for slope-based endpoints in clinical trials of 
chronic kidney disease”, Stats Med 38, 4218-4239 (2019) [R19-4093]
15. BI-KMED-BDS-QRG-0010: “Quick Reference Guide: Preparation of tables for results 
disclosure”
16. BI-KMED-BDS-HTG-0035: “How to Guide: Handling of Missing and Incomplete AE 
dates”


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17. BI-KMED-BDS-HTG-0041: “How to Guide: Analysis and Presentation of Adverse 
Event Data from Clinical Trials – Display Template”
18. BI-KMED-BDS-HTG-0042: “How to Guide: Handling, Display and Analysis of 
Laboratory Data”


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9.2
INTERIM ANALYSIS
A formal interim analysis may be performed by the DMC when a minimum of 150 first 
ESKD events have occurred. If based on the results of the interim analysis, pre-defined 
stopping criteria are met and the DMC recommend stopping the trial for efficacy, substantial 
further data will be collected as patients will attend their final follow-up visits and provide 
latest information on their renal status and blood for central creatinine analysis. All formal 
hypothesis testing will be based on the results of the analyses from the final database 
including data from the final follow-up visits. Note the information fraction used in the alpha-
spending functions for the primary and key secondary endpoints will be based on the number 
of primary outcome events observed at the time of the DMC interim analysis, as a proportion 
of the anticipated number at the scheduled end of the trial. Formal statistical testing of the key 
secondary endpoints will be performed via the Hochberg procedure controlling the overall 
type I error rate, refer to Section 7.5.1.
Agreement may be sought from the Steering Committee to delay or cancel the planned 
interim analysis in the following circumstances:
∀
If predictive models based on available blinded data indicate an expected period of 
less than or equal to 3 months between the accrual of 150 first ESKD events and of 
1070 first primary outcome events. In this instance the interim analysis would not be 
conducted.
∀
If unforeseen circumstances (e.g. a significant worsening of the COVID-19 pandemic) 
make the conduct of the interim analysis operationally not feasible. In this instance the 
interim analysis would be delayed and potentially not conducted if the delay led to the 
above bullet being met.
If a formal interim efficacy analysis is not conducted the primary endpoint will be formally 
assessed without adjustment for multiplicity and the key secondary endpoints controlled at the 
familywise error rate of 5.0%.




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proc nlmixed data = <input data> gconv=1E-18 fconv=2.2E-18 qpoints=50;
  parms / data= <param>; *-- dataset of initial parameter values from optimisation step --*;
  *-- r = bounds for recurrent events, h = bounds for death events --*;
  bounds r01 r02 r03 r04 r05 h01 h02 h03 h04 h05 theta >= 0;
  base_haz_r = r01*event_r1+r02*event_r2+r03*event_r3+r04*event_r4+r05*event_r5;
  cum_base_haz_r = r01*dur_r1+r02*dur_r2+r03*dur_r3+r04*dur_r4+r05*dur_r5;
  base haz d = h01*event d1+h02*event d2+h03*event d3+h04*event d4+h05*event_d5;
  cum_base_haz_d = h01*dur_d1+h02*dur_d2+h03*dur_d3+h04*dur_d4+h05*dur_d5;
  logofloggammadens = (1/theta)*nu-(1/theta)*exp(nu)-lgamma(1/theta)-(1/theta)*log(theta);
  logofstandardnormal = -(nu**2)/2;
  linpred1= beta11*TRT + <beta1x*covariatex> +nu;
  linpred2= beta21*TRT + <beta2x*covariatex> +gamma*nu;
  loglik1=-exp(linpred1) * cum base haz r;
  loglik2=-exp(linpred2) * cum_base_haz_d;
  *-- log likelihood for recurrent events --*;
  if cnsr = 1 then loglik=log(base_haz_r)+linpred1;
  *-- log likelihood for deaths --*;
  if cnsr = 2 then loglik=loglik1+log(base_haz_d)+linpred2+loglik2+logofloggammadens-
logofstandardnormal;
  *-- log likelihood for censoring --*;
  if cnsr = 0 then loglik=loglik1 + loglik2 + logofloggammadens - logofstandardnormal;
  model timevar ~ general(loglik);
  random nu ~ normal(0,1) subject=usubjid;
run;
** End of Code **;
9.6
DEFINING SUSTAINED EGFR DECLINES AND USE OF LOCAL DATA
The following rules provide further detail on the derivation rules for defining sustained eGFR 
declines and the use of local data:
∀
Select only one value per visit window to be used in the derivation of events, plus the 
final follow-up visit sample if not already selected. Results after the final follow-up 
visit are not used.


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∀
Events are derived from the central and local laboratory data separately. Local 
laboratory values cannot confirm a central laboratory value (or vice versa), with 
respect to being ‘sustained’.
∀
An event cannot be obtained from a local laboratory value at a visit if a central 
laboratory value is also available at that visit.
∀
When determining if a value is sustained due to a second measurement the second 
measurement meeting the criteria must be from the next planned visit in the protocol 
defined schedule and be at least 30 days later. If a visit is missing before the next 
value meeting the criteria, then this is not considered sustained, e.g., meeting the 
criteria at 6 months and 18 months with no measurements at 12 months does not 
qualify as an event.
∀
A value may also be considered sustained if it is the latest result at the last visit 
window. Last visit window is defined separately for central and local laboratory data
so may be defined as two different visit windows in a patient.
∀
For central laboratory data it is defined as the last visit window that contains either a 
central laboratory measurement or a direct visit, i.e., a visit in person.
∀
For local laboratory data it is defined as the last visit window that contains either a 
local laboratory measurement or a direct visit, i.e., a visit in person.










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