Sequential Expansion of Comparative Effectiveness of Oral Anticoagulants: A Cohort Study
Conditions: Atrial Fibrillation
Sponsor: Boehringer Ingelheim

ABCD
TITLE PAGE
Protocol for observational studies based on existing data
TITLE PAGE
Document Number: 
c02336230-01
BI Study No.:
1160.207
BI Investigational 
Product(s):
PRADAXA (dabigatran etexilate)
Title:
Sequential Expansion of Comparative Effectiveness of Oral 
Anticoagulants: A Cohort Study
(Phase 2 of the BI/
 Pradaxa study program)
Title for lay people:
Comparative effectiveness of oral anticoagulants
Date of last version of 
protocol:
25 Feb 2014
EU PAS Register No:
only applicable for PASS
N/A
Marketing 
authorization holder(s):
Boehringer Ingelheim
Author / Responsible 
Parties/BI contact 
person:
 
 
.  
All from the 
 
 
 
Country(-ies) of study:
US
Status:
Final Protocol
EU-QPPV:
only applicable for PASS
Signature of EU-QPPV:
only applicable for PASS
Version and Date:
Version 1, 25 Feb 2014
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PROTOCOL ABSTRACT
Name of company:
ABCD
Boehringer Ingelheim 
Name of product: 
PRADAXA®
Name of active ingredient:
DABIGATRAN ETEXILATE
Protocol date:
Study number:
Version/Revision:
Version/Revision date:
25 Feb 2014
1160.207
Version 1
25 Feb 2014
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Title of study:
Sequential expansion of comparative effectiveness of oral anticoagulants: a cohort 
study
Team member 
Epidemiology:
Project team:
 
 
Rationale and 
background:
A number of new oral anticoagulants are being developed and marketed to 
replace vitamin K antagonists.  Unlike vitamin K antagonists, these new drugs 
do not require dose titration involving intensive therapeutic monitoring of 
prothrombin time to achieve target anticoagulation within a narrow 
therapeutic range. However, their long-term safety and effectiveness have not 
been characterized in a real-world setting.
Research question and 
objectives:
This protocol is for a series of comparative effectiveness and safety analyses 
within periodically updated cohorts of patients initiating dabigatran 
(compared to warfarin) and other new oral anticoagulants (NOAC) (as they 
become available), compared to warfarin, followed longitudinally for the 
occurrence of a variety of health outcomes.
Objectives
1) Primarily, to conduct direct comparisons over time between dabigatran 
and warfarin and quantify the association between anticoagulant choice 
and the occurrence of specific outcomes of interest
2) Secondarily, to monitor the number of people initiating other NOAC 
medications and, when sufficient, to compare study outcomes between 
other NOAC medications and warfarin 
Study design:
Observational sequential cohort study based on existing data

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Name of company:
ABCD
Boehringer Ingelheim 
Name of product: 
PRADAXA®
Name of active ingredient:
DABIGATRAN ETEXILATE
Protocol date:
Study number:
Version/Revision:
Version/Revision date:
25 Feb 2014
1160.207
Version 1
25 Feb 2014
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This document may not - in full or in part - be passed on, reproduced, published or otherwise used without prior written permission
Population:
Patients with a recorded diagnosis of atrial fibrillation without evidence of 
valvular etiology who initiate dabigatran (or other NOACs as they become 
available) compared with warfarin initiators.
Study data source:
This study will be conducted within both UnitedHealth and Marketscan data 
sources.  The first analyses of this study will include data from October 2010 
through December 2012 for the cohort formation and data from July 2008 
through September 2010 for disease risk score (DRS) calculation. Both data 
sources will be updated on a 6-month basis through December 2015
Expected study size:
The estimated final study size will be ~ 60,000 dabigatran initiators, matched 
to ~60,000 warfarin initiators with approximately 24,000 cumulative person-
years of observation in each exposure group, and other NOAC initiators 
(numbers dependent on use) separately matched to a similar number of 
warfarin initiators.
The estimated study size (after PS matching) for interim analyses:
Interim report 1 (Apr 2014): ~ 24,000 dabigatran and ~24,000 warfarin 
initiators with 10,000 PYs of observation in each group 
Interim report 2 (Jul 2014): ~ 30,000 dabigatran and ~30,000 warfarin 
initiators with 12,350 PYs of observation in each group
Interim report 3 (Nov 2014): ~ 36,000 dabigatran and ~36,000 warfarin 
initiators with 14,700 PYs of observation in each group
Interim report 4 (Mar 2015): ~ 42,000 dabigatran and ~42,000 warfarin 
initiators with 17,050 PYs of observation in each group
Interim report 5 (Sep 2015): ~ 48,000 dabigatran and ~48,000 warfarin 
initiators with 19,400 PYs of observation in each group
Interim report 6 (Mar 2016): ~ 54,000 dabigatran and ~54,000 warfarin 
initiators with 21,750 PYs of observation in each group
Final report (Dec 2016): ~ 60,000 dabigatran and ~60,000 warfarin initiators 
with 24.100 PYs of observation in each group

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Name of company:
ABCD
Boehringer Ingelheim 
Name of product: 
PRADAXA®
Name of active ingredient:
DABIGATRAN ETEXILATE
Protocol date:
Study number:
Version/Revision:
Version/Revision date:
25 Feb 2014
1160.207
Version 1
25 Feb 2014
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© 2014 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
Main criteria for 
inclusion:

A recorded diagnosis of atrial fibrillation.

Initiation of anticoagulant medication (dabigatran (or other NOACs as 
they become available) or warfarin).

At least 18 years of age on the date of anticoagulant initiation.

CHA2DS2-VASc score ≥ 1
Main criteria for 
exclusion:

Patients with missing or ambiguous age or sex information.

Patients with evidence of valvular disease.

Patients with less than 12 months enrolment preceding the date of 
anticoagulant initiation 

Patients with  a dispensing of any oral anticoagulant during the 12 
months preceding the date of anticoagulant initiation

Patients with a nursing home stay during baseline
Comparison group:
Warfarin
Expected duration of 
exposure:
As observed in the data source

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TABLE OF CONTENTS
TITLE PAGE ...........................................................................................................................1
PROTOCOL ABSTRACT......................................................................................................2
TABLE OF CONTENTS ........................................................................................................5
LIST OF TABLES...................................................................................................................7
LIST OF FIGURES.................................................................................................................8
1.
LIST OF ABBREVIATIONS AND TERMS......................................................9
2.
RESPONSIBLE PARTIES ................................................................................11
3.
AMENDMENT AND UPDATES ......................................................................12
4.
MILESTONES ....................................................................................................13
5.
RATIONALE AND BACKGROUND ..............................................................14
6.
RESEARCH QUESTIONS AND OBJECTIVES............................................15
7.
RESEARCH METHODS...................................................................................16
7.1
STUDY DESIGN.................................................................................................16
7.2
SETTING.............................................................................................................17
7.3
SUBJECTS ..........................................................................................................17
7.4
VARIABLES .......................................................................................................19
7.4.1
EXPOSURES.......................................................................................................19
7.4.2
OUTCOME(S).....................................................................................................21
7.5
DATA SOURCES ...............................................................................................36
7.6
BIAS .....................................................................................................................37
7.7
STUDY SIZE.......................................................................................................38
7.9
DATA ANALYSIS..............................................................................................40
7.9.1
MAIN ANALYSIS ..............................................................................................40
7.10
QUALITY CONTROL.......................................................................................45
7.11
LIMITATIONS OF THE RESEARCH METHODS ......................................45
7.12
OTHER ASPECTS .............................................................................................46
8.
PROTECTION OF HUMAN SUBJECTS .......................................................47
9.
MANAGEMENT AND REPORTING OF ADVERSE 
EVENTS/ADVERSE REACTIONS..................................................................48
10.
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY 
RESULTS ............................................................................................................49
11.
REFERENCES....................................................................................................50
12.
FUNDING............................................................................................................53

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13.
ANNEX ................................................................................................................54
ANNEX 1: LIST OF STAND-ALONE DOCUMENTS .....................................................54
ANNEX 3  EXAMPLE STUDY SHELL TABLES.............................................................65
ANNEX 4  STUDY FIGURES..............................................................................................73

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LIST OF TABLES 
Table 1
Market availability for the treatments of interest.......................................19
Table 2
Outcome Definitions.......................................................................................21
Table 7
UnitedHealth and MarketScan databases, estimated numbers of  
dabigatran and warfarin with non-valvular atrial fibrillation diagnosis, 
in the period October 2010 – June 2012.......................................................37
Table 8
Projected minimum detectable relative rates* by reporting period..........38
 
 
 
Table A3 
Follow-up and outcomes among matched cohorts ......................................70
Table A4 
Follow-up and distribution of reasons for discontinuation........................71
 

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LIST OF FIGURES
Figure 1
Patient Selection Flow....................................................................................19
Figure A1
Patient Selection Flow Diagram (CONSORT Style)...................................73
Figure A2
Survival curves (time to event)......................................................................74

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1.
LIST OF ABBREVIATIONS AND TERMS 
ACCP
American College of Chest Physicians
ACEI
Angiotensin-converting Enzyme Inhibitor
AES
Advanced Encryption Standard
AF
Atrial Fibrillation
ALT
Serum Alanine Aminotransferase
ARB
Angiotensin Receptor Blocker
ASCVD
Atherosclerotic Cardiovascular Disease
BB
Beta Blocker
BI
Boehringer Ingelheim
BMI
Body Mass Index
CABG
Coronary Artery Bypass Graft
CAD
Coronary Artery Disease
CCB
Calcium Channel Blocker
CHA2DS2-VASc
Congestive Heart Failure, Hypertension, Age > 75, Diabetes 
Mellitus, Prior Stroke or Transient Ischemic Attack, Vascular 
Disease, Age 65-74, Sex Category
CHADS2
Congestive Heart Failure, Hypertension, Age> 75, Diabetes 
Mellitus, Prior Stroke or Transient Ischemic Attack
CHF
Congestive Heart Failure
CI
Confidence Interval
CONSORT
Consolidated Standards for Reporting Trials
CPT
Current Procedural Terminology
Cr
Creatinine
DM
Diabetes Mellitus
DRG
Disease
DRS
Disease Risk Score
DVT
Deep Venous Thromboembolism
Dx
Diagnosis-Related Group
ESC
European Society of Cardiology
GFR
Glomerular Filtration Rate
GI
Gastrointestinal
H2 Receptor
Histamine H2 Receptor
HAS-BLED
Hypertension, Abnormal Liver/Renal function, Stroke, Bleeding 
history or predisposition, Labile INR, Elderly (Age >65), Drugs-
Alcohol usage
HbA1c
Hemoglobin A1C
HCPC
Healthcare Common Procedure Coding
hdPS
High-dimensional Propensity Score
HR
Hazard Ratio
ICD-9
International Classification of Diseases, Ninth Revision, Clinical 
Modification

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ICH
Intracerebral Hemorrhage
INR
International Normalized Ratio
ITT
Intent-To-Treat
LDL
Low Density Lipoprotein
LOS
Length of Stay
MDRD
Modification of Diet in Renal Disease
MI
Myocardial Infarction
NOAC
New Oral Anticoagulant
NSAID
Non-steroidal Anti-inflammatory Drug
NVAF
Non-valvular Atrial Fibrillation
PAD
Peripheral Artery Disease
PCI
Percutaneous Coronary Intervention
PE
Pulmonary Embolism
PGP
P-glycoprotein
PPI
Proton Pump Inhibitor
PPV
Positive Predictive Value
PS
Propensity Score
PTCA
Percutaneous Transluminal Coronary Angioplasty
PVD
Peripheral Vascular Disease
PY
Person-Year
RE-LY
Randomized Evaluation of Long-Term Anticoagulation Therapy
RR
Relative Risk
SAH
Subarachnoid Hemorrhage
SCr
Serum Creatinine
SD
Standard Deviation
TIA
Transient Ischemic Attack
US
United States
VTE
Venous Thromboembolism

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2.
RESPONSIBLE PARTIES
 (1)
 (1)
 (1)
 (1)
(1)
 

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3.
AMENDMENT AND UPDATES
None

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4.
MILESTONES
Planned dates for the following milestones:
Date
Phase 2
Data Source
Milestone
Month
United
Claims and lab data are released 
every 6 months in Jan and Jul 
(6-month lag time)
MarketScan
Claims data are released quarterly
in Mar, Jun, Sept, and Dec 
(9-month lag time) 
Lab data are released yearly 
in Dec (12-month lag time)  
Jun, 2012
Contract
0
Year 1
Jun, 2013
Draft Protocol
12
Year 2
Jan, 2014
Final Protocol
19
Apr, 2014
Interim Report 1
22
Data through Dec 2012 
Claims through Dec 2012 
Labs through Dec 2012
Jul, 2014
Interim Report 2
25
Data through Jun 2013
(Update received in Jan 2014)
Claims through Jun 2013 
(Update received in Mar 2014)
Labs through Dec 2012
(Update received in Dec 2013)
Nov, 2014
Interim Report 3
29
Data through Dec 2013
(Update received in Jul 2014)
Claims through Sep 2013
(Update received in Jun 2014)
Labs through Dec 2012
(Update received in Dec 2013)
Year 3
Mar, 2015
Interim Report 4
32
Data through Jun 2014
(Update received in Jan 2015)
Claims through Dec 2013
(Update received in Dec 2014)
Labs through Dec 2013
(Update received in Dec 2014)
Sep, 2015
Interim Report 5
39
Data through Dec 2014
(Update received in Jul 2015)
Claims through Sep 2014
(Update received in Jun 2015)
Labs through Dec 2013
(Update received in Dec 2014)
Year 4
Mar, 2016
Interim Report 6
45
Data through Jun 2015
(Update received in Jan 2016)
Claims through Dec 2014 
(Update received in Dec 2015)
Labs through Dec 2014
(Update received in Dec 2015)
Year 4
Dec, 2016
Final Report
54
Data through Dec 2015
(Update received in Jul 2016)
Claims through Dec 2015
(Update received in Sep 2016)
Labs through Dec 2014
(Update received in Dec 2054)

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5.
RATIONALE AND BACKGROUND
A number of new oral anticoagulants are being developed and marketed to replace vitamin K 
antagonists, one of the most important drugs in modern medicine. [P11-11875] Unlike 
vitamin K antagonists, these new drugs do not require dose titration involving intensive 
therapeutic monitoring of prothrombin time to achieve target anticoagulation within a narrow 
therapeutic range. In Phase III studies, these drugs were found to be therapeutically 
advantageous or non-inferior over warfarin. In the coming years, as many as six new 
anticoagulants could be on the market and a lack of valid comparative evidence will hinder 
prescriber and payor decision-making.
To date, these drugs have been studied in randomized clinical trials for three separate 
indications: (1) prevention of stroke and systemic embolism among patients with atrial 
fibrillation; (2) prevention of deep venous thrombosis (DVT) among patients undergoing hip 
or knee replacement therapy; and (3) treatment of venous thromboembolism (VTE). Phase III 
clinical trials comparing dabigatran, rivaroxaban, apixaban, and edoxaban to warfarin in 
patients with non-valvular atrial fibrillation (NVAF) have been completed. [R11-4190] [P09-
11669] [R11-4223] [R13-5082] The objective of this part of the project is to conduct a series 
of comparative effectiveness and safety studies across the available anticoagulants, starting 
with warfarin and dabigatran and including additional ones as they become available within 
data sources available to us at the Division of Pharmacoepidemiology.  Such sequential 
approach will extend Phase I analyses (study protocol 1160.157) by providing greater 
precision around effect estimates as well as providing an evaluation of their use in actual 
practice and among subgroups of patients that were not represented in clinical trials.  This 
evaluation will provide a direct assessment of comparative effectiveness and potential 
adverse events across the anticoagulants that may have eluded the pre-marketing trials.  

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6.
RESEARCH QUESTIONS AND OBJECTIVES
This protocol is for a series of comparative effectiveness and safety analyses within 
periodically updated cohorts of patients with NVAF at risk for stroke initiating dabigatran or 
other oral NOAC medications as they become available, compared to warfarin, followed 
longitudinally for the occurrence of a variety of health outcomes.
Specific objectives of this active surveillance program are: 
1) Primarily, to conduct direct comparisons over time between dabigatran and warfarin and 
quantify the association between anticoagulant choice and the occurrence of specific 
outcomes of interest
2) Secondarily, to monitor the number of people initiating other NOAC medications as 
they become available and, when sufficient, to compare study outcomes between other 
NOAC medications and warfarin.

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7.
RESEARCH METHODS
7.1
STUDY DESIGN
This study will involve a sequentially built parallel cohort design with propensity score (PS) 
matching to address potential confounding. Each new data update will provide additional 
follow-up time on the patients already in the cohort, as well as new initiators who will be 
matched on PS and calendar quarter of initiation and added to the existing cohort for the 
cumulative analyses. This study design was selected to facilitate the inclusion of additional 
subjects and follow-up time as data become available over the course of the study period.
The study will be conducted within two US-based longitudinal healthcare claims databases 
(MarketScan and UnitedHealth Research Database, see also section 6.5 for more details). 
Cohort selection and all analyses will be performed separately within each database and a 
combined analysis that pools results from the two databases for the same time periods will be 
done if appropriate, based on an assessment of homogeneity of treatment effect.  Pooling of 
results across data sources will correspond to a weighted average effect (as in a fixed effects 
meta-analysis) using the Mantel-Haenszel method. [R97-0509] It is expected that there will 
be little heterogeneity of treatment effects across the databases since the databases are similar 
with respect to who is included in the database (employed people and their dependents) and 
the nature of data captured (health insurance transactions billed on a negotiated fee for 
service basis). Heterogeneity will be assessed by comparing the treatment effect point 
estimates across data sources. Assessment of heterogeneity will not rely on a statistical test of 
heterogeneity, since the large study size may indicate significant heterogeneity (p<0.05) even 
if estimates are similar (i.e. a difference that is not clinically meaningful) and the purpose of 
this assessment of heterogeneity is intended only for determining whether it is reasonable to 
combine data sources. If contrary to expectations, there is a difference >30% in the overall 
effect measure for a primary outcome across the two data sources, we will conduct an 
additional investigation that assesses treatment effect within levels of protocol-specified 
subgroups (Section 6.9.2) separately by a database. If treatment effect is different across 
levels of the subgroup variable within a data source, and the distribution of this subgroup 
variable differs by data source, then the pooling will be conducted within strata of the 
subgroup variable or variables across which heterogeneity is observed to account for this 
heterogeneity. 
The primary analyses will involve dabigatran initiators compared to warfarin initiators; as 
other NOAC medications become available for stroke prevention, we will form additional 
cohorts of other NOAC medications and separately compare them to warfarin in the 
secondary analyses once sufficient number of initiators will have accrued. The same (as 
described below for dabigatran) inclusion/exclusion criteria will apply and a similar set of 
analyses will be conducted.

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7.2
SETTING
Initiators of dabigatran and warfarin from two US data sources: (1) UnitedHealth Research 
Database and (2) MarketScan Commercial Claims and Encounters database and Medicare 
supplement between October 2010 and December 2012, with 6-month updates through 
December 2015. Initiators of other NOAC medications will be added as these medications 
become available for stroke prevention in NVAF. Data from July 2008 through September 
2010 will be used for disease risk score (DRS) calculation.
 
 
 
 
 
 
 
 
 
7.3
SUBJECTS
Patient Selection:

The main cohort will consist of patients with NVAF at risk for stroke initiating an oral 
anticoagulant medication in the timeframe of the study
-
warfarin and dabigatran for the primary analysis
-
other NOACs to be added separately in the secondary analysis as they become 
available for stroke prevention in later time intervals

Warfarin initiators between January 2009 and September 2010 will be used for 
estimation of disease risk scores.  
Inclusion criteria: 

Initiation of an oral anticoagulant is defined by a dispensing of an anticoagulant 
medication (warfarin or a NOAC medication) in the source data, with no dispensing 
of any oral anticoagulant in the prior 12 months. The date of that dispensing will be 
defined as the index date for that initiation.

At least one ICD-9 diagnosis code of 427.31 (atrial fibrillation) at any time prior to 
and including the index date 

At least 12 months (365 days) continuous enrollment, defined as ≤32 days enrollment 
gap using enrollment and disenrollment dates, preceding the index date 

18 years of age and older at index date

CHA2DS2-VASc score ≥ 1
Exclusion criteria: 

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
Patients with missing or ambiguous age or sex information

Patients with a nursing home stay during baseline

Patients with a dispensing of any oral anticoagulant during the 12 months preceding 
and including the index date

Patients with documented evidence of valvular disease defined as at least 1 inpatient 
or outpatient ICD-9 Dx code of [R11-4334]
394.x (diseases of mitral valve)
395.x (diseases of aortic valve)
396.x (diseases of mitral and aortic valve)
397.x (diseases of other endocardial structures)
398.9x (other and unspecified rheumatic heart diseases)
V42.2 (heart valve replaced by transplant)
V43.3 (heart valve replaced by a mechanical device/prosthesis)
OR 
ICD-9 procedure code 35.1x (open heart valvuloplasty without replacement), 35.2x 
(replacement of heart valve) [R03-1232]
OR 
one of the following CPT codes:
33660-33665 (atrioventricular valve repair)
33400-33403 (aortic valve valvuloplasty)
33420-33430 (mitral valve repair/valvuloplasty/replacement)
33460 (valvectomy, tricuspid valve, with cardiopulmonary bypass)
33463-33468 (tricuspid valve repair/valvuloplasty/replacement)
33475 (replacement, pulmonary valve)
33496 (prosthetic valve dysfunction repair)
0257T (implantation of catheter-delivered prosthetic aortic heart valve; open thoracic 
approach)
0258T (transthoracic cardiac exposure for catheter-delivered aortic valve replacement; 
without cardiopulmonary bypass)
0259T (transthoracic cardiac exposure for catheter-delivered aortic valve replacement; 
with cardiopulmonary bypass)
0262T (implantation of catheter-delivered prosthetic pulmonary valve, endovascular 
approach)
at any time prior to and including the index date.
We will balance baseline covariates among patients initiating each drug by means of a 
multivariate confounder summary score (by matching on the exposure propensity score, with 
confounder balance assessed by the disease risk score). [R12-1912]
Cohort formation
We will receive new data as they become available on a periodic basis (every 6 months) and 
we will update the study cohorts through December 2015. Initiators of oral anticoagulants
identified in each data cut, as previously described, will form sequential cohorts.  

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In each sequential cohort we will balance baseline covariates among patients initiating each 
drug by matching on the exposure propensity score and calendar quarter of initiation. 
Patients’ follow-up will end when there is a treatment gap of ≥14 days from the end of 
calculated days supplied. Patients will be allowed to contribute only once.
Figure 1
Patient Selection Flow 
7.4
VARIABLES
7.4.1
EXPOSURES
Table 1
Market availability for the treatments of interest
United Data and MarketScan data:
Oct 2010– Dec 2012(initial cohort)
Dec 2012 – Dec 2015 (subsequent cohorts)
Include:
• Atrial fibrillation
• Initiation of anticoagulant medication
• CHA2DS2-VASc score ≥ 1
Exclude:
• <12 Months enrollment before 
1st dispensing
• Missing or ambiguous age or sex
• Valvular disease
• Use of any oral anticoagulant 
during the prior 12 months
• Nursing home stay
Patients are eligible 
for cohort re-entry
PS-Matching
Balanced study 
cohort
Not
matched
Successfully
matched
Class
Drug
FDA approved*
FDA approved for stroke prevention in 
patients with non-valvular atrial 
fibrillation at risk for stroke
Direct 
thrombin 
inhibitors
Dabigatran
19 October 2010
19 October 2010
Direct Xa 
inhibitors
Rivaroxaban
1 July 2011
4 November 2011
Apixaban
28 December 2012
28 December 2012

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Table 1 (con’t) 
Market availability for the treatments of interest
*as of December2013
The primary contrast of interest is between new initiators of warfarin and new initiators of 
dabigatran, defined as no anticoagulation with any oral anticoagulant in the 12 months 
before the index prescription.
In the secondary analysis and as they become available for stroke prevention in NVAF 
patients, other NOAC medications will be compared to warfarin. The same definitions and 
inclusion/exclusion criteria will be applied.
Concomitant therapy with medications that are not cohort-defining medications (defined as 
simultaneous use on the day of dabigatran or warfarin initiation) will be accounted for in the
study analyses as a covariate and used for balancing or stratification.  
Study follow-up
We will follow patients for each of the outcomes of interest in a prospective manner and we 
will estimate measures of effect using person-time based analyses.  
The primary analyses will use an ‘as treated’ approach.  Follow-up will start the day after 
cohort inclusion, which is the day of treatment initiation, and will end at the time of 
disenrollment, end of the observation period (available data), death, admission to a nursing 
home, discontinuation of the index study exposure, or switch to a different anticoagulant 
whichever comes first.  Exposure will be considered discontinued if there is a treatment gap 
≥14 days from the end of calculated days supplied. Warfarin therapy involves dose titration 
following initiation before a stable therapeutic INR is obtained. We will use the reported 
days’ supply as a proxy for duration of exposure following a dispensing as it may more 
adequately reflect the use pattern within a commercial health insurer database represented by 
UnitedHealth and MarketScan. This approach involves a potential mismatch between the 
presumed exposure derived from dispensing data and actual exposure.  The utilization study 
(described in study protocol 1160.177) will inform the sensitivity analyses around this 
assumption and seek to clarify how sensitive results are to variations in the exposure 
assumption. Switchers will be censored in the as-treated approach on the day of the 
dispensing of the alternative medication. If switching was the consequence of a side effect of 
a drug, most likely the index drug was discontinued for some time before the new drug was 
initiated. Any clinical event therefore was most likely recorded during that period and will be 
Edoxaban
Phase III
N/A
Otamixaban
Phase III
N/A
Betrixaban
Phase II
N/A

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attributed to the index drug.
 
 
 
 
 
7.4.2
OUTCOME(S)
The primary outcomes of interest include stroke (hemorrhagic, ischemic, uncertain 
classification) and major bleeding. Secondary outcomes are: stroke or systemic embolism, , 
transient ischemic attack (TIA), myocardial infarction (MI), venous thromboembolism 
(VTE), deep vein thrombosis (DVT), pulmonary embolism (PE).
Systemic embolism (defined as an acute vascular occlusion of the extremities or any organ, 
such as kidneys, mesenteric arteries, spleen, retina or grafts), ischemic stroke, hemorrhagic 
stroke, stroke of uncertain classifications, major intracranial bleeding, major extracranial 
bleeding, major gastrointestinal (GI) bleeding, major upper GI bleeding, major lower GI 
bleeding, major urogenital bleeding, major other bleeding. Further outcomes include 
hepatotoxicity and all-cause mortality.   
As mortality data in the commercial databases is currently limited to inpatient deaths, we will 
seek to improve the ascertainment of the death outcome through external linkage, such as 
with the Social Security Death Master File.
Table 2
Outcome Definitions
Outcome
Hospital Discharge Code(s)
Comments
Primary Outcomes
Stroke
As primary ICD-9 discharge diagnosis (Dx):
431.x  Intracerebral hemorrhage (ICH)
433.x1  Occlusion and stenosis of precerebral arteries with 
cerebral infarction
434.x1  Occlusion and stenosis of cerebral arteries with 
cerebral infarction
436.x  Acute, but ill-defined cerebrovascular events
See Mini-Sentinel report 
for PPV for individual 
codes or other algorithms
[R14-0052]
Major 
hemorrhage
Major intracranial bleeding, major extracranial bleed
(for codes see component outcomes below)
Secondary outcomes
Stroke or 
systemic 
embolism
Stroke or systemic embolism (for codes see component
outcomes below)

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Table 2 (con’t)
Outcome Definitions
Outcome
Hospital Discharge Code(s)
Comments
Systemic 
embolism
ICD-9 Diagnoses:
  444.x    Arterial embolism
No validation studies 
available. Codes are 
thought to be specific 
because of the 
substantial clinical 
symptomatic and 
required therapy. 

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Table 2 (con’t)
Outcome Definitions
Ischemic stroke
As primary ICD-9 discharge diagnosis (Dx):
ICD-9 Dx 433.x1  Occlusion and stenosis of precerebral 
arteries with cerebral infarction
ICD-9 Dx 434.x1  Occlusion and stenosis of cerebral 
arteries with cerebral infarction
PPV 95.5% in 
commercially-insured 
population for the 
codes in any position
[R11-4887]
Use of codes in the 
primary position 
generally increases the 
PPVs [R14-0052]
Hemorrhagic 
stroke
As primary ICD-9 discharge diagnosis (Dx):
431.x  Intracerebral hemorrhage (ICH)
Median PPV 96% 
(86% if all discharge 
diagnoses) for ICH 
based on 2 validation 
studies [R14-0052]
Stroke 
uncertain 
classification
As primary ICD-9 discharge diagnosis (Dx):
ICD-9 Dx code 436.x (acute, but ill-defined 
cerebrovascular disease)
Mini-Sentinel report: 
Median PPV of 81% 
for the code of 436
[R14-0052]
Transient 
Ischemic 
Attack (TIA)
ICD-9 Dx code 435.xx (transient cerebral ischemia) as 
the principal (primary) discharge diagnosis
PPV of 89% (primary 
Dx) and 77% (primary 
and secondary) in 1992 
study [R13-0519] and 
70% (primary only in 
Canadian database) 
[R13-0520] have been 
reported.
Median PPV is 79% 
(72 if all discharge Dx)
[R14-0052]
Myocardial 
infarction (MI)
ICD-9 Dx 410.X (acute myocardial infarction) 
excluding 410.x2 (subsequent episode of care), as the 
principal (primary) or the next (secondary) diagnosis
AND 
a length of stay (LOS) between 3-180 days, or death if 
LOS is < 3 days
PPV 94% in Medicare 
claims data [R11-4316]
PPV 88.4% in 
commercially-insured 
population [R11-4887]
Venous 
Thromboembol
ism (VTE)
DVT or PE (for codes see component outcomes below)

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Table 2 (con’t)
Outcome Definitions
Deep vein 
thrombosis 
(DVT)
Validated algorithm:
ICD-9 451.1x  (Phlebitis and thrombophlebitis of deep
vessels of lower extremities)
ICD-9 451.2x (of lower extremities, unspecified)
ICD-9 451.81 (of Iliac vein)
ICD-9 451.9x  (of unspecified site)
ICD-9 453.1x  (thrombophlebitis migrans)
ICD-9 453.2x ( venous embolism and thrombosis of 
vena cava)
ICD-9 453.8x (venous embolism and thrombosis of 
other specified veins)
ICD-9 453.9x (venous embolism and thrombosis of 
unspecified site)
Not in the validated algorithm but will be included 
following Mini-Sentinel recommendation for VTE 
outcome:
ICD-9 453.40 (Venous embolism and thrombosis of 
unspecified deep vessels of lower extremity (includes 
DVT)
ICD-9 453.41 (Venous embolism and thrombosis of 
deep vessels of proximal lower extremity (includes 
femoral, iliac, popliteal, thigh, and upper leg)
ICD-9 453.42 (Venous embolism and thrombosis of 
deep vessels of distal lower extremity (includes calf, 
lower leg, peroneal, and tibia)
ICD-9 453.0 (Hepatic vein thrombosis)
Algorithm for Deep 
vein thrombosis 
(DVT): ICD-9 codes of 
451.1, 451.2, 451.81, 
451.9, 453.1, 453.2, 
453.8, 453.9 [hospital 
discharge, any 
position] had PPV of 
0.72 and specificity > 
0.99 in Medicare 
population [R11-4334]
Mini-Sentinel: while 
using ICD-9 codes 
415.x (PE), 451.x and 
453.x (DVT) as a VTE 
event yielded the 
highest PPV, for a 
specific event (DVT or 
PE) PPV was lower; 
therefore, the 
performance of 
algorithms depends on 
a population studied
[R13-0522]
Pulmonary 
Embolism (PE)
ICD-9 415.1x (pulmonary embolism and infarction)
PPV of 72% in a 
community sample (45 
YO and older) [R05-
0358]
Major 
intracranial 
bleeding
ICD-9 diagnosis:
430.x  (Subarachnoid hemorrhage (SAH))
431.x  (Intracerebral hemorrhage (ICH))
432.x (other and unspecified intracranial hemorrhage,  
including 432.1x – subdural hemorrhage)
PPV 77% or higher 
reported [R14-0052]
Major 
extracranial 
bleeding
Major upper GI bleed, major lower and unspecified GI 
bleed, major urogenital bleed, major other bleed (for codes 
see component outcomes below)
No validation studies 
available for this 
outcome
Major GI 
bleeding
Major upper GI bleeding, major lower/unspecified GI 
bleeding (for codes see component outcomes below)
No validation studies 
available for this 
outcome

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Table 2 (con’t)
Outcome Definitions
Major upper 
GI bleed 
ICD-9 diagnoses: 
531.0x (acute gastric ulcer with hemorrhage with/without 
obstruction)
531.2x (with hemorrhage and perforation with/without 
obstruction)
531.4x (chronic or unspecified gastric ulcer with hemorrhage 
with/without obstruction)
531.6x (with hemorrhage and perforation with/without 
obstruction)
532.0x (acute duodenal ulcer with hemorrhage with/without 
obstruction)
532.2x (with hemorrhage and perforation with/without 
obstruction)
532.4x (chronic or unspecified duodenal ulcer with 
hemorrhage with/without obstruction)
532.6x (with hemorrhage and perforation with/without 
obstruction)
533.0x (acute peptic ulcer of unspecified site with 
hemorrhage with/without obstruction)
533.2x (with hemorrhage and perforation with/without 
obstruction)
533.4x (chronic or unspecified peptic ulcer of unspecified site 
with hemorrhage with/without obstruction)
533.6x (with hemorrhage and perforation with/without 
obstruction), 
534.0x (acute gastrojejunal ulcer with hemorrhage 
with/without obstruction)
534.2x (with hemorrhage and perforation with/without 
obstruction)
534.4x (chronic or unspecified gastrojejunal ulcer with 
hemorrhage with/without obstruction)
534.6x (with hemorrhage and perforation with/without 
obstruction)
578.0 (hematemesis) OR
ICD-9 procedure code 44.43 (endoscopic control of gastric or 
duodenal bleeding) OR
CPT code 43255 (upper gastrointestinal endoscopy including 
esophagus, stomach, and either the duodenum and/or jejunum 
as appropriate with control of bleeding, any method)
PPV of 87.8% in 
commercially-insured 
population [R11-4887]
Major lower 
GI bleeding
Lower GI/unspecified GI site bleeds [R11-2274]:
Diverticulosis of small intestine with hemorrhage: 
562.02
Diverticulitis of small intestine with hemorrhage: 
562.03
Diverticulosis of colon with hemorrhage: 562.12
Diverticulitis of colon with hemorrhage: 562.13
Hemorrhage of rectum and anus: 569.3x
Angiodysplasia of intestine with hemorrhage: 569.85
Blood in stool: 578.1x
Hemorrhage of GI tract, unspecified: 578.9
PPVs for individual 
codes [R11-2274]:
562.12 – 91.7%
562.13 – 66.7% 
569.3 - 71.4%
569.85 – 100%
578.1 -  81.8%
578.9 -88.2%

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Table 2 (con’t)
Outcome Definitions
Major 
urogenital 
bleed
ICD-9 diagnoses:
Hematuria: ICD-9 Dx: 599.7 
Excessive/frequent menstruation: ICD-9 Dx  626.2x and
secondary diagnosis indicating acute bleeding: anemia 
(280.0, 285.1, 285.9), [R11-2274]
PPVs for individual 
codes [R11-2274]:
599.7 -  75.0%
626.2 – 100% (2 cases)
[R11-2274]
Other major 
bleeds
Other major bleeds [R11-2274]:
Hemathrosis: 719.1x
Hemopericardium: 423.0x
Hemoptysis: 786.3x
Epistaxis: 784.7x
Hemorrhage not specified 459.0x
Acute posthemorrhagic anemia 285.1x
PPVs for individual 
codes [R11-2274]:
719.1x – 100%
786.3x – 80%
784.7x – 100%
459.0x – 100%
285.1x – 100%
 
 
 
 
 
 

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7.5
DATA SOURCES
The data source for this project will be a combination of claims data from United Healthcare, 
a large national commercial health insurer, and MarketScan, a research claims database from 
commercial employer-sponsored health plans from July 2008 through December 2012 for the 
first interim report, with 6-month updates through December 2015. Data from July 2008 
through September 2010 will be used for DRS estimation (see Main Analysis Section (6.9.1) 
for more details) while data from October 2010 will be used for cohort formation and 
analysis. Because of a 6-month time lag before data become available for United and 9-
month time lag for MarketScan, we will not have access to any information beyond 
December 2012 for the first interim report. 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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
 
 
 
 
 
 
 
 
We have obtained the following preliminary estimates from the UnitedHealth and 
MarketScan databases regarding the number of patients initiating dabigatran or warfarin (new 
users) and meeting the main study selection criteria in the period October 2010 – June 2012.
Table 7
UnitedHealth and MarketScan databases, estimated numbers of 
dabigatran and warfarin with non-valvular atrial fibrillation 
diagnosis, in the period October 2010 – June 2012
Medication
United Healthcare
MarketScan
Total
Dabigatran
4,150
20,000
24,150
Warfarin
7,720
40,000
47,720
7.6
BIAS
Various design and analysis methods will be implemented to reduce the potential for bias in 
the study.  We will employ new-user cohorts of NOAC medications and warfarin in order to 
address differences that might arise in the comparison of newer and older treatments, such as 
survivor bias and attrition of susceptibles.  The comparator cohort will be formed from 
warfarin initiators with similar clinical profiles to dabigatran and other NOAC medications 
initiators to reduce confounding by indication.  We will employ propensity score matching of 
NOAC/dabigatran and warfarin cohorts in order to improve the balance of the cohorts with 
respect to numerous variables and will further assess the balance across the matched cohorts 
on the basis of disease risk scores for the primary outcomes.  We will use established 

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algorithms for outcome identification and only outcomes expected to be ascertained well in 
insurance claims.
7.7
STUDY SIZE
The ability of this research program to detect a given risk increase depends on the incidence 
of the outcome as well as the number of cohort entrants and duration of follow-up. The study 
size will depend on the number of dabigatran (or other NOAC medications) and warfarin 
initiators who meet the study inclusion and exclusion criteria and are successfully matched 
into cohorts. On the basis of the outcome incidence rate observed in the comparison group in 
the pilot phase of this project (Phase 1)  and the cumulative person-time of observation over 
the study period, we estimated the minimum relative rate that can be detected with 80% 
power for dabigatran-warfarin comparison..  During the period October 2010 – June 2012, 
among patients with a minimum of 12 months baseline history, no prior use of any 
anticoagulants, and a diagnosis of non-valvular atrial fibrillation, there are 4,158 dabigatran 
incident users in the UnitedHealth database and approximately 20,000 dabigatran users in 
MarketScan database.  These dabigatran users will be matched to a similar number of 
warfarin incident users.  Assuming that approximately 70%  or patients will be matched, an 
average follow-up of 5 months (both based on the preliminary results from Phase 1 of the 
BI/
 Pradaxa project) and the additional users who initiated dabigatran during July-
December 2012 period, there should be slightly more 10,000  person-years of dabigatran 
follow-up for the initial analysis.  As this project expands in 6 month increments, the person-
time, along with outcomes and the ability to detect a particular relative risk will increase.
The table below provides estimates of the minimum relative rates that can be detected with 
80% power for the major study outcomes under specific assumptions regarding their 
incidence in the comparator group (labeled “base rate”) and the accrual of person-time.  The 
base case incidence rates are the rates observed in warfarin initiators who were calendar 
quarter- and PS- matched to dabigatran initiators during the October 2010-June 2012 period 
in the UnitedHealth database (Phase 1 of the project).  We conservatively assumed that the 
number of patients initiating dabigatran each month during July 2012 – December 2015 is 
equal to the average monthly number of initiators during the first half of 2012, that at least 
2/3 of these patients are matched 1:1 to comparator patients, and that each patient contributes 
0.41 years of follow-up time.
Table 8
Projected minimum detectable relative rates* by reporting period
Phase 1 
(NOAC 
Cohort)
Interim 
report 1
Interim 
report 2
Interim 
report 3
Interim 
report 4
Interim 
report 5
Interim 
report 6
Final 
report
Report Date
Apr, 
2014
Jul, 
2014
Nov, 
2014
Mar, 
2015
Sep, 
2015
Mar, 
2016
Dec, 
2016

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Table 8 (con’t) 
Projected minimum detectable relative rates* by reporting period
Data through
(MarketScan/
United)
Jun, 
2012
Dec, 
2012
Jun, 
2013
Sep/Dec, 
2013
Dec 
2013/Jun
, 2014
Sept/Dec, 
2014
Dec 
2014/Jun
, 2015
Dec, 
2015
Estimated 
number of 
matched 
patients
24,000
30,000
36,000
42,000
48,000
54,000
60,000
Cumulative 
person-time 
of 
observation
10,000
12,350
14,700
17,050
19,400
21,750
24,100
Outcome
Base 
rate †
Minimum detectable relative rate
Stroke
31.59
1.24
1.21
1.19
1.18
1.17
1.16
1.15
Major 
Hemorrhage
66.72
1.16
1.14
1.13
1.12
1.11
1.11
1.10
Ischemic 
stroke
32.71
1.23
1.21
1.19
1.17
1.16
1.15
1.15
Hemorrhagic 
stroke
2.09
1.87
1.77
1.70
1.64
1.60
1.56
1.53
MI
14.73
1.35
1.32
1.29
1.27
1.25
1.23
1.22
Major GI 
bleeding
31.63
1.24
1.21
1.19
1.18
1.17
1.16
1.15
Hepatotoxici
ty
4.20
1.70
1.62
1.57
1.52
1.49
1.46
1.43
* This table reports the minimum relative rate that can be detected with 80% power assuming 
an alpha level of 0.05 and a 2-sided test.  
† Base rate is incidence rate per 1,000 Person-Years observed in warfarin initiators matched 
to dabigatran during the October 2010-June 2012 period in the UnitedHealth database
 
 
 
 
 
 
 

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7.9
DATA ANALYSIS
All analysis will be performed with SAS Inc, Version 9.3.
7.9.1
MAIN ANALYSIS
All analyses will be conducted in both data sources and may be combined in pooled analyses 
if appropriate, based on homogeneity of treatment effect. Pooling of results across data 
sources will correspond to a weighted average effect (as in a fixed effects meta-analysis) 
using the Mantel-Haenszel method. [R97-0509] Heterogeneity will be assessed by comparing 
the treatment effect point estimates across data sources. If there is a difference >30% in the 
overall effect measure for a primary outcome across the two data sources, we will conduct an 
additional investigation that assesses treatment effect within levels of protocol-specified 
subgroups (Section 6.9.2) separately by a database. If treatment effect is different across 
levels of the subgroup variable within a data source, and the distribution of this subgroup 
variable differs by data source, then the pooling will be conducted within strata of the 
subgroup variable or variables across which heterogeneity is observed to account for this 
heterogeneity (see Section 6.2 for more details). In each data source, we will compare 
distributions of socio-demographic, clinical and utilization characteristics among initiators of 
different anticoagulant agents, and calculate event rates during follow-up for each of the 
specified outcomes.  
Unadjusted and adjusted relative risks (hazard ratios) and rate differences will be estimated. 
In adjusted analyses, we will use propensity score (PS) matching to balance potential 
confounders. [R13-1120] [R12-1912] PS will be derived from predicted probabilities of 
treatment initiation, given all measured covariates. We will estimate the primary propensity 
score for each patient using a logistic regression model that includes all pre-defined 
covariates (from Section 6.4.3). The propensity score will be used to match dabigatran
initiators to initiators of warfarin on a 1:1 fixed ratio basis using a nearest-neighbor algorithm
and a caliper of 0.05. In addition, patients will be matched on calendar quarter of initiation.
Individual covariates will be further tabulated and compared across matched cohorts. If 
substantial covariate imbalance between dabigatran and warfarin is noted as assessed by a 
standardized difference >0.1, then we will further adjust the outcome models for HAS-BLED 
and CHA2DS2-VASc score as Cohort Phase 1 results indicated that these scores include all 
the variables typically imbalanced.
 
 

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We will plot post-PS-matching Kaplan-Meier curves for event-free survival as a function of 
the duration of use of the index anticoagulant agent to evaluate the proportionality of hazards. 
 
 
 
  
 
 
 
 
 

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The secondary analyses will involve other NOAC medications as compared to warfarin.  
Other NOACs will include rivaroxaban, apixaban and others once they become available for 
stroke prevention in NVAF patients. We will monitor the number of patients initiating other 
NOACs and provide these numbers along with power calculations for primary outcomes at 
each interim report. Once sufficient numbers have accrued, and sufficient follow up time is 
available, these other NOAC initiators will be separately matched to warfarin initiators and 
primary analyses (and further/sensitivity analyses if numbers allow) as described above for 
dabigatran-warfarin comparison will be done. 

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7.10
QUALITY CONTROL
All aspects of data analysis will be conducted according to standard procedures of the 
Division of Pharmacoepidemiology. Programming for this project will be conducted by a 
primary analyst and validated by a separate analyst (validation analyst).  For all data 
processing and analysis steps, the validation analyst will review the program along with input 
and output data sets, and for select steps of the project will employ double programming 
techniques to reduce the potential for programming errors.
7.11
LIMITATIONS OF THE RESEARCH METHODS
As an observational study, there are inherent limitations with respect to potential for alternate 
explanations for any observed association.
The source claims data include limitations with respect to certainty of capture of exposure, 
covariates, and outcomes.  As a comprehensive insurance database, essentially all billable 
medical services will result in claims for reimbursement, so that certainty of capture is tied to 
likelihood of a claim being submitted to the insurer. 
Given the characteristics of the UnitedHealth data (commercial health insurer), patients older 
than 65 years will be under-represented in the data. Only approximately 35% of incident 
dabigatran users during the 2010-2011 period were 65 years of age and older. As NVAF also 
predominately affects older population, it will be under-represented in the data as well.
Although duration of atrial fibrillation may represent a risk factor for study outcomes, this 
covariate will be incompletely captured since the patient history in the dataset is relatively 
short (at least 6 months, and an average of approximately 2 years), and a first claim within 
the database may not represent atrial fibrillation onset since the condition is typically not 
diagnosed at its onset. 
Dosing of warfarin in clinical practice is complicated, and estimating dose and duration of 
exposure based on healthcare utilization data is therefore challenging.  The “days’ supply” 
field is expected to be most meaningful, but the potential for misclassification exists.
There are a number of covariates, such as the type of atrial fibrillation, cause-specific 
mortality, BMI, smoking, that are not directly assessed in a health insurer database. 
Information on formulary and reimbursement is not available for MarketScan data.  Further, 
some covariates that can be directly assessed through diagnosis and procedure codes (such as 
renal dysfunction) have uncertain sensitivity, specificity, and predictive value. Estimation of 
creatinine clearance even in the subgroup of patients with laboratory values present is not 
feasible as information on height and weight is not available. A modified MDRD equation is 
going to be used (see Further Analysis section), which - although found to accurately 
estimate GFR from serum creatinine measurements - is not used for dosing. In our study, 
however, we will only use it to assess balance between exposure cohorts. 
In addition, medication use in United Healthcare data and MarketScan data - as in all 
administrative healthcare databases - is restricted to prescription drug medication. 

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Consequently, the use of over-the-counter (OTC) medications (e.g., OTC aspirin) is not 
captured. In addition, exposure is assessed based on prescription pick-up at a pharmacy and 
might be misclassified in “as treated” analysis if patients do not take their medications. 
However, misclassification of prescription drug exposure is generally considered less than in 
other exposure assessment approaches, including physician prescribing records and patient 
self-reporting. [P13-03077] [P13-03078]
7.12
OTHER ASPECTS 
Any other aspect of the research method not covered by the previous sections.

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8.
PROTECTION OF HUMAN SUBJECTS
Data analysis personnel will have access to patients protected health information (PHI) while 
linking databases and constructing study variables.  After data linkage and variable 
construction is completed, the subjects' PHI will be deleted from the study database, therefore 
posing minimal risk to patients' privacy.
This study will be submitted to the Institutional Review Board (IRB) of the
 
.
.

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9.
MANAGEMENT AND REPORTING OF ADVERSE 
EVENTS/ADVERSE REACTIONS
This will be a retrospective observational study; all patient data will be de-identified and 
analyzed in aggregate. Individual patient safety related information will not be captured 
during this study. Thus, individual safety reporting is not applicable for this study.

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10.
PLANS FOR DISSEMINATING AND COMMUNICATING 
STUDY RESULTS
The interim and final reports will consist of a description of the methods, including patient 
selection and variable definitions along with tabular summaries of cohort characteristics, 
numbers of patients receiving each anticoagulant and associated follow-up time.  Counts of 
outcomes and corresponding rates and measures of association will be presented. The tabular 
results will be followed by an interpretive summary along with a discussion of the findings 
and implications.
The scheduling of communication of interim results will be specified in a separate document. 
Manuscripts describing this work will be submitted for publication in peer-review journals. 
Findings may also be submitted for presentation at scientific conferences.

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11.
REFERENCES
P06-10925
Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford 
MJ. Validation of clinical classification schemes for predicting stroke: 
results from the National Registry of Atrial Fibrillation. JAMA 
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P08-02098
Myers RP, Leung Y, Shaheen AA, Li B. Validation of ICD-9-CM/ICD-
10 coding algorithms for the identification of patients with 
acetaminophen overdose and hepatotoxicity using administrative data. 
BMC Health Serv Res 2007;7:159.
P09-11669
Connolly SJ, Ezekowitz MD, Yusuf S, et al. Dabigatran versus warfarin 
in patients with atrial fibrillation. N Engl J Med 2009;361:1139-51.
P11-11875
Potpara TS, Lip GY. New anticoagulation drugs for atrial fibrillation. 
Clin Pharmacol Ther 2011;90:502-6.
P12-01676
You JJ, Singer DE, Howard PA, et al. Antithrombotic therapy for atrial 
fibrillation: Antithrombotic Therapy and Prevention of Thrombosis, 9th 
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Practice Guidelines. Chest 2012;141:e531S-75S.
P12-05791
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uidances/UCM292362.pdf.)
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Rassen JA, Glynn RJ, Rothman KJ, Setoguchi S, Schneeweiss S. 
Applying propensity scores estimated in a full cohort to adjust for 
confounding in subgroup analyses. Pharmacoepidemiol Drug Saf 
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P12-11192
Camm AJ, Lip GY, De Caterina R, et al. 2012 focused update of the ESC 
Guidelines for the management of atrial fibrillation: An update of the 
2010 ESC Guidelines for the management of atrial fibrillation * 
Developed with the special contribution of the European Heart Rhythm 
Association. Europace 2012;14:1385-413.
P13-03077
West SL, Strom BL, Freundlich B, Normand E, Koch G, Savitz DA. 
Completeness of prescription recording in outpatient medical records 
from a health maintenance organization. J Clin Epidemiol 1994;47:165-
71.
P13-03078
West SL, Savitz DA, Koch G, Strom BL, Guess HA, Hartzema A. Recall 
accuracy for prescription medications: self-report compared with 
database information. Am J Epidemiol 1995;142:1103-12.
R03-1232
Go AS, Hylek EM, Borowsky LH, Phillips KA, Selby JV, Singer DE. 
Warfarin use among ambulatory patients with nonvalvular atrial 

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fibrillation: the anticoagulation and risk factors in atrial fibrillation 
(ATRIA) study. Ann Intern Med 1999;131:927-34.
R05-0358
Cushman M, Tsai AW, White RH, et al. Deep vein thrombosis and 
pulmonary embolism in two cohorts: the longitudinal investigation of 
thromboembolism etiology. Am J Med 2004;117:19-25.
R10-5332
Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical 
risk stratification for predicting stroke and thromboembolism in atrial 
fibrillation using a novel risk factor-based approach: the euro heart 
survey on atrial fibrillation. Chest 2010;137:263-72.
R10-6394
Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJ, Lip GY. A 
novel user-friendly score (HAS-BLED) to assess 1-year risk of major 
bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest 
2010;138:1093-100.
R11-2274
Cunningham A, Stein CM, Chung CP, Daugherty JR, Smalley WE, Ray 
WA. An automated database case definition for serious bleeding related 
to oral anticoagulant use. Pharmacoepidemiol Drug Saf 2011;20:560-6.
R11-4190
Granger CB, Alexander JH, McMurray JJ, et al. Apixaban versus 
warfarin in patients with atrial fibrillation. N Engl J Med 2011;365:981-
92.
R11-4223
Patel MR, Mahaffey KW, Garg J, et al. Rivaroxaban versus warfarin in 
nonvalvular atrial fibrillation. N Engl J Med 2011;365:883-91.
R11-4316
Kiyota Y, Schneeweiss S, Glynn RJ, Cannuscio CC, Avorn J, Solomon 
DH. Accuracy of Medicare claims-based diagnosis of acute myocardial 
infarction: estimating positive predictive value on the basis of review of 
hospital records. Am Heart J 2004;148:99-104.
R11-4329
Winkelmayer WC, Schneeweiss S, Mogun H, Patrick AR, Avorn J, 
Solomon DH. Identification of individuals with CKD from Medicare 
claims data: a validation study. Am J Kidney Dis 2005;46:225-32.
R11-4334
Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, 
Gage BF. Accuracy of ICD-9-CM codes for identifying cardiovascular 
and stroke risk factors. Med Care 2005;43:480-5.
R11-4887
Wahl PM, Rodgers K, Schneeweiss S, et al. Validation of claims-based 
diagnostic and procedure codes for cardiovascular and gastrointestinal 
serious adverse events in a commercially-insured population. 
Pharmacoepidemiol Drug Saf 2010;19:596-603.
R12-0541
Friberg L, Rosenqvist M, Lip GY. Evaluation of risk stratification 
schemes for ischaemic stroke and bleeding in 182 678 patients with atrial 
fibrillation: the Swedish Atrial Fibrillation cohort study. Eur Heart J 
2012;33:1500-10.
R12-1912
Rosenbaum PR, Rubin DB. The central rol of the propensity score in 
observational studies for causal effects. Biometrica 1983:41-55.

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R12-1912
Rosenbaum PR, Rubin DB. The central role of the propensity score in 
observational studies for causal effects. Biometrica 1983:41-55.
R13-0519
Benesch C, Witter DM, Jr., Wilder AL, Duncan PW, Samsa GP, Matchar 
DB. Inaccuracy of the International Classification of Diseases (ICD-9-
CM) in identifying the diagnosis of ischemic cerebrovascular disease. 
Neurology 1997;49:660-4.
R13-0520
Kokotailo RA, Hill MD. Coding of stroke and stroke risk factors using 
international classification of diseases, revisions 9 and 10. Stroke 
2005;36:1776-81.
R13-0521
Molnar AO, Coca SG, Devereaux PJ, et al. Statin use associates with a 
lower incidence of acute kidney injury after major elective surgery. J Am 
Soc Nephrol 2011;22:939-46.
R13-0522
Tamariz L, Harkins T, Nair V. A systematic review of validated methods 
for identifying venous thromboembolism using administrative and claims 
data. Pharmacoepidemiol Drug Saf 2012;21 Suppl 1:154-62.
R13-0523
Glynn RJ, Gagne JJ, Schneeweiss S. Role of disease risk scores in 
comparative effectiveness research with emerging therapies. 
Pharmacoepidemiol Drug Saf 2012;21 Suppl 2:138-47.
R13-0524
Hansen B. The prognostic analogue of the propensity score. Biometrika 
2008;95:481-8.
R13-0525
Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart 
MA. High-dimensional propensity score adjustment in studies of 
treatment effects using health care claims data. Epidemiology 
2009;20:512-22.
R13-0526
Huybrechts KF, Rothman KJ, Silliman RA, Brookhart MA, Schneeweiss 
S. Risk of death and hospital admission for major medical events after 
initiation of psychotropic medications in older adults admitted to nursing 
homes. CMAJ 2011;183:E411-9.
R13-0527
Rassen JA, Schneeweiss S. Using high-dimensional propensity scores to 
automate confounding control in a distributed medical product safety 
surveillance system. Pharmacoepidemiol Drug Saf 2012;21 Suppl 1:41-9.
R13-0528
Patorno E, Bohn RL, Wahl PM, et al. Anticonvulsant medications and the 
risk of suicide, attempted suicide, or violent death. JAMA 
2010;303:1401-9.
R13-0540
Rule AD, Larson TS, Bergstralh EJ, Slezak JM, Jacobsen SJ, Cosio FG. 
Using serum creatinine to estimate glomerular filtration rate: accuracy in 
good health and in chronic kidney disease. Ann Intern Med 
2004;141:929-37.
R13-1120
Schneeweiss S. A basic study design for expedited safety signal 
evaluation based on electronic healthcare data. Pharmacoepidemiol Drug 
Saf 2010;19:858-68.

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R13-4176
Olesen JB, Lip GY, Hansen PR, et al. Bleeding risk in 'real world' 
patients with atrial fibrillation: comparison of two established bleeding 
prediction schemes in a nationwide cohort. J Thromb Haemost 
2011;9:1460-7.
R13-5082
Giugliano RP, Ruff CT, Braunwald E, et al. Edoxaban versus warfarin in 
patients with atrial fibrillation. N Engl J Med 2013;369:2093-104.
R14-0052
Andrade SE, Harrold LR, Tjia J, et al. A systematic review of validated 
methods for identifying cerebrovascular accident or transient ischemic 
attack using administrative data. Pharmacoepidemiol Drug Saf 2012;21 
Suppl 1:100-28.
R96-0690
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum 
creatinine. Nephron 1976;16:31-41.
R97-0509
Mantel N, Haenszel W. Statistical aspects of the analysis of data from 
retrospective studies of disease. Journal of the National Cancer Institute 
1959;22:719-48.
12.
FUNDING
Boehringer Ingelheim GmbH

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13.
ANNEX
ANNEX 1: LIST OF STAND-ALONE DOCUMENTS
None 
 
 
                                           
                                           
                                           
                                           
 
                                           
                                           
                                           
                                           
                                           
                                           
                                           
                                           
 
                                           
                                           
                                           
                                           
                                           
                                           
                                           
                                           
                                           

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Table A3 Follow-up and outcomes among matched cohorts
Group
Size 
Follow-up (P-Y)
Outcome events
Incidence Rate
HR
95% CI
Dabigatran
N
Warfarin
N
This table will be repeated for each of the outcomes

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Table A4 Follow-up and distribution of reasons for discontinuation
Group
Size
Follow-up (years)
Reasons for discontinuation (N, %)
Mean
Median
Max
Discon
tinue 
Switch
Event
Disenro
llment
Death
Nursing 
home 
admission
Dabigatran
N
Warfarin
N
This table will be repeated for each of the outcomes.

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ANNEX 4  STUDY FIGURES
NOAC: New Oral Anticoagulant
Figure A1
Patient Selection Flow Diagram (CONSORT Style) 
This figure will be produced for each interim report and the final report
NOAC 
matched to 
warfarin
(N= ???)
United Health and 
MarketScan Data
(N= ???)
(N= ???)
Include: Patients 18 year of age and 
older with atrial fibrillation at risk for 
stroke AND a warfarin or dabigatran 
dispensing during the period Oct 2010-
Jun 2012
Exclude: Patients with <12 months prior 
to cohort entry, patients with use of any 
oral anticoagulant in the 12 months 
prior to cohort entry, patients with 
missing or ambiguous age or sex, 
patients with a nursing home stay 
during baseline, patients with evidence 
of valvular disease
NOAC
(N= ???)
Warfarin
(N= ???)
Warfarin 
matched to 
NOAC
(N= ???)

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Figure A2
Survival curves (time to event)
Separate figures to be created for each of the study outcomes. These figures will be produced 
for each interim report and the final report and displayed in the respective report. 

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APPROVAL / SIGNATURE PAGE 
 
Document Number: 
 
Version Number:
Document Name: 
 
 
 
                                                                                                                      
 
Title: 
 
 
 
 
                                                                                                                     
 
Signatures (obtained electronically) 
 
Meaning of Signature  
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Date Signed 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c02336230
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1160-0207-protocol
Sequential Expansion of Comparative Effectiveness of Oral Anticoagulants: A Cohort
Study
Approval-EU Qualified Person
Pharmacovigilance
25 Feb 2014 15:48 CET
Approval-Pharmacovigilance
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Author-Other
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Approval-
 Pharmacovigilance
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Affairs
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Completion
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Approval-Therapeutic Area 
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