The Effectiveness of Tiotropium Add-on Therapy Using a Real-world Cohort of Patients With Asthma
Conditions: Asthma
Sponsor: Boehringer Ingelheim

ABCD
001-MCS-90-124_RD-01 (4.0)
TITLE PAGE
Protocol for non-interventional studies based on existing data
TITLE PAGE
Document Number:
c28659325-01
BI Study Number:
0205-0543
BI Investigational
Product(s):
Tiotropium Bromide 1.25 mcq.
Title:
The effectiveness of Tiotropium Add-on therapy using a Real-
world cohort of patients with Asthma
Protocol version 
identifier:
V. 1.0
Date of last version of 
protocol:
Not applicable
PASS:
“No”
EU PAS register 
number:
“Study not registered” 
Active substance:
Tiotropium bromide 1.25 mcq.
Medicinal product:
  N/A       
Product reference:
N/A
Procedure number:
N/A
Joint PASS:
“No”
Research question and 
objectives:
To evaluate the effectiveness of add on therapy with Tiotropium 
Respimat® compared to increasing the dose of ICS in patients 
with a diagnosis of Asthma and on ICS/LABA therapy.
Country(-ies) of study:
U.S.A.
Author:
Marketing authorisation 
holder(s):
N/A
MAH contact person:
N/A
In case of PASS, add:
N/A

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<EU-QPPV:>
In case of PASS, add:
<Signature of EU-
QPPV:>
N/A
Date:
02/18/2019
Page 1 of 28
Proprietary confidential information
© 2020 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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1.
TABLE OF CONTENTS
TITLE PAGE.................................................................................................................. 1
1.
TABLE OF CONTENTS....................................................................................... 3
2.
LIST OF ABBREVIATIONS................................................................................ 5
3.
RESPONSIBLE PARTIES.................................................................................... 6
4.
ABSTRACT........................................................................................................... 7
5.
AMENDMENTS AND UPDATES....................................................................... 8
7.
RATIONALE AND BACKGROUND................................................................ 10
8.
RESEARCH QUESTION AND OBJECTIVES ................................................. 11
9.
RESEARCH METHODS .................................................................................... 12
9.1
STUDY DESIGN............................................................................................ 12
9.2
SETTING........................................................................................................ 13
9.3
VARIABLES .................................................................................................. 13
9.3.1
Exposures ................................................................................................ 13
9.3.2
Outcomes................................................................................................. 13
9.3.2.1
Primary outcomes..................................................................................13
9.3.2.2
Secondary outcomes..............................................................................13
9.3.3
Covariates................................................................................................ 14
9.4
DATA SOURCES........................................................................................... 16
9.5
STUDY SIZE.................................................................................................. 16
9.6
DATA MANAGEMENT................................................................................ 17
9.7
DATA ANALYSIS......................................................................................... 17
9.7.1
Main analysis........................................................................................... 17
9.8
QUALITY CONTROL................................................................................... 18
9.9
LIMITATIONS OF THE RESEARCH METHODS...................................... 18
9.10
OTHER ASPECTS ......................................................................................... 19
9.11
SUBJECTS...................................................................................................... 20
9.11.1
Cases........................................................................................................ 20
9.11.2
Controls................................................................................................... 20
9.12
BIAS................................................................................................................ 20
10.
PROTECTION OF HUMAN SUBJECTS .......................................................... 22

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11.
MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS....................................................................................................... 23
12.
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY 
RESULTS............................................................................................................ 24
13.
REFERENCES .................................................................................................... 25
13.1
PUBLISHED REFERENCES......................................................................... 25
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS.............................................. 26
ANNEX 2. ENCEPP CECKLIST FOR STUDY PROTOCOLS ................................. 27

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2.
LIST OF ABBREVIATIONS
CCI
Charlson Comorbidity Index
COPD
Chronic obstructive pulmonary disease
CTMF
Clinical Trial Master File
ACAAI
American College of Allergy, Asthma and Immunology
ACT
Asthma control test
ATS
American Thoracic Society
BI
Boehringer Ingelheim
EMR
Electronic Medical Records
EMA
European Medicines Agency
ERS
European Respiratory Society
FDA
Food and Drug Administration
GPV
Global Pharmacovigilance 
HCRU
Health Care Resource Utilization
HIPPA
Health Insurance Portability and Accountability Act
ICD
International Classification of Diseases 
ICS
Inhaled Corticosteroid 
LABA
  Long-acting beta-agonist 
LTRA
Leukotriene Receptor Antagonists
PSM
Propensity Score Matching

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3.
RESPONSIBLE PARTIES
Company
Personnel
Clinical advisors
 
BI

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4.
ABSTRACT
Name of company:
Boehringer Ingelheim
Name of finished medicinal product:
Spiriva Respimat 1.25 mcq
Name of active ingredient:
Tiotropium Bromide®   1.25 mcg
Protocol date:
Study number:
Version/Revision:
Version/Revision date:
18 Feb 2019
0205-0543
1
NA
Title of study:
The effectiveness of Tiotropium Add-on therapy using a Real-world cohort of 
patients with Asthma
Rationale and 
background:
While asthma imposes a substantial burden on the healthcare system, the cost 
of uncontrolled asthma is more than double that for controlled asthma 
patients. Asthma therapy involves a stepwise approach depending on control 
and severity levels. To better guide treatment decision making, it is imperative 
to understand the impact of different treatment choices on health outcomes in 
a real-world setting for patients taking ICS/LABA combinations.
Research question 
and objectives:
To evaluate the effectiveness of add on therapy with Tiotropium Respimat® 
compared to increasing the dose of ICS in patients with a diagnosis of Asthma 
and on ICS/LABA therapy.
Study design:
Retrospective cohort data analysis of patients with asthma prescribed with 
ICS/LABA therapy. Patients will be followed after the date of first 
ICS/LABA prescription and those prescribed Tiotropium Respimat® will be 
classified under the ‘Tio’ group while the rest will be under the ‘NonTio’ 
group. Outcomes will be compared between these two groups.
Population:
Asthmatics 6 years and above and on ICS/LABA at baseline
Variables:
Baseline measures will include patient demographics, medications, control 
status, comorbidities, resource use, eosinophil levels (if available), ACT score 
(if available).
Data sources:
IMS Pharmetrics (IMS or Database I);
EMRClaims+ (Database II)
Study size:
>6,300 (expected)
Data analysis:
Propensity Score Matching will be conducted using baseline characteristics in 
order to ensure as much similarity between the two groups. Time to first 
exacerbation (primary outcome) will be compared between the two groups 
descriptively, as well as using Cox PH modelling techniques. Secondary 
outcomes will include rate of exacerbation, proportion of patients with 
exacerbation, health care resource use and cost during follow-up,
 
Milestones:
Study protocol; Draft Results; Final Results

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5.
AMENDMENTS AND UPDATES
None

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7.
RATIONALE AND BACKGROUND
While asthma imposes a substantial burden on the healthcare system, the cost of uncontrolled 
asthma is more than double that for controlled asthma patients (ACAAI). The European 
National Health and Wellness Survey (P19-00715) and the Real-world Evaluation of Asthma 
Control and Treatment (US) (R16-0701) survey both found that 55% of asthma patients were 
uncontrolled, even among those who are treated. Asthma therapy involves a stepwise 
approach depending on control and severity levels. Uncontrolled asthma, which may present 
regardless of severity level, results in exacerbations, use of systemic corticosteroids, and 
declined lung function (P14-03600). When asthma is not controlled, guidelines recommend 
increased ICS dose, and use of ICS in combination with long-acting β2-agonists (LABA), 
and/or other add-on therapy, including leukotriene receptor antagonists (LTRA), antibody 
biologics or oral corticosteroids.  The ERS/ATS guidelines (P14-03600) define severe asthma 
as that which remains uncontrolled despite use of high dose ICS as well as controller 
medications or systemic corticosteroids. Uncontrolled asthma is associated with an increased 
risk of exacerbation, which results in impaired lung function, reduced patient quality of life 
and increased health care resource use. To better guide treatment decision making, it is 
imperative to understand the impact of different treatment choices on health outcomes in a 
real-world setting for patients taking ICS/LABA combinations.
The intended audience will be health systems, payers and prescribers. The results of the study 
will be used to provide evidence of the effectiveness of tiotropium as add-on therapy in 
reducing exacerbations, reducing the increased dosing of current medications and health care 
resource utilization for their asthma patients. 
In September 2015, the FDA approved Spiriva Respimat for Inhalation Spray for the long-
term, once-daily, maintenance treatment of asthma in patients 12 years of age and older (6 
years and above approved in Feb 2017).

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8.
RESEARCH QUESTION AND OBJECTIVES
To evaluate the effectiveness of add on therapy with Tiotropium Respimat® compared to 
increasing the dose of ICS in patients with a diagnosis of Asthma and on ICS/LABA therapy.

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9.
RESEARCH METHODS
9.1
STUDY DESIGN
Data extraction from both databases (I and II, see section 9.4) will be conducted by 
.  All patients will be required to have a prescription for ICS/LABA therapy [e.g. 
Advair (Diskus and HFA), Airduo, Breo, Dulera, or Symbicort]. The date of the first 
prescription of ICS/LABA within the study period (Jan 1st 2016 to Nov 30th 2018) will be 
defined as ICS/LABA-initiation (ICS/LABAi) date. This baseline cohort will then be 
followed to identify two cohorts (two arms of the study). One cohort that receives a 
prescription for Tiotropium Respimat®  1.25 mcg (on top of baseline ICS/LABA) will be 
classified as the ‘Tio’ group, and the second cohort that receives a “step-up” from baseline 
low-dose ICS/LABA to medium/high dose ICS/LABA or from baseline medium dose 
ICS/LABA to high dose ICS/LABA or an additional prescription/refill of high-dose-
ICS/LABA following the first prescription of baseline high dose ICS/LABA within the 
study period, will be classified as the ‘NonTio’ group. The date of the first prescription for 
Tiotropium Respimat®  1.25 mcg in the ‘Tio’ group will be defined as the index date for 
the ‘Tio’ group. Similarly the date of the first prescription for a “step-up” from baseline 
low-dose ICS/LABA to medium/high dose ICS/LABA or from baseline medium dose 
ICS/LABA to high dose ICS/LABA or an additional prescription/refill of high-dose-
ICS/LABA following the first prescription of baseline high dose ICS/LABA (evidenced by 
at least 90-days of prescription utilization) within the study period will be defined as the 
index date for the ‘NonTio’ group.
Patients will be required to have a minimum follow-up period of 30 days after the index 
date for the analyses of the primary endpoint with no limit on the maximum period  (this 
30-day minimum follow-up period requirement will be waived in a sensitivity analysis). 
Subject to sample size requirements, patients will be required to have available records for 
at least 12 months prior to the index date to ensure no prior use of Tiotropium Respimat®  
and to establish baseline patient characteristics.  This 12-month period prior to the index 
date will be defined as the pre-index period.  

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Figure 9.1.1  Study Design
9.2
SETTING
See section 9.11 below.
9.3
VARIABLES
9.3.1
Exposures
The exposure variables in this study include Tio initiation, and ICS/LABA dose increase or 
an additional prescription/refill of high-dose-ICS/LABA following the first prescription of 
baseline high dose ICS/LABA for at least 3 months.
9.3.2
Outcomes
9.3.2.1
Primary outcomes
(Datbase I/II combined)
The primary outcome measure is time to first exacerbation per person.
Exacerbations will be defined as either a hospitalization with a primary diagnosis of 
asthma, an ER visit with a primary diagnosis of asthma, an asthma exacerbation diagnosis 
recorded (ICD 493.02, 493.12, 493.22, 493.92, J45.21, J45.31, J45.41, J45.51, J45.901).
The primary endpoint analysis will be of patients aged 12 years and above.
9.3.2.2
Secondary outcomes
Databases I/II combined
Secondary endpoints will include,
Rate of exacerbation, 

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Health Care Resource Utilization (HCRU)
HCRU is defined as frequency of hospitalizations, ER visits, and outpatient visits during 
follow-up, all-cause and asthma related, and the associated costs (medical and pharmacy). 
Additional Secondary outcomes Database II
Where Tio patients and their matched subgroup of NonTio  patients both have available 
lung function test results at baseline and in the follow up period, we will utilize change in 
lung function (trough FEV1) as a secondary outcome.  
Where Tio patients and their matched subgroup of NonTio patients both have available 
ACT score results at baseline and in the follow up period, we will utilize change in ACT 
score.  
9.3.3
Covariates
Other covariates are described in Table 1, including demographic information as available in 
the dataset as recorded at index date. Comorbidities included in the CCI will be identified 
during the pre-index period. Other and specific comorbidities such as cardiovascular 
conditions, cerebrovascular diseases, hypertension, diabetes, metabolic and endocrine 
comorbidities, anxiety and depression, gastro-esophageal reflux disease, cancer and obesity 
will also be identified during baseline. Additionally, polypharmacy at baseline, will be 
identified in the pre-index period.  Finally, a composite measure of asthma control status will 
be made as defined in Table 1, classified as Well and Poor. Asthma Control Test score and 
eosinophil blood count levels as available, will also be identified at baseline for Cohort II 
only.  We will also record exacerbation rate, resource use parameters, and cost during 
baseline.

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Table 1: Matching Parameters
Variable Name and 
Type
Description
Applicable to Study Cohort: 
1=IMS, 2=EMRClaims+
ICS/LABA dose on 
ICS/LABAi date
The dose level of the first prescription on 
the ICS/LABAi date (low, medium, or 
high)
1 and 2
Demographics 
(categorical and 
continuous variables)
Age (10-year increments) and Gender 
Male/Female),
Region (if available, Northeast, Midwest, 
South, West)
1 and 2
CCI (continuous 
variable)
Charlson Comorbidity Index score
1 and 2
Specific 
comorbidities 
(categorical 
variables)
Cardiovascular conditions, 
cerebrovascular diseases, hypertension, 
diabetes, metabolic and endocrine 
comorbidities, anxiety and depression, 
gastro-esophageal reflux disease, cancer 
and obesity identified using appropriate 
ICD codes. All above measures will be 
coded as binary (yes/no) variables.
1 and 2
Medications 
(categorical variable)
Polypharmacy level matched within a 
range of 2 drugs (for example, 0-2,3-5,6-
8,8-10 and so on).  
1 and 2
Asthma Control 
Status:
Well Control or 
Poor Control 
(categorical variable)
‘Well Controlled’ if patient has no 
prescriptions for an OCS, and no asthma-
related emergency department visits or 
hospitalizations other than the first 
diagnosis recorded in the data extracted 
(Ref: Stempel JACI 2005).
Categories will include Well Controlled 
and Not Well Controlled.
1 and 2
Hospital admissions 
Outpatient visits 
ER visits and OCS 
use
(categorical 
variables)
Poorly Controlled patients (“Not Well 
Controlled”) will further be matched based 
on the presence of asthma-related 
admissions, outpatient visits, and ER visits 
or use of OCS during the pre-index period.
1 and 2
Eosinophil levels 
(EMRClaims+ 
database only) 
(categorical 
variables)
Eosinophil level categories: <150 
cells/µL,151-300cells/µL, 301-400 
cells/µL, ≥400 cells/µL (as available)    
2
Asthma Control Test 
(ACT) results
(EMRClaims+ 
database only) 
(categorical 
variables)
ACT score categories developed based on 
data distribution (as available)
2

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9.4
DATA SOURCES
Two separate databases will be appended to create the analytic dataset to obtain sufficient 
power for the primary endpoint analysis.  This approach will provide both comprehensive 
geographic representation from national claims, and important asthma clinical measures 
available through electronic medical records (EMR).  Both databases have been widely 
published in the academic asthma literature. 
As a general note, this study protocol attempts to anticipate availability of detailed data 
elements of the two real-world data sets listed below.  Consistent with accepted research 
standards using retrospective administrative data, evaluation of missing data and study 
variables is often required to ultimately finalize the study protocol as it relates to inclusion 
of covariates as well as secondary outcome measures.  
IMS Pharmetrics (IMS or Database I)
We will establish Database 1 using medical and pharmacy claim records from IMS 
Pharmetrics data.  Data from January  2015-2018 will be extracted, with the first patient 
follow-up period for tiotropium 1.25 mcg dose patients starting January 2016.  This 
database contains administrative insurance data and enrolment information derived from 
approximately 150 million commercially insured and Medicare lives. This longitudinal 
database allows documentation and analysis of the patient journey from diagnosis to 
intervention and follow-up. It is nationally representative covering 90% of US hospitals 
and compliant with current HIPAA (Health Insurance Portability and Accountability Act) 
regulations.
EMRClaims+ (Database II)
We will establish database II using EMRClaims+®, which will offer lung function results, 
Asthma Control Test (ACT) scores, as well as eosinophil counts for asthma patients in 
addition to administrative data. EMRClaims+® is an integrated health services database 
containing more than 20 million EMR across seven states in the Midwestern region of the 
United States.   The database includes administrative insurance claims of approximately 
690,000 lives linked to an overlapping healthcare provider database of EMR, including 
laboratory values, and provider billing files.  
The above two databases will be combined for the analysis of endpoints common to both 
databases. 
9.5
STUDY SIZE
The expected number of asthma patients aged 12 years and above, without concurrent 
COPD, and continuous enrollment for 12 months prior to the Tiotropium Respimat®  date 
is estimated to be approximately 2,100 to be matched to double (4200 patients) the number 
of NonTio patients resulting in a total N =6,300.   Power calculation was conducted for the 
primary endpoint, time-to-first exacerbation by the end of the follow-up time. The 
calculation was based on detecting a significant treatment effect using Cox proportional 
hazard model. Estimates were obtained from the MEZZO trial comparing tiotropium 2.5 
μg vs. salmeterol (P15-01655). Assuming 6.4% of patients in the control group followed 

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up for 5.5 months will have an exacerbation (based on the salmeterol group in the MEZZO 
study) and assuming a constant hazard rate, equating to an exponential rate parameter of 
0.012 per month for the control group and 0.0096 per month for the Tio group, the power 
is calculated to be 77%. Using the Primo study, assuming 26.9% of patients in the control 
group followed up for 11 months will have an exacerbation (based on the Tio R 5 group in 
the 48-week study Primo) and assuming a constant hazard rate, equates to an exponential 
rate parameter of 0.028 per month in the control group and 0.0224 per month in the Tio 
group, the power is 98%.  The Mezzo-derrived power calculation likely underestimates the 
power since our study design includes sicker patients that required a step-up in ICS 
treatment (not required in the Mezzo Study). While we expect that the actual power will lie 
between the two estimates (assuming that the patient population is similar to the less severe 
Primo patients and the more severe MEZZO patients), the estimated power is greater than 
77%.
9.6
DATA MANAGEMENT
All established security and confidentiality procedures will be observed by BI and/or 
 
 personnel who are assigned appropriate access to the data. Enrolment data, medical 
claims, and prescription claims will be accessed from this administrative claims dataset. The 
analyses will be performed on limited data sets that are void of member protected health 
information and all results were shared in aggregate form only.
9.7
DATA ANALYSIS
9.7.1
Main analysis
We will provide the sample attrition at each step of the inclusion-exclusion criteria as well 
as a baseline demographic and comorbidity breakdown. We will provide a comparative 
breakdown in baseline measures for the unmatched and matched cohorts to assess if PSM 
eliminated baseline differences. For the primary endpoints analysis, we will calculate the 
time to first exacerbation per patient and compare it between the two groups (Tio vs. 
NonTio).  For secondary endpoint analyses we will compare the rate of exacerbation, 
proportion of patients with exacerbations after 6 months and one year (based on Kaplan 
Meier estimates), HCRU and average cost during follow-up and compare them between the 
two groups (Tio vs. NonTio). 
 
The primary outcome of the study will be analyzed using Cox proportional hazard 
modelling. The secondary outcome of rate of exacerbation per patient will be analyzed 
using negative binomial regression. This technique works on the assumption that the rate 
of exacerbation varies among every subject in the study (P16-06846). Also this model 
accounts for overdispersion of data which is likely to happen due to variability between the 
patients. Balance in covariates will be checked after matching. If PSM was able to balance 
all observed baseline characteristics, the regression models for outcomes  will be limited to 
the databases (IMS and EMR) and to the key independent variable of interest (namely Tio 
use vs. ICS/LABA dose increase) and model overfitting is not, therefore, of concern.  
However, if there are unbalanced baseline characteristics, we will include these 
characteristics in the regression as covariates.  For regression model covariate selection we 

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will also estimate the multicollinearity of covariates by assessing their correlations of 
independent variables. For example, if comorbidities from the specific list are also 
included in CCI, they will only be included in the CCI.  
In order to handle missing data, in the PSM we will create a category variable (‘missing 
data”) for each covariate to ensure that patients with that variable and without that variable 
are respectively matched. Patients with missing prescription data required for classification 
of the treatment groups will be excluded.  Patients with missing lung function scores and 
ACT scores at baseline and in the follow up period will be excluded from these respective 
secondary analyses. 
9.8
QUALITY CONTROL
All programming will be quality controlled by two-step code checking. All results generated 
will be reviewed internally by two co-investigators separately prior to finalization.
9.9
LIMITATIONS OF THE RESEARCH METHODS
Claims and EMR data are subject to certain limitations. The presence of a claim for a filled 
prescription or prescription absent a claim does not indicate that the medication was 
consumed or that it was taken as prescribed, and any medications filled over-the-counter or 
provided as samples by the physician will not be observed in the claims data. Finally, as 
with all claims-based analyses, study results may not be generalizable to the overall 
population as patients who have commercial health insurance may be different from those 
with non-commercial or without (commercial) health insurance. Database I 
underrepresents the population aged 65 years and older, which may affect external validity 
in the case of Medicare, Medicare Advantage or Medicaid patients.  Since unmatched 
patients will be excluded, the results may not be generalizable to all patients. Some study 
measures and outcomes will include missing data and hence reduce the sample size.  Not 
all patients in Database II will have lung function results or ACT scores, therefore, the 
sample size for related secondary endpoints or sub-group analyses may produce results for 
these analyses that are not generalizable.  While duplication analyses will make double 
counting the same patient across both datasets negilible, it should be noted that the same 
patient may be present in both cohorts. 

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Including patients with persistent use of high-dose ICS/LABA(as opposed to an increase in 
ICS/LABA dose) in the NonTio group, may complicate the interpretation of the results, as 
patients with a deterioration in their asthma necessitating an increase in asthma medication 
(Tio group) will be matched to patients continuing on the same medication (high-dose 
ICS/LABA).
No claims regarding the effectiveness of Tio should be made on the basis of this study. 
This real-world evidence study lacks controls available with randomized controlled trials. 
Patient misclassification, missing data, objective and reliable  measurement of patient 
outcomes, and lack of detailed information regarding subjects’ cinical history or clinical 
status during the study timeframe may undermine the accuracy of our study results. 
9.10
OTHER ASPECTS
The IMS® PharMetrics Plus database is comprised of adjudicated claims for more than 
150 million unique enrollees across the US. Enrollees with both medical and pharmacy 
coverage in 2012 represented 40 million active lives. Patients in the majority of three-digit 
zip codes and in every metropolitan statistical area of the US are represented, with 
coverage of data from 90% of US hospitals, 80% of all US doctors, and representation 
from 85% of the Fortune 100 companies. Because the database is constructed from a 
variety of geographic regions and employer groups, the database maintains a level of 
diversity while representing the overall trend in commercial health plan coverage. The 
underrepresentation of the population aged 65 years and older may affect external validity 
in the case of Medicare, Medicare Advantage or Medicaid patients. 
EMRClaims+®, will offer lung function results, Asthma Control Test (ACT) scores, as 
well as eosinophil counts for asthma patients in addition to administrative data. 
EMRClaims+® is an integrated health services database containing more than 20 million 
EMR across 7 states in the Midwestern region of the United States.   The database includes 
administrative insurance claims across approximately 690,000 lives linked to an 
overlapping healthcare provider database of EMR, including laboratory values, and 
provider billing files.  This data source uniquely provides a strong-level of internal validity 
since two separate sources (EMR and administrative data) cross reference unique patient 
identifiers.  In the event of discrepancies between administrative files and EMR data (or for 
uncertainty about disease classification), manual evaluation of the individual patients' 
medical records is conducted to provide resolution based on access to the complete patient 
medical history in the EMR.   
The databases do not have the capability to uniquely identify members who disenroll and 
re-enroll; consequently, these individuals are assigned a new identifier and may be 
represented in the data as two unique subjects. It is also possible that a patient may be in 
both cohorts.  Both possibilities will be checked using zip codes.  If two patients are 
suspected of being the same, only the data with the longer follow-up period will be used.

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9.11
SUBJECTS
1. Patients with least one asthma diagnosis in the inpatient setting or at least two 
separate instances of asthma diagnosis (separated by at least 30 days) recorded in 
the outpatient or emergency room setting will be included (ICD 9 CM: 493.xx or 
ICD 10: J45-J45.999).
2. Patients will be required to be already on ICS/LABA.
3. Patients below the age of 6 years on the ICS/LABAi  date will be excluded. 
4. Patients will be required to have available records 12 months prior to the index date
(6 months will be used if patient exclusions due to this criteria adversely affect the 
study sample size).
5. Patients with a diagnosis of COPD at any time during the study period will be 
excluded.
6. Those who are on biologics at baseline will be removed. 
7. After the PSM process, unmatched patients will be excluded.
9.11.1
Cases
NA
9.11.2
Controls
NA
9.12
BIAS
Channeling Bias Mitigation
Introduction of channeling bias in this study is highly likely using retrospective claims data 
based on asthma medication use; patients between the two cohorts may differ in baseline 
control and severity levels. On aggregate, patients for whom Tiotropium Respimat®  1.25 
mcg was added (vs NonTio) are likely to be less well-controlled and more severe both at 
baseline and  and during the follow up period.  Absent a method to control for this 
channeling bias, it is likely that placing sicker patients in the Tiotropium Respimat®  
1.25mcg group will confound an accurate comparison of cost, resource use, and other 
outcomes between the groups. Two design features of our study will help mitigate this 
bias.  First,  our comparison (NonTio) group will be required to step-up their baseline 
ICS/LABA dose or have an  additional prescription/refill of high-dose-ICS/LABA 
following the first prescription of baseline high dose ICS/LABA within the study period. 
Second, we will use Propensity Score Matching (PSM) to match patients on key measures 
of disease control and severity as listed in Table 1, such as demographics, Charlson 
Comorbidity Index (CCI) score, specific comorbidities, number of prescriptions (overall 
and asthma-related medications). This baseline matching strategy will be particularly 
important to ensure that patients in the TIO group who have a corresponding increase in 
their ICS dose at or prior to the date of their TIO prescription (for example, if the patient 
has an exacerbation), will be matched to a corresponding NonTIO patient in terms of 
increased ICS dose or additional ICS prescription. It should be noted that after the 
prescription index date for both Tio and NonTio patients, we anticipate changes in ICS 
medication for patients in both cohorts.  These ICS medication changes reflect patient 

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outcomes in the follow-up period, where patients who encounter exacerbation in either 
group are likely to see a change in the ICS dose.  
 
 
  As a result, post-index period ICS medication 
changes will not alter the classification of patient groups nor will it be the basis for 
exclusion of these patients.     
We will conduct 1:2 matching using a nearest neighbour matching approach with a radius of 
0.2*SD(log(P)). This will be conducted in both databases (IMS: Cohort I and EMRClaims+: 
Cohort II) separately.  

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10.
PROTECTION OF HUMAN SUBJECTS
All data are HIPAA compliant to protect patient privacy.

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11.
MANAGEMENT AND REPORTING OF ADVERSE 
EVENTS/ADVERSE REACTIONS
No Adverse Events are anticipated to be identified in this study. 
Data is anonymized and extracted, analyzed, validated and reported in aggregate.
There is no potential that any employee of BI or agent working on behalf of BI will access 
individual patient data where adverse events is identified during data compilation, data 
reporting or data analysis.

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12.
PLANS FOR DISSEMINATING AND COMMUNICATING 
STUDY RESULTS
TBD

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13.
REFERENCES
13.1
PUBLISHED REFERENCES
P14-03600
Chung KF et al. International ERS/ATS Guidelines on definition 
evaluation and treatment of severe asthma. Eur Respir J 43, 343-373 
(2014)
P15-01655
Kerstjens HA et al. Tiotropium and salmeterol as add-on therapies to 
inhaled corticosteroids for patients with symptomatic asthma: two replicate, 
double-blind, placebo-controlled, parallel-group, active-comparator, 
randomised trials. Lancet Respir Med. 2015 May;3(5):367-76
P16-06846
Keene ON, Calverley PMA, Jones PW, Vestbo J, Anderson JA.  Statistical 
Analysis on exacerbation rates in COPD, TRISTAN, and ISOLDE 
revisited.  Eur Respir J 32 (1) 17-24 (2008)
P19-00715
Braido F.  Failure in Asthma control:  Reasons and Conseuqences.  
Scientifica 2013.  549252 (2013)
R11-4318
Guidelines for Good Pharmacoepidemiology Practices (GPP) (revision 2: 
April 2007). http://www.pharmacoepi.org/resources/guidelines_0827.cfm 
(access date: 13 September 2011) ; Bethesda: International Society for 
Pharmacoepidemiology (ISPE); 2007.
R16-0701
Peters SP, Jones CA, Haselkorn T, Mink DR, Valacer DJ, Weiss ST.  Real-
world Evaluation of Asthma Control and Treatment (REACT):  findings 
from a national web-based survey.  J Allergy Clin Immunol 119 (6) 1454-
1461 (2007) 

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ANNEX 1. LIST OF STAND-ALONE DOCUMENTS
NA

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ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS
NA

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