CITRUS Study (Comparing the Incidence Between Tiotropium and ICS/LABA in Real World Use in South Korea)
Conditions: Pulmonary Disease, Chronic Obstructive
Sponsor: Boehringer Ingelheim

ABCD
 
 
 
001-MCS-90-124_RD-01 (4.0) 
Protocol for non-interventional studies based on existing data 
 
Document Number: 
c26865718-02 
BI Study Number: 
0205-0542  
BI Investigational 
Product(s): 
Spiriva® HandiHaler® & Respimat®  
(Tiotropium) 
Title: 
Non-interventional study to compare effectiveness of LAMA to fixed 
dose combination of inhaled corticosteroid and long-acting beta 
agonists (ICS/LABA) in patients with chronic obstructive pulmonary 
disease (COPD) based on existing data 
Protocol version 
identifier: 
Version 1 
Date of last version of 
protocol: 
8 Apr 2020  
PASS: 
No 
EU PAS register 
number: 
32329 
Active substance: 
Tiotropium Bromide Monohydrate 
Medicinal product: 
Spiriva® HandiHaler®,Respimat®  
Product reference: 
Ba 679 BR  
Procedure number: 
 
Joint PASS: 
No 
Research question and 
objectives: 
A study to compare the occurrence of several outcomes after 
initiation of ICS/LABA therapy with their occurrence after initiation 
of LAMA therapy in COPD will be conducted. More specifically, the 
objective is to compare: 
- 
Comparison of pneumonia incidence in COPD patients using 
LAMA and ICS/LABA 
- 
Comparison of exacerbations frequency and rate in COPD 
patients using LAMA and ICS/LABA 
- 
Comparison of time to start triple combination therapy (time 
from initial ‘LAMA mono’ or ICS+LABA’ to 
‘LAMA+LABA+ICS’ combination) in COPD patients using 
LAMA and ICS/LABA 
- 
Comparison of health care utilization: Medical cost / No. of 
prescriptions, visits and hospitalizations 

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BI Study Number 0205-0542 
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001-MCS-90-124_RD-01 (4.0) 
- 
Ly Expected adverse events after long term use of ICS : 
recurrence of TB (tuberculosis), incidence of NTM(Non-
tuberculosis Mycobacteria) lung disease  
- 
Comparison of all-cause mortality differences in COPD 
patients using LAMA and ICS/LABA 
- 
Comparison of lung cancer incidence in COPD patients using 
LAMA and ICS/LABA 
Country of study: 
South Korea 
Author: 
 
  
 
Marketing authorisation 
holder(s): 
 
 
 
  
MAH contact person: 
  
 
 
Phone: 
 
 
In case of PASS, add: 
<EU-QPPV:> 
NA 
In case of PASS, add: 
<Signature of EU-
QPPV:> 
NA 
Date: 
3 Jun 2020 
 
Page 2 of 31 
 
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© 2022 Boehringer Ingelheim International GmbH or one or more of its affiliated companies. All 
rights reserved. 
This document may not - in full or in part - be passed on, reproduced, published or otherwise used 
without prior written permission 

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001-MCS-90-124_RD-01 (4.0) 
1. 
TABLE OF CONTENTS 
TITLE PAGE ............................................................................................................................... 1 
1. 
TABLE OF CONTENTS ................................................................................................... 3 
2. 
LIST OF ABBREVIATIONS ............................................................................................ 4 
3. 
RESPONSIBLE PARTIES ................................................................................................ 6 
4. 
ABSTRACT ....................................................................................................................... 7 
5. 
AMENDMENTS AND UPDATES ................................................................................. 10 
6. 
MILESTONES ................................................................................................................. 10 
7. 
RATIONALE AND BACKGROUND ............................................................................ 12 
8. 
RESEARCH QUESTION AND OBJECTIVES .............................................................. 12 
9. 
RESEARCH METHODS ................................................................................................ 13 
9.1 
STUDY DESIGN ....................................................................................................... 13 
9.2 
SETTING .................................................................................................................... 13 
9.3 
VARIABLES .............................................................................................................. 12 
9.3.1 
Exposures ........................................................................................................... 13 
9.3.2 
Outcomes ............................................................................................................ 14 
9.3.2.1 
Primary outcomes ........................................................................................... 14 
9.3.2.2 
Secondary outcomes ....................................................................................... 13 
 
 
9.3.3 
Covariates ........................................................................................................... 14 
9.4 
DATA SOURCES ...................................................................................................... 14 
9.5 
STUDY SIZE .............................................................................................................. 15 
9.6 
DATA MANAGEMENT ........................................................................................... 14 
9.7 
DATA ANALYSIS .................................................................................................... 14 
9.7.1 
Analysis Dataset: Patients selection ................................................................... 15 
9.7.2 
Main analysis ..................................................................................................... 16 
 
 
9.8 
QUALITY CONTROL ............................................................................................... 18 
9.9 
LIMITATIONS OF THE RESEARCH METHODS .................................................. 19 
9.9.1 
Data sources and variables ................................................................................. 18 
9.9.2 
Identifying patients with COPD ......................................................................... 18 
9.9.3 
Drug exposure .................................................................................................... 18 
9.9.4 
Bias and confounding  ........................................................................................ 18 
9.9.5 
Analyses ............................................................................................................. 18 
 
9.10 
OTHER ASPECTS ..................................................................................................... 19 
9.11 
PATIENTS ................................................................................................................. 19 

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001-MCS-90-124_RD-01 (4.0) 
9.11.1 
Cases .................................................................................................................. 18 
9.11.2 
Controls .............................................................................................................. 18 
9.12 
BIAS ........................................................................................................................... 18 
10. 
PROTECTION OF PATIENTS ....................................................................................... 21 
11. 
MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS ................................................................................................................... 22 
12. 
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS ...... 23 
13. 
REFERENCES ................................................................................................................ 24 
13.1 
PUBLISHED REFERENCES .................................................................................... 24 
13.2 
UNPUBLISHED REFERENCES ............................................................................... 24 
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS ........................................................... 24 
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS ........................................... 25 
ANNEX 3. ADDITIONAL INFORMATION ........................................................................... 26 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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001-MCS-90-124_RD-01 (4.0) 
2. 
LIST OF ABBREVIATIONS 
 
AE 
Adverse Event 
CI 
Confidence Interval 
  
 
  
  
 
  
  
 
  
 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
IEC 
Independent Ethics Committee 
IRB 
Institutional Review Board 
 FDC 
Fixed dose combination 
MD 
Medical doctor 
HR 
Hazard Ratio 
SPC 
Summary of Product Characteristics 
TMM 
Team Member Medicine 
TMW 
Trial Medical Writer 
TBD 
To Be Decided 
 
  
 
ER 
Emergency Room 
  

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001-MCS-90-124_RD-01 (4.0) 
3. 
RESPONSIBLE PARTIES 
Principal investigator: 
 
  
 
 
 
 
 
 
  
  
 
 
 
 
 

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001-MCS-90-124_RD-01 (4.0) 
4. 
ABSTRACT 
 
 
Name of company: Boehringer Ingelheim 
Name of finished medicinal product:  
Spiriva® HandiHaler®,Respimat® (Tiotropium Bromide Monohydrate)  
Name of active ingredient: 
Tiotropium Bromide Monohydrate 
 
 
Protocol date:  
 3 Jun 2020 
Study 
number: 
0205-0542 
Version/Revision: 
 
 1 
Version/Revision 
date: 
 
  
Title of study: 
Non-interventional study to compare effectiveness of LAMA to 
fixed dose combination of inhaled corticosteroid and long-acting 
beta agonists (ICS/LABA) in patients with chronic obstructive 
pulmonary disease (COPD) based on exiting data  
Rationale and 
background: 
According to the GOLD guidelines, ICS use should be limited in 
scope to a small portion of COPD patients3. However, ICS is 
largely overprescribed in clinical practice, regardless of COPD 
severity and exacerbation risk4-10.  
 
Even though Regular maintenance ICS therapy is associated with 
an increased risk of pneumonia, physicians do not change their 
current practice easily1,3,11. Therefore, we need a supportive data to 
niche on the proper role of ICS in treating COPD patients 
Tiotropium has been the No. 1 COPD maintenance therapy over 
the past 12 years in Korea and it is time to a timely review its 
clinical benefit in the real world setting through cumulated data. 
Spiolto Respimat® (it is called as Vaheleva® Respimat® in 
Korea) data has not been cumulated enough to be compared with 
ICS/LABA because its launch date in Korea was April 1st 2016. 
 
Research question and 
objectives: 
A study to compare the occurrence of several outcomes after 
initiation of ICS/LABA therapy with their occurrence after initiation 
of LAMA therapy in COPD will be conducted. More specifically, the 
objective is to compare: 
- 
Comparison of pneumonia incidence in COPD patients using 
LAMA and ICS/LABA ( pneumonia relative hospitalization 
and death will be seen as sub-analysis) 
- 
Comparison of exacerbations frequency and rate in COPD 
patients using LAMA and ICS/LABA 
- 
Comparison of time to start triple combination therapy (time 
from initial ‘LAMA mono’ or ICS+LABA’ to 

Boehringer Ingelheim 
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Protocol for non-interventional studies based on existing data 
BI Study Number 0205-0542 
c26865718-02
Proprietary confidential information © 2022 Boehringer Ingelheim International GmbH or one or more of its affiliated companies 
 
 
 
001-MCS-90-124_RD-01 (4.0) 
Name of company: Boehringer Ingelheim 
Name of finished medicinal product:  
Spiriva® HandiHaler®,Respimat® (Tiotropium Bromide Monohydrate)  
Name of active ingredient: 
Tiotropium Bromide Monohydrate 
 
 
Protocol date:  
 3 Jun 2020 
Study 
number: 
0205-0542 
Version/Revision: 
 
 1 
Version/Revision 
date: 
 
  
‘LAMA+LABA+ICS’ combination) in COPD patients using 
LAMA and ICS/LABA 
- 
Comparison of health care utilization: Medical cost / No. of 
prescriptions, visits and hospitalizations 
- 
Expected adverse events after long term use of ICS : 
recurrence of TB and incidence of NTM lung disease  
- 
Comparison of all-cause mortality differences in COPD 
patients using LAMA and ICS/LABA 
Ccomparison of lung cancer incidence in COPD patients using 
LAMA and ICS/LABA 
Study design: 
Non-interventional, Single-country study based on existing data from 
medical records of COPD patients treated with LAMA or fixed dose 
combination of  ICS/LABA 
Population: 
• 
Inclusion criteria  
– 
Diagnosed with COPD [based on ICD-10 code 
(J43.x-44.x except J430), as the primary or within 
the forth secondary diagnosis and initiated LAMA 
or ICS/LABA more than twice a year from Jan 1, 
2005 to Apr 30 2016]. 
– 
Age>55 years old as of 2005 when enroll started 
• 
Exclusion criteria  
– 
Prescription history with any long acting and short 
bronchodilator for maintenance therapy (the patient 
should be inhaler naïve) from 2002 to 2005 
– 
Prescription history with Leukotriene receptor 
antagonist(LTRA) or ICS 
– 
Prescription history of LABA/LAMA FDC 
Patients with lung cancer, IPF, ILD or lung transplantation at the time 
of COPD diagnosis  
Variables: 
Detailed definitions of variables that will be derived for statistical 
analyses and summaries will be included in the Statistical 
Analysis Plan (SAP). 

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001-MCS-90-124_RD-01 (4.0) 
Name of company: Boehringer Ingelheim 
Name of finished medicinal product:  
Spiriva® HandiHaler®,Respimat® (Tiotropium Bromide Monohydrate)  
Name of active ingredient: 
Tiotropium Bromide Monohydrate 
 
 
Protocol date:  
 3 Jun 2020 
Study 
number: 
0205-0542 
Version/Revision: 
 
 1 
Version/Revision 
date: 
 
  
Data sources: 
Korea National Health Insurance claim data & mortality data from 
the Bureau of Statistics from Jan 2005 to Apr 2016. 
Study size: 
At least 10,000 total.   
At least 5,000 for each arm. 
Data analysis: 
All analyses will be performed with SAS and R . All variables will be 
summarized descriptively through displays of mean(± standard 
deviations), median, and ranges for continuous variables, and 
frequency distributions of categorical variables. To address the 
imbalance of potential confounders between LAMA ICS/LABA 
groups, we matched treatment groups using propensity scores 
estimated as by multiple logistic regression analysis based on as age, 
sex, socioeconomics status, Charlson Comorbidity Index, and 
asthma, and history of COPD exacerbation. Cox proportional hazards 
regression analyses will be used to estimate hazard ratios (HRs) HRs 
and 95% confidence intervals (95% CIs) for all outcomes. For 
(possibly) repeating events (such as exacerbation event) additionally 
a Poisson regression model will be fitted for the number of events 
(taking into account the matching). Detailed methodology for 
summary and statistical analyses of data in this study will be 
documented in an SAP. 
Milestones: 
Start of data collection in 2020 April 15  
End of data collection in 2020 Dec 31 
Start of data analysis in 2021 Jan 1   
End of data analysis in 2021 Dec 31  
Final report of study results expected in 2022 Aug  

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001-MCS-90-124_RD-01 (4.0) 
5. 
AMENDMENTS AND UPDATES 
 Number 
Date 
Section of  
study 
protocol 
Amendment or 
update 
Reason 
1 
8 Apr 2020 
Milestones 
Update 
Specific dates have been 
added for the study 
timeline 
2 
3 Jun 2020 
Milestones 
Update 
Dates have been added 
for the study timeline  

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6. 
MILESTONES 
 
Milestone 
Planned Date 
Registration in the EU PAS 
register 
15 Nov 2019 
Start of data collection 
15 Apr 2020 
End of data collection 
31 Dec 2020 
Final report of study results  
30 Aug 2022 
 
 

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001-MCS-90-124_RD-01 (4.0) 
7. 
RATIONALE AND BACKGROUND 
 
According to the GOLD guidelines, ICS use should be limited to a small portion of COPD patients3.  
However, ICS are largely overprescribed in clinical practice, regardless of COPD severity and 
exacerbation risk4-10. Even though maintenance ICS therapy is associated with an increased risk of 
pneumonia, physicians do not change their current practice easily1,3,11. Therefore, we need a 
supportive data on the proper role of ICS in treating COPD patients. 
 
Tiotropium has been the No. 1 COPD maintenance therapy over the past 12 years in South Korea and 
a timely review its clinical benefit in the real world setting through cumulated data. 
 
Spiolto Respimat® has not been accumulated enough data to be compared with ICS/LABA because 
its launch date in Korea was April 1st 2016.  
8. 
RESEARCH QUESTION AND OBJECTIVES 
In COPD patients, long-term use of ICS is reported to be linked to an increase in the rate of serious 
pneumonia1. A study to compare the occurrence of several outcomes after initiation of ICS +LABA 
therapy with the occurrence after initiation of LAMA therapy in COPD will be conducted. More 
specifically, the objective is to compare: 
- Comparison of pneumonia incidence in COPD patients using LAMA and ICS/LABA 
- Comparison of exacerbations frequency and rate in COPD patients using LAMA and ICS/LABA 
- Comparison of time to start triple combination therapy (time from initial ‘LAMA mono’ or 
ICS+LABA’ to ‘LAMA+LABA+ICS’ combination) in COPD patients using LAMA and ICS/LABA 
- Comparison of health care utilization: Medical cost / No. of prescriptions, visits and hospitalizations 
- Expected events after long-term use of ICS: osteoporosis, bone fracture, diabetes mellitus, cataracts 
and recurrence of tuberculosis, Non-tuberculosis Mycobacteria lung disease 
- Comparison of all-cause mortality differences in COPD patients using LAMA and ICS/LABA 
- Comparison of lung cancer incidence in COPD patients using LAMA and ICS/LABA 
 

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001-MCS-90-124_RD-01 (4.0) 
9. 
RESEARCH METHODS 
9.1 
STUDY DESIGN 
This is a non-interventional, single-country study based on existing data from medical records of 
patients in Korea National Health Insurance claim data & mortality data from the Bureau of Statistics 
from Jan 2005 to Apr 2016. This is a retrospective review study of nationwide cohort, which analyses 
the claims data of the entire Korean population.  
 
In total, at least 10,000 eligible patients are planned to be enrolled to this study. 
 
9.2 
SETTING 
The study will be conducted in a general practice setting, Korea National Health Insurance claim data 
& mortality data from the Bureau of Statistics, which includes computerized medical records of more 
than half million patients in South Korea. The maximal observation period will be from Jan 2005 to 
Apr 2016.  
 
 
• 
Inclusion criteria  
– 
Diagnosed with COPD [based on ICD-10 code(J43.x-44.x except J430), as the 
primary or within the fourth secondary diagnosis and initiated LAMA or 
ICS/LABA more than twice a year from Jan 1, 2005 to Apr 30 2016]. 
– 
Age >55 years old as of 2005 when enroll started  
 
• 
Exclusion criteria  
– 
Prescription history with any long acting bronchodilator for maintenance therapy (the 
patient should be inhaler naïve) from 2002 to 2005. 
– 
Prescription history with ipratropium bromide  
– 
Prescription history with Leukotriene receptor antagonist(LTRA) or ICS 
– 
Prescription history of LABA/LAMA FDC 
– 
Patients with lung cancer, IPF, ILD or lung transplantation at the time of COPD 
diagnosis  
 
9.3 
VARIABLES 
Detailed definitions of variables that will be derived for statistical analyses and summaries will be 
included in the Statistical Analysis Plan (SAP). Variables and their description are shown on (see 
Appendix Table 1). 
 
9.3.1 
Exposures 
The exposure measures are based on the prescription of LAMA or fixed dose combination of 
ICS/LABA. Using the medication possession ratio (MPR), to describe adherence, the case of overall 

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mean MPR ≥80% defined as good adherence. Therefore, usually one inhaler is used per month, this 
study includes patients who have been prescribed total more than 10 inhalers per 12 months (1 year). 
 
9.3.2 
Outcomes 
9.3.2.1 
Primary outcomes 
Primary endpoint 
– Recorded pneumonia based on  1)ICD-10 code (J12.x-J18.x, J69.0, J84.9, B96.0, J85.1) AND 2) 
CPT code of chest x-ray(71045-71048) or chest CT(71250,71260,71270,G0297) AND 3) 
prescription of antibiotics for pneumonia in Korean Guideline)  incidence rate per year  
– Frequency rate of COPD exacerbation per year 
Moderate exacerbation: recorded as when COPD patients visited outpatient clinics with an 
ICD-10 code of COPD and systemic steroid medication and/or antibiotics were prescribed 
(within the first year after initial prescription of inhalers) 
Severe exacerbation: when COPD patients visited the emergency room or were admitted to 
hospital with an ICD-10 code of COPD(due to COPD worsening) and were prescribed 
systemic steroid medication and/or antibiotics (within the first year after initial prescription of 
inhalers) 
–Time to start triple combination therapy ICS/LABA/LAMA)                                                            
Time to add LAMA in patients with using ICS/LABA or, time to add ICS/LABA in patients 
with using LAMA before.  
 
9.3.2.2 
Secondary outcomes 
 
Secondary endpoint 
– 
Health care utilization : Medical cost / number of annual visits, prescriptions and  
hospitalizations (hospitalization mainly due to severe exacerbation of COPD) over one year. 
– 
All-cause mortality  
– 
Recorded incidence of lung cancer (based on ICD-10 code C34.XX) 
 
 
 
 
 
 
 
9.3.3 
Covariates 
Age, sex and history of COPD exacerbation, income status(quartile) or medical health insurance are 
all matching factors and will thus inherently be accounted for.  

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001-MCS-90-124_RD-01 (4.0) 
9.4 
DATA SOURCES 
Korea National Health Insurance claim data & mortality data from the Bureau of Statistics from Jan 
2005 to Apr 2016 will be used for this study. It includes computerized medical records of more than 
half million patients practices in South Korea. 
 
 
9.5 
STUDY SIZE 
In 2008~2013 NHI database, approximately 200,000 patients per year with COPD were diagnosed 
using COPD diagnostic code and a prescription for COPD medications (LAMA, LABA, ICS + 
LABA, SAMA, SABA, SAMA + SABA, PDE-4, systemic beta agonist, theophylline). In COPD 
patients, the use of LAMA and ICS/LABA was 26 to 37%, respectively.   We expect the study to 
include a minimum of 5,000 patients per arm, a conservative estimate.  
 
 
9.6 
DATA MANAGEMENT 
 
We will collect the data from the medical insurance claims from the Korean National Health 
Insurance (NHI) claims database, which will be provided for research purposes by the Korean NHIC 
with strict confidentiality guidelines All analyses were performed with SAS and R . 
 
Data for this study will be obtained via the following sources: 
 
·Eligibility DB 
- Sociodemo-graphics variables : sex, age, residential area, insurance type (the employee insured, 
the self-employed insured, dependants, medical aid), monthly contributions, occupation 
- Vital statistics : dates of birth and death, cause of death (ICD-10 codes)  
·Health care utilization DB  
- Diagnosis : International Classification of Disease-10 codes (main disease code, sub disease code) 
- Utilization and cost : date of visit, types of medical institutions (clinics/hospitals/tertiary 
hospitals/public health centres), types of visit (inpatient/outpatient/emergency/intensive 
care), length of stay, medical cost (insurer/patient), et al. 
- Health care procedures and medications : Operation and procedure codes, medication history 
(generic name code, dose, duration of prescription), material codes, et al. 
 
Data is extracted from the NHIS and stored on a secured, shared server for statistical analyses. The 
original data will be stored in its own, read-only directory to protect the integrity of the extracted data. 
After obtaining an approval from the NHIS, data analysts can access the data and conduct analysis in 
a secured computer. NHIS’s policy strictly forbids exportation of the original data, however, results 
obtained from statistical analyses can be exported after an internal review. 
 
 
9.7 
DATA ANALYSIS 
. 
The study population consists of COPD patients that have received LAMA and ICS/LABA treatment. 
The study consists of three stages: a) identification and extraction of LAMA-exposed and ICS/LABA-

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exposed cohort, b) matching between LAMA-exposed and ICS/LABA-exposed   and c) descriptive 
analysis of cohorts and analysis of outcomes. 
 
Detailed methodology for summary and statistical analyses of data generated in this study will be 
documented in an SAP. The SAP may modify the plans outlined in the protocol; any major 
modifications of primary endpoint definitions or their analyses would be reflected in a protocol 
amendment.  
 
For the purpose of this study, analyses will be conducted using SAS statistical software and R. To 
address the imbalance of potential confounders between LAMA ICS/LABA groups, we matched 
treatment groups using propensity scores estimated as by multiple logistic regression analysis based 
on as age, sex, socioeconomics status, Charlson Comorbidity Index, and asthma, history of COPD 
exacerbation. Demographics and clinical characteristics will be tabulated. Frequencies and 
percentages will be presented for categorical variables. For continuous variables, means, standard 
deviations, and ranges, or medians and inter-quartile ranges, will be reported as appropriate. We used 
a standardised difference to compare baseline characteristics between COPD patients who were 
treated with LAMA and those treated with ICS/LABA. The matched Cox proportional hazards 
regression analyses will be used to estimate hazard ratios (HRs) HRs and 95% confidence intervals 
(95% CIs) for all outcomes. For (possibly) repeating events (such as exacerbation event) additionally 
a Poisson regression model will be fitted for the number of events (taking into account the matching). 
The cox and Poisson models will be adjusted for unbalanced PS-variables at baseline. Mortality was 
estimated by the Kaplan-Meier method, and results were compared between groups using the log-rank 
test. 
 
 
9.7.1 
Analysis Dataset : Patients selection  
 
The matching between LAMA[Spriva® HandiHaler® Respimat® (Tiotropium Bromide 
Monohydrate)] and ICS/LABA are performed by sex, age category (5 year spans above 55 years), 
years since diagnosis of COPD, as available in the database, and propensity score. 
 
9.7.1.1 Propensity score methodology 
 
The propensity score will model the likelihood among COPD patients of receiving LAMA and 
ICS/LABA. The model for the propensity score will to the extent possible include the following 
elements: 
1) Age and sex  
2) Socioeconomic status (e.g. income, educational level, single living 
3) History of COPD exacerbation 
4) Charlson Comorbidity Index 
5) History of asthma 
 
A logistic regression analysis will be performed on the identified COPD patients where treatment with 
LAMA and ICS/LABA groups is the dependent, dichotomous variable and the independent variables 
are listed above (age, sex and history of COPD exacerbation et al.).  Based on this analysis, the 
propensity score is calculated for each patient. For subgroup analyses, PS matching and evaluation of 
its success, as presented below, will be re-done as covariate balance is not automatically maintained in 
sub-cohorts. 
 

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Smoking may be an important confounder in COPD but smoking status is usually not available in the 
databases at all. If smoking status is confirmed to be available, the data will be analysed with and 
without smoking status included in the model and the magnitude of the confounding effect assessed 
(sensitivity analysis). 
 
PS matching will be done in a 1:1 ratio using the nearest-neighbor algorithm, using calipers of width 
equal to 0.2 of the standard deviation of the logit of the PS (matches of the main exposure sub-cohort 
and the comparator sub-cohort are formed if the caliper width is not exceeded for the logit of PS). For 
LAMA-exposed patient to ICS/LABA-exposed patients will be selected within the same matching 
interval of the propensity score. The distribution of propensity scores will be examined between 
LAMA-exposed and eligible ICS/LABA-exposed. In the matching procedure, matched comparator 
sub-cohort patients (ICS/LABA) will be removed from the pool of eligible patients among the 
comparator sub-cohort so that a matched patient is no longer available for consideration as a potential 
match for another exposed patient.  
 
Evaluation of the success of the matching procedure will be based on a standardized difference 
(detailed below) of a covariate that is less than 0.1 between treatment groups. A standardized 
difference of a covariate of less than 0.1 between treatment groups in this study indicates a negligible 
difference in the mean or prevalence of the covariate. If larger standardized differences than 0.1 for 
some covariates exist after matching, they will be used in post-matching adjustments (i.e. PS-
variables with standardized difference >0.1 will be adjusted for in the analyses). Further adjustments 
can also be made as appropriate in additional models. Based on differences identified through 
exploratory analysis of baseline variables, we matched individual patients from each cohort (1:1) to 
ensure comparison of similar patients.  
 
 
9.7.2 
Main analysis 
 
For the primary effectiveness outcomes incidence rates (events per 1,000patients-years) with 
corresponding 95% confidence intervals (CI) will be calculated. This will be evaluated by a matched 
Cox proportional hazards regression model for counting processes, which allow the follow-up time to 
be divided into several periods and therefore control for baseline and time-dependent covariates, using 
the full observational period of available data, i.e. up to 11 years of follow up. The Cox proportional 
hazards regression will take into account the fact that individual matching (1:1) will be performed by 
considering the exposed patient and his/her matched controls as one stratum and including this as a 
stratum in the Cox proportional hazards model. Additional variables will be included in the model if 
available. The cumulative incidence plots will be accompanied by number of patients at risk at different 
time points during follow-up.  For (possibly) repeating events (such as exacerbation event) additionally 
a Poisson regression model will be fitted for the number of events (taking into account the matching). 
Time in the study will be included as an offset variable in the model. The cox and Poisson models will 
be adjusted for unbalanced PS-variables at baseline.  
The outcome will be analyzed separately for each: 
1) Primary outcome 
- Comparison of pneumonia incidence in COPD patients using LAMA and ICS/LABA 
- Comparison of exacerbations frequency and rate in COPD patients using LAMA and 
ICS/LABA : moderate or severe exacerbation 

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- Comparison of time to start triple combination therapy (time from initial ‘LAMA mono’ or 
ICS+LABA’ to ‘LAMA+LABA+ICS’ combination) in COPD patients using LAMA and 
ICS/LABA 
  
 
2) Secondary outcome 
-  Comparison of all-cause mortality differences in COPD patients using LAMA and ICS/LABA 
- Comparison of lung cancer incidence in COPD patients using LAMA and ICS/LABA 
 
- Comparison of health care utilization: Medical cost / No. of prescriptions, visits and  
hospitalizations (hospitalization mainly due to severe exacerbation of COPD) 
 
Health care utilization 
Health care utilization outcomes will be analyzed separately in each treatment group. Analyses will be 
conducted for 1)total health care expenditure 2)COPD-related utilization and cost for all of the medical 
resource utilization and costs during the follow-up period. For outpatient services, analyses were 
confined to visits with the ICD-10 code of COPD (J43.x–J44.x, except J430) with the prescription of 
COPD-related medication. For inpatient services, analyses were confined to admission with ICD-10 
code of COPD or COPD-related disease (pneumonia: J12.x–J17.x, pulmonary thromboembolism: I26, 
I26.0, and I26.9; dyspnea: R06.0; or acute respiratory distress syndrome: J80) with the prescription of 
COPD-related medication. Medical costs per person per year will be reported overall and separately 
based on type of service: inpatient healthcare visits, outpatient healthcare visits, and pharmacy 
dispensations. This involves calculating the average cost among members who are alive in the 
beginning of a month. 
 
 
 
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
  

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001-MCS-90-124_RD-01 (4.0) 
9.8 
QUALITY CONTROL 
The study will be conducted as specified in this protocol. The principal investigator, the co-
investigators and the sponsors of the study must approve all revisions to the protocol. All changes 
must be documented as protocol amendments.  
All analyses will be performed in a manner consistent with the Strengthening the Reporting of 
Observational Studies in Epidemiology (STROBE) guidelines and applicable sections of the 
Consolidated Standards of Reporting Trials (CONSORT) guidelines. 
 
 
9.9 
LIMITATIONS OF THE RESEARCH METHODS 
9.9.1 
Data sources and variables 
As this study will incorporate data sources from the availability, coverage, and validity of information 
will vary.  
9.9.2 
Identifying patients with COPD 
The beginning of COPD symptoms cannot be determined from the utilized data sources, whereas date 
of diagnosis usually can be determined. Therefore, COPD patients were determined using COPD 
diagnostic code and a prescription for COPD medications 
9.9.3 
Drug exposure 
Secondary data sources do not include information on actual drug use patterns and, therefore, the drug 
exposure in this study may be misclassified. Further, the data sources might not include complete 
information on drug prescriptions. Prescription data is one further potential source for exposure 
misclassification as the dispensation date cannot be determined.  
9.9.4 
Bias and confounding 
Confounding by indication cannot be completely excluded from this study although several approaches 
will be used to minimize confounding. Further, there will be residual confounding related to, for 
example, incomplete recording of diagnoses and lack of variables in the data sources to be utilized. 
9.9.5 
Analyses 
This will be a non-interventional, population-based, and observational study. Therefore, the results will 
indicate correlation between drug use and selected outcomes.  
 
9.10 
OTHER ASPECTS 
No 

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9.11 
PATIENTS 
9.11.1 
Cases 
9.11.2 
Controls 
Cases and Controls were previously described. 
 
9.12 
BIAS 
 
This study will include users of LAMA and ICS/LABA. Immortal time bias will be minimal, as the 
follow-up will begin at the initiation of drug use. Adherence to drug use will be unknown.  
 
Comparing the outcomes between users of LAMA and ICS/LABA will decrease confounding by 
indication, as the comparison group will have a similar indication to drug use than the patients in the 
LAMA-exposed cohorts.  
 
The compared sub-cohorts will be matched on the basis of PS. The PS will be computed on the basis of 
a wide range of covariates related to sociodemographic characteristics, history of exacerbation, other 
comorbidities, and prior/concomitant use of other drugs. The PS matching will decrease the systematic 
differences between the sub-cohorts and, thus, decrease confounding.  
 
 

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001-MCS-90-124_RD-01 (4.0) 
10. 
PROTECTION OF PATIENTS  
This study is based on existing data collected in general practices and does not require patient 
informed consent. All data used for this study are anonymized. 
 
Approval of the study protocol will be obtained from IRB/IEC in South Korea before coding, 
extraction, and processing of Korea National Health Insurance claim data & mortality data from the 
Bureau of Statistics data. Ethics approval for this study will be obtained from the name of the 
IEC/IRB 

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001-MCS-90-124_RD-01 (4.0) 
11. 
MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS 
Not applicable. Data is anonymized and extracted, analyzed, 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 in which the patient may be identified during data compilation, data reporting or data 
analysis. 

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001-MCS-90-124_RD-01 (4.0) 
12. 
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS 
We plan to publish the study in a peer-reviewed medical journal. Authorship and publication will 
follow the corresponding BI SOP and guidelines of good scientific practise. 

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001-MCS-90-124_RD-01 (4.0) 
13. 
REFERENCES 
 
13.1 
PUBLISHED REFERENCES 
1. Crim C, Calverley PM et al. Pneumonia risk in COPD patients receiving inhaled 
corticosteroid alone or in combination: TORCH study results. Eur Respir J 2009; 34 :641–
647. 
2. Nieto A et al. Adverse effects of inhaled corticosteroids in funded and nonfunded studies. 
Arch Intern Med. 2007;167:2047–53. 
3. Vogelmeier CF  et al. Global strategy for the diagnosis, management, and prevention of 
chronic obstructive lung disease 2017 report: GOLD executive summary. 2017;53:128–49. 
4. Barrecheguren M et al. Treatment patterns in COPD patients newly diagnosed in primary 
care. A population-based study. Respir Med. 2016;111:47–53. 
5. Reddel HK et al. Assessment and management of asthma and chronic obstructive pulmonary 
disease in Australian general practice. Aust Fam Physician. 2017;46:413–9. 
6. Price D et al. Management of COPD in the UK primary care setting: an analysis of real-life 
prescribing patterns. Int J Chron Obstruct Pulmon Dis. 2014;9:889–904. 
7. Izquierdo JL et al. Misdiagnosis of patients receiving inhaled therapies in primary care. Int J 
Chron Obstruct Pulmon Dis. 2010;5:241–9. 
8. Burgel PR et al. Real-life use of inhaled corticosteroids in COPD patients versus the GOLD 
proposals: a paradigm shift in GOLD 2011 Eur Respir J. 2014;43:1201–3. 
9. Roche N et al. Real-life use of fluticasone propionate/salmeterol in patients with chronic 
obstructive pulmonary disease: a French observational study. BMC Pulm Med. 2014;14:56. 
10. Calle Rubio M et al. Clinical audit of COPD in outpatient respiratory clinics in Spain:the 
EPOCONSUL study. Int J Chron Obstruct Pulmon Dis. 2017;12:417–26. 
11. Nieto A et al. Adverse effects of inhaled corticosteroids in funded and nonfunded studies. 
Arch Intern Med. 2007;167:2047–53. 
 
 
 
13.2 
UNPUBLISHED REFERENCES 

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001-MCS-90-124_RD-01 (4.0) 
ANNEX 1. LIST OF STAND-ALONE DOCUMENTS 
None 

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001-MCS-90-124_RD-01 (4.0) 
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS 
Study title: 
Comparing the Incidence between Tiotropium and ICS/LABA in Real world Use in South 
Korea 
Acronym title : CITRUS study  
 
EU PAS Register® number: EUPAS32329 
Study reference number (if applicable): 
 
Section 1: Milestones 
Yes 
No 
N/A 
Section 
Number 
1.1 
Does the protocol specify timelines for  
 
 
 
 
1.1.1 Start of data collection1 
 
 
 
6 
1.1.2 End of data collection2 
 
 
 
6 
1.1.3 Progress report(s) 
 
 
 
6 
1.1.4 Interim report(s) 
 
 
 
6 
1.1.5 Registration in the EU PAS Register® 
 
 
 
6 
1.1.6 Final report of study results. 
 
 
 
6 
Comments: 
 
 
Section 2: Research question 
Yes 
No 
N/A 
Section 
Number 
2.1 
Does the formulation of the research question and 
objectives clearly explain:  
 
 
 
7,8 
2.1.1 Why the study is conducted? (e.g. to address an 
important public health concern, a risk identified in 
the risk management plan, an emerging safety 
issue) 
 
 
 
7,8 
2.1.2 The objective(s) of the study? 
 
 
 
8 
2.1.3 The target population? (i.e. population or 
subgroup to whom the study results are intended to 
be generalised) 
 
 
 
9.1 
2.1.4 Which hypothesis(-es) is (are) to be tested? 
 
 
 
7 
2.1.5 If applicable, that there is no a priori 
hypothesis? 
 
 
 
 
Comments: 
 
 
 
1 Date from which information on the first study is first recorded in the study dataset or, in the case of secondary use of data, the date from 
which data extraction starts. 
2 Date from which the analytical dataset is completely available. 

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Section 3: Study design 
Yes 
No 
N/A 
Section 
Number 
3.1 
Is the study design described? (e.g. cohort, case-
control, cross-sectional, other design)  
 
 
 
9.1 
3.2 
Does the protocol specify whether the study is based 
on primary, secondary or combined data collection? 
 
 
 
9.1 
3.3 
Does the protocol specify measures of occurrence? 
(e.g., rate, risk, prevalence) 
 
 
 
9.7.2 
3.4 
Does the protocol specify measure(s) of association? 
(e.g. risk, odds ratio, excess risk, rate ratio, hazard 
ratio, risk/rate difference, number needed to harm 
(NNH)) 
 
 
 
9.7.2 
3.5 
Does the protocol describe the approach for the 
collection and reporting of adverse events/adverse 
reactions? (e.g. adverse events that will not be 
collected in case of primary data collection) 
 
 
 
11 
Comments: 
 
 
Section 4: Source and study populations 
Yes 
No 
N/A 
Section 
Number 
4.1 
Is the source population described? 
 
 
 
9.4 
4.2 
Is the planned study population defined in terms of: 
 
 
 
 
4.2.1 Study time period 
 
 
 
9.2 
4.2.2 Age and sex 
 
 
 
9.2 
4.2.3 Country of origin 
 
 
 
9.2 
4.2.4 Disease/indication 
 
 
 
9.2 
4.2.5 Duration of follow-up 
 
 
 
9.2 
4.3 
Does the protocol define how the study population 
will be sampled from the source population? 
(e.g. event or inclusion/exclusion criteria) 
 
 
 
9.2 
Comments: 
 
 
Section 5: Exposure definition and measurement 
Yes 
No 
N/A 
Section 
Number 
5.1 
Does the protocol describe how the study exposure is 
defined and measured? (e.g. operational details for 
defining and categorising exposure, measurement of 
dose and duration of drug exposure) 
 
 
 
9.3.1 
5.2 
Does the protocol address the validity of the exposure 
measurement? (e.g. precision, accuracy, use of 
validation sub-study) 
 
 
 
9.7 
5.3 
Is exposure categorised according to time windows?  
 
 
 
 

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Section 5: Exposure definition and measurement 
Yes 
No 
N/A 
Section 
Number 
5.4 
Is intensity of exposure addressed?  
(e.g. dose, duration) 
 
 
 
9.2 
5.5 
Is exposure categorised based on biological 
mechanism of action and taking into account the 
pharmacokinetics and pharmacodynamics of the drug? 
 
 
 
 
5.6 
Is (are) (an) appropriate comparator(s) identified? 
 
 
 
9.3.1 
Comments: 
The claimed data does not indicate the smoking status of the patients and only includes patients 
who have used inhalers for 80% in the past year. Therefore study’s exposure categories are non-
applicable.  
 
Section 6: Outcome definition and measurement 
Yes 
No 
N/A 
Section 
Number 
6.1 
Does the protocol specify the primary and secondary 
(if applicable) outcome(s) to be investigated? 
 
 
 
9.3.2 
6.2 
Does the protocol describe how the outcomes are 
defined and measured?  
 
 
 
9.3.2 
6.3 
Does the protocol address the validity of outcome 
measurement? (e.g. precision, accuracy, sensitivity, 
specificity, positive predictive value, use of validation 
sub-study) 
 
 
 
9.7.1, 9.7.3 
6.4 
Does the protocol describe specific outcomes relevant 
for Health Technology Assessment? (e.g. HRQoL, 
QALYs, DALYS, health care services utilisation, 
burden of disease or treatment, compliance, disease 
management) 
 
 
 
9.3.2 
Comments: 
 
 
Section 7: Bias 
Yes 
No 
N/A 
Section 
Number 
7.1 
Does the protocol address ways to measure 
confounding? (e.g. confounding by indication) 
 
 
 
 
7.2 
Does the protocol address selection bias? (e.g. healthy 
user/adherer bias) 
 
 
 
9.12 
7.3 
Does the protocol address information bias? 
(e.g. misclassification of exposure and outcomes, 
time-related bias) 
 
 
 
9.7.3 
Comments: 
As per section 9.12, this study compares that outcome between users of LAMA and ICS/LABA. As 
both groups have similar indication to drug confounding by indication effect is minimal. 
 

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Section 8: Effect measure modification 
Yes 
No 
N/A 
Section 
Number 
8.1 
Does the protocol address effect modifiers? 
(e.g. collection of data on known effect modifiers, 
sub-group analyses, anticipated direction of effect)  
 
 
 
9.7 
Comments: 
 
 
Section 9: Data sources 
Yes 
No 
N/A 
Section 
Number 
9.1 
Does the protocol describe the data source(s) used in 
the study for the ascertainment of: 
 
 
 
 
9.1.1 Exposure? (e.g. pharmacy dispensing, general 
practice prescribing, claims data, self-report, face-
to-face interview) 
 
 
 
9.1 
9.1.2 Outcomes? (e.g. clinical records, laboratory 
markers or values, claims data, self-report, patient 
interview including scales and questionnaires, vital 
statistics) 
 
 
 
9.2 
9.1.3 Covariates and other characteristics? 
 
 
 
9.3 
9.2 
Does the protocol describe the information available 
from the data source(s) on: 
 
 
 
 
9.2.1 Exposure? (e.g. date of dispensing, drug 
quantity, dose, number of days of supply 
prescription, daily dosage,  prescriber) 
 
 
 
9.4 
9.2.2 Outcomes? (e.g. date of occurrence, multiple 
event, severity measures related to event) 
 
 
 
9.7 
9.2.3 Covariates and other characteristics? (e.g. age, 
sex, clinical and drug use history, co-morbidity, co-
medications, lifestyle) 
 
 
 
9.7 
9.3 
Is a coding system described for:  
 
 
 
 
9.3.1 Exposure? (e.g. WHO Drug Dictionary, 
Anatomical Therapeutic Chemical (ATC) 
Classification System) 
 
 
 
9.2 
9.3.2 Outcomes? (e.g. International Classification of 
Diseases (ICD), Medical Dictionary for Regulatory 
Activities (MedDRA)) 
 
 
 
9.3.2 
9.3.3 Covariates and other characteristics? 
 
 
 
9.3.3 
9.4 
Is a linkage method between data sources described? 
(e.g. based on a unique identifier or other)  
 
 
 
9.3-9.6 
Comments: 
 
 

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Section 10: Analysis plan 
Yes 
No 
N/A 
Section 
Number 
10.1 Are the statistical methods and the reason for their 
choice described?  
 
 
 
9.7 
10.2 Is study size and/or statistical precision estimated? 
 
 
 
9.5, 9.7 
10.3 Are descriptive analyses included? 
 
 
 
9.7 
10.4 Are stratified analyses included? 
 
 
 
 
10.5 Does the plan describe methods for analytic control of 
confounding? 
 
 
 
9.7 
10.6 Does the plan describe methods for analytic control of 
outcome misclassification? 
 
 
 
9.3.3 
10.7 Does the plan describe methods for handling missing 
data? 
 
 
 
 
10.8 Are relevant sensitivity analyses described? 
 
 
 
9.7.3 
Comments: 
There is no missing data as we are using national health claim data source and this is universal 
health plan covering all Korean population 
 
Section 11: Data management and quality control 
Yes 
No 
N/A 
Section 
Number 
11.1 Does the protocol provide information on data 
storage? (e.g. software and IT environment, database 
maintenance and anti-fraud protection, archiving) 
 
 
 
9.6 
11.2 Are methods of quality assurance described? 
 
 
 
9.8 
11.3 Is there a system in place for independent review of 
study results?  
 
 
 
 
Comments: 
Our study will only go through internal BI review process and external CRO.  
 
Section 12: Limitations 
Yes 
No 
N/A 
Section  
Number 
12.1 Does the protocol discuss the impact on the study 
results of: 
 
 
 
 
12.1.1 Selection bias? 
 
 
 
 
12.1.2 Information bias? 
 
 
 
 
12.1.3 Residual/unmeasured confounding? 
(e.g. anticipated direction and magnitude of such 
biases, validation sub-study, use of validation and 
external data, analytical methods). 
 
 
 
 
12.2 Does the protocol discuss study feasibility? (e.g. study 
size, anticipated exposure uptake, duration of follow-
up in a cohort study, patient recruitment, precision of 
the estimates) 
 
 
 
9.2, 9.5 

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Comments: 
There is very little possible chance of information bias as there is only one national health 
insurance scheme.  
 
Section 13: Ethical/data protection issues 
Yes 
No 
N/A 
Section  
Number 
13.1 Have requirements of Ethics Committee/ Institutional 
Review Board been described? 
 
 
 
10 
13.2 Has any outcome of an ethical review procedure been 
addressed? 
 
 
 
 
13.3 Have data protection requirements been described? 
 
 
 
 
Comments: 
Our data set are extracted from the National Health Insurance Service and will be stored securely 
on its own in a shared server. The original data will be stored on its own, read-only directory to 
protect the integrity of the extracted data.  
 
Section 14: Amendments and deviations 
Yes 
No 
N/A 
Section 
Number 
14.1 Does the protocol include a section to document 
amendments and deviations?  
 
 
 
5 
Comments: 
 
 
Section 15: Plans for communication of study results 
Yes 
No 
N/A 
Section 
Number 
15.1 Are plans described for communicating study results 
(e.g. to regulatory authorities)?  
 
 
 
12 
15.2 Are plans described for disseminating study results 
externally, including publication? 
 
 
 
12 
Comments: 
 
 
Name of the main author of the protocol: 
  
Date: 07/April/2020 
 
Signature:  
  
 
 

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001-MCS-90-124_RD-01 (4.0) 
ANNEX 3. ADDITIONAL INFORMATION 
Appendix Table 1. List of variables in the NHIS database 
DB (number of 
variables) 
Variable name 
Details 
The eligibility of the 
insured DB  
STND_Y 
Standard year for the eligibility 
of the insured 
PERSON_ID 
Personal identification number 
is replaced by serial number 
SEX 
Sex 
AGE_GROUP 
Age group at time of diagnosed 
DTH_YM 
Year and month of death 
DTH_CODE1 
Level 1 (detailed) cause of 
death 
DTH_CODE2 
Level 2 cause of death 
SIDO 
Province of residence 
SGG 
District of residence 
CTRB_PT_TYPE_CD 
Percentile group of income 
level 
The medical 
treatment DB (called 
Table 20) [electronic 
bill of medical 
treatment]  
PERSON_ID 
Personal identification number 
is replaced by serial number 
KEY_SEQ 
Key sequence number of claim 
YKIHO_ID 
Medical care institution 
identification number 
RECU_FR_DT 
The first day of receiving 
treatment 
FORM_CD 
Form of claimed bill 
DSBJT_CD 
Medical subject code 
MAIN_SICK 
Main disease code 
SUB_SICK 
Sub disease code 
IN_PAT_CORS_TYPE 
Route through hospitalization 
OFFC_INJ_TYPE 
Type of injuries incurred while 
on duty 

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001-MCS-90-124_RD-01 (4.0) 
DB (number of 
variables) 
Variable name 
Details 
RECN 
Days of receiving medical care 
VSCN 
Days of visit hospitals or 
inpatient 
FST_IN_PAT_DT 
First date of inpatient 
DMD_TRAMT 
Amount of medical expenses 
based on claims 
DMD_SBRDN_AMT 
Expenses paid by beneficiary 
based on claims 
DMD_JBRDN_AMT 
Expenses paid by insurer based 
on claims 
DMD_CT_TOT_AMT 
Total amount for CT based on 
claims 
DMD_MRI_TOT_AMT 
Total amount for MRI based on 
claims 
EDEC_ADD_RT 
Extra rate applied based on 
claims reviewed 
EDEC_TRAMT 
Amount of medical expenses 
based on claims reviewed 
EDEC_SBRDN_AMT 
Amount of expenses paid by 
beneficiary based on claims 
reviewed 
EDEC_JBRDN_AMT 
Amount of expenses paid by 
insurer based on claims 
reviewed 
EDEC_CT_TOT_AMT 
Total amount for CT based on 
claims reviewed 
EDEC_MRI_TOT_AMT 
Total amount for MRI based on 
claims reviewed 
DMD_DRG_NO 
DRG number of claim 
MPRSC_ISSUE_ADMIN_ID 
MPRSC_GRANT_NO 
Institution identification number 
which issued prescriptions 
Prescription identification 
number (newly added since 
2011 database) 
TOT_PRES_DD_CNT 
Total days of prescription 
KEY_SEQ 
Key sequence number of claim 

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001-MCS-90-124_RD-01 (4.0) 
DB (number of 
variables) 
Variable name 
Details 
The medical 
treatment DB (called 
Table 30) [details of 
medical treatment 
bill] 
SEQ_NO 
Sequence number  
RECU_FR_DT 
Date of the first treatment 
CLAUSE_CD 
Code for clause 
ITEM_CD 
Code for item 
DIV_TYPE_CD 
Code for the type of treatment 
DIV_CD 
Code for treatment 
I_II_TYPE 
Code for an application of 
additional rate (Type I or II)) 
UN_COST 
Amount of unit cost 
AMT 
Amount of cost paid 
DD_MQTY_EXEC_FREQ 
Amount of daily dose or 
frequency of medication 
MDCN_EXEC_FREQ 
Total days of medication or 
frequency of medication 
DD_MQTY_FREQ 
Amount of single dose 
The medical 
treatment DB (called 
Table 40) [details of 
disease]  
KEY_SEQ 
Key sequence number of claim 
SEQ_NO 
Sequence number 
RECU_FR_DT 
Date of the first treatment 
DSBJT_CD 
Code for medical examination 
SICK_SYM 
Code for disease 
The medical 
treatment DB (called 
Table 60) [details of 
prescription]  
KEY_SEQ 
Key sequence number of claim 
SEQ_NO 
Sequence number 
RECU_FR_DT 
Date of the first treatment 
DIV_TYPE_CD 
Code for the type of treatment 
DIV_CD 
Code for treatment 

Boehringer Ingelheim 
Page 35 of 35
Protocol for non-interventional studies based on existing data 
BI Study Number 0205-0542 
c26865718-02
Proprietary confidential information © 2022 Boehringer Ingelheim International GmbH or one or more of its affiliated companies 
 
 
 
001-MCS-90-124_RD-01 (4.0) 
DB (number of 
variables) 
Variable name 
Details 
GNL_NM_CD 
Code for generic medication 
name 
DD_MQTY_FREQ 
Amount of single dose 
DD_EXEC_FREQ 
Amount of daily dose 
MDCN_EXEC_FREQ 
Total days of medication or 
frequency of medication 
UN_COST 
Amount of unit cost 
AMT 
Amount of cost