Retrospective, Non-interventional Study to Evaluate Chronic Myeloid Leukemia Treatment Landscape and Real-life Treatment Outcomes in Hungary: Analysis of National Health Insurance Fund Database
Conditions: Chronic Myeloid Leukaemia
Sponsor: Pfizer

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NON-INTERVENTIONAL (NI) STUDY PROTOCOL 
Study information 
Title 
Retrospective, non-interventional study to 
evaluate Chronic Myeloid Leukemia 
treatment landscape and real-life treatment 
outcomes in Hungary: analysis of National 
Health Insurance Fund database 
Protocol number 
B1871064 
Protocol version identifier 
1.0 
Date 
16 Nov 2020 
Active substance 
bosutinib (L01XE14). 
Medicinal product 
bosutinib (Bosulif) 
Research question and objectives 
The objectives of this study are to describe 
patient demographics, clinical and disease 
characteristics and treatment patterns of 
CML in Hungary. 
The primary endpoint of this study is the 
overall survival of CML patients treated 
with tyrosine kinase inhibitors in Hungary. 
The OS of all enrolled patients, OS by 
sequence pattern and by the number of 
treatment lines will be analyzed.  
Secondary objectives are description of the  
treatment length in 1st and later lines,  
incidence and prevalence of CML, the  
patient demographics (as age, gender, 
comorbidities), average number of patients’ 
comorbidities, most frequent comorbidities 
and patient number with comorbidities at 
baseline and at different treatment lines by 
investigated TKI,  distribution of the 
investigated TKI therapies by treatment lines 
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and the real-life treatment sequences in 
Hungary. 
Author 
 MD 
  
 
Hungary 
This document contains confidential information belonging to Pfizer.  Except as otherwise 
agreed to in writing, by accepting or reviewing this document, you agree to hold this 
information in confidence and not copy or disclose it to others (except where required by 
applicable law) or use it for unauthorized purposes.  In the event of any actual or suspected 
breach of this obligation, Pfizer must be promptly notified. 
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1. TABLE OF CONTENTS 
 
1. TABLE OF CONTENTS .......................................................................................................3 
2. LIST OF ABBREVIATIONS ................................................................................................5 
3. RESPONSIBLE PARTIES ....................................................................................................7 
4. AMENDMENTS AND UPDATES .....................................................................................10 
5. MILESTONES .....................................................................................................................11 
6. RATIONALE AND BACKGROUND ................................................................................12 
7. RESEARCH QUESTION AND OBJECTIVES .................................................................13 
8. RESEARCH METHODS ....................................................................................................14 
8.1. Study design ............................................................................................................14 
8.2. Setting ......................................................................................................................14 
8.2.1. Inclusion criteria .........................................................................................15 
8.2.2. Exclusion criteria ........................................................................................15 
8.3. Variables ..................................................................................................................15 
8.4. Data sources ............................................................................................................17 
8.5. Study size ................................................................................................................17 
8.6. Data analysis ...........................................................................................................18 
8.7. Limitations of the research methods .......................................................................21 
8.8. Other aspects ...........................................................................................................22 
9. PROTECTION OF HUMAN SUBJECTS ..........................................................................22 
9.1. Patient information ..................................................................................................22 
9.2. Patient consent .........................................................................................................22 
9.3. Institutional review board (IRB)/Independent ethics committee (IEC) ..................22 
9.4. Ethical conduct of the study ....................................................................................22 
10. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS ......................................................................................................................23 
11. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS........23 
12. REFERENCES ..................................................................................................................23 
13. LIST OF TABLES .............................................................................................................24 
ANNEX 1. LIST OF STAND ALONE DOCUMENTS .........................................................24 
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ANNEX 2. ADDITIONAL INFORMATION .........................................................................24 
 
 
 
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2. LIST OF ABBREVIATIONS 
 
Abbreviation 
Definition 
1L 
First line treatment 
2L 
Second line treatment 
3L 
Third Line  
AE 
Adverse Event 
BCL-ABL1 
Breakpoint Cluster Region—Abelson fusion gene 
CCR 
Complete Clinical Response 
CML 
Chronic Myeloid Leukemia  
DSU 
Drug Safety Unit 
ELN 
European LeukemiaNet 
EMA 
European Medicine Agency 
ICD -10 
International Classification of Diseases – 10th 
revision 
ICHI   
International Classification of Health Interventions 
IEC 
Independent ethics committee 
IRB 
Institutional   review board 
MR 
Molecular response 
NHIF 
National Health Insurance Fund 
NPP 
Named Patient Program 
OS 
Overall Survival 
Ph 
Philadelphia 
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TKI 
Tyrosine Kinase Inhibitor 
TTT code 
The code used by NHIF to identify the medicinal 
product 
 
 
 
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3. RESPONSIBLE PARTIES 
Principal Investigator(s) of the Protocol 
Name, degree(s) 
Job Title 
Affiliation 
Address 
Prof. 
 
MD, PhD, DSc 
 
 
 
 
 
 
 
 
 
Hungary 
 MD, 
PhD 
 
 
 
 
 
 
 
   
Hugnary 
 
MD, PhD 
 
 
 
 
 
 
 
 
Hungary 
 
MD 
 
. 
 
 
Hungary 
 
MD 
 
 
 
 
 
Hungary 
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4. ABSTRACT 
Study Title: Retrospective, non-interventional study to evaluate Chronic Myeloid Leukemia 
treatment landscape and real-life treatment outcomes in Hungary: analysis of National Health 
Insurance Fund database 
Protocol Version and Date: Version 1.0; 16 Nov 2020 
Primary Author: 
 MD, 
 
Hungary 
Rationale and background: Patients, with the diagnosis of chronic myeloid leukemia 
(CML) nowadays expect a life expectancy close to the average life expectancy, due to the 
availability of the targeted Bcr-Abl tyrosine kinase inhibitor (TKI) treatments. However, the 
majority of patients should receive continuous treatment for an indefinite period, even for the 
rest of their lives. Five TKIs (imatinib, nilotinib, dasatinib, bosutinib, and ponatinib) are 
available in Hungary in everyday clinical practice. 
By the decision of the CML, treatment physicians should take into account the patient's risk 
classification, comorbidities and patient preferences not only by determining first-line 
treatment but at therapy switch. Despite the excellent results, half of the patients will 
eventually fail (due to intolerance or resistance) to first-line treatment, and many may require 
a second, third, or even additional line of therapy. 
Few publications exist on real-world treatment pattern from Western Europe, but there is no 
such data from Hungary so far. Given the population, genetic, cultural, health condition and 
health care system differences on country and geographic region level, it is important to 
investigate real world data regionally.  
Research question and objectives: The objectives of this study are to describe patient 
demographics, clinical and disease characteristics and treatment patterns of CML in 
Hungary. 
The primary endpoint of this study is the overall survival of CML patients treated with 
tyrosine kinase inhibitors in Hungary. The OS of all enrolled patients, OS by sequence 
pattern and by the number of treatment lines will be analysed and displayed on Kaplan-Meier 
curve.  
Secondary objectives are description of the treatment length in 1st and later lines, incidence 
and prevalence of CML, the  patient demographics (age, gender, comorbidities), average 
number of patients’ comorbidities, most frequent comorbidities and patient number with 
comorbidities at baseline and at different treatment lines by investigated TKI, distribution of 
the investigated TKI therapies by treatment lines and the real-life treatment sequences in 
Hungary. 
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Study design: Retrospective, non-interventional study to evaluate Chronic Myeloid 
Leukemia treatment landscape and real-life treatment outcomes in Hungary using the 
database of the National Health Insurance Fund of Hungary 
Population:  All patients treated with TKI based on CML diagnosis between 01 January 
2011-30 June 2020.  
Variables: The variables assessed in this study are patient demographics, clinical 
characteristics, comorbid conditions, chronic myeloid leukemia treatment history and TKI 
treatment pattern. 
Data sources: Prescription claims data, outpatient and inpatient data from the database of the 
National Health Insurance Fund of Hungary. Hungary provides universal healthcare for its 
citizens, thanks to the single-payer public system, the NHIF database contains all prescription 
claims data of all reimbursed medicinal products, all outpatient and inpatient data from all 
Hungarian patients.  
Study size: Approximately 1000-1200 patients’ data will be analysed. 
Data analysis: The mathematical algorithm required for analysis is designed and provided 
by RxTarget Statistical Programming and Analysis Ltd. using SQL programming language 
based on a preliminary study plan. The algorithm is run by experts at NHIF using primary 
social security number-level data from selected patients. Anonymized data is provided by 
NHIF in an aggregated form without any individual identification parameter based on a 
specific permit, with the strict consideration of data protection rules. Descriptive statistics 
will be applied for the variables, and no hypothesis is tested.  
Milestones: 
Milestone 
Planned date 
Start of data analysis 
Q4 2020 
End of data analysis 
Q4 2020 
First report 
Q4 2020 
Final study report 
Q1 2021 
Manuscript for publication 
Q3 2021 
 
 
 
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5. AMENDMENTS AND UPDATES 
None. 
 
 
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6. MILESTONES 
 
Milestone 
Planned date 
Start of data Analysis 
Q4 2020 
End of data Analysis 
Q4 2020 
First report 
Q4 2020 
Final study report 
Q1 2021 
Manuscript for publication 
Q3 2021 
 
 
 
 
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7. RATIONALE AND BACKGROUND 
CML is a neoplastic disease whose genetic and cytogenetic changes play important roles in 
prognosis and treatment strategies. Philadelphia (Ph) translocation t(9;22)(q34;q11) results 
the BCL-ABL1 fusion gene causing a constitutively activated tyrosine kinase. The presence 
of the Philadelphia (Ph) chromosome or the BCL-ABL1 fusion gene is part of the diagnosis 
of the disease.1 The course of the disease consists of 3 stages, the chronic, the blast phase and 
the accelerated phase. In the chronic phase, up to 30-40% of patients are asymptomatic and 
approximately 85% of patients are diagnosed in this phase.1 
According to the international literature the incidence of chronic myeloid leukemia (CML) is 
1-1.5 / 100,000 inhabitants per year. Prevalence trend to be 4 times higher than the incidence. 
The increase in prevalence began with the introduction of tyrosine kinase inhibitors (TKI). 
Based on the literature data, the average age of patients at diagnosis is 60-65 years, and CML 
is exceptionally rare in childhood. Slightly more men are affected by this disease than 
women (1.2-1.3: 1). 
The primary goal of the treatment is to achieve complete cytogenetic remission and a 
significant molecular response. Treatment should be started immediately after diagnosis and 
the majority of patients should receive continuous treatment for an indefinite period, or even 
for the rest of their lives to control the malignant disease. TKI treatment should be withheld 
during pregnancy. Treatment discontinuation may be considered in patients with durable 
deep molecular response with the goal of achieving treatment free remission.2 
The prognosis of chronic myeloid leukemia (CML) has changed since the introduction of 
imatinib in the early 2000’s. Survival in CML patients changed and improved drastically 
with the introduction of imatinib. At the time of diagnosis, patients can expect a normal life 
expectancy nowdays.5 With imatinib treatment, 8-10 years survival rates are above 80%, and 
the cause of death in CML patients is typically unrelated to CML, in most cases related to co-
morbidities.4,5 
The most effective treatment options are the drugs belonging to the group of tyrosine kinase 
inhibitors (TKIs), however, allogeneic haematopoietic stem cell transplantation is still the 
therapeutic option available.1 First-, second- and third generation tyrosine kinase inhibitors 
are currently available. The ELN (European LeukemiaNet) 2020 guideline provides guidance 
for physicians to develop an appropriate treatment strategy.2 
According to the latest guidelines (ELN 2020), beside the efficacy of the TKIs, the 
contraindications and typical adverse event profile, early and late toxicity profile of the 
available TKIs, the risk classification, patient preferences and even the existing comorbidities 
should be taken into account by designing the treatment plan. The results of the available 
first- and second-generation TKIs suggest that a more rapid and deeper molecular response 
can be achieved with second-generation TKIs, however, there is no significant difference in 
long-term survival between first-generation imatinib and second-generation TKIs (dasatinib, 
nilotinib, bosutinib).2 
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Close monitoring of the therapeutic response is required and made by regular monitoring 
BCL-ABL1 levels at specified intervals. Switching the therapy may occur in the case of 
relapse, resistance to the TKI or intolerable toxicity. As nowadays 5 TKIs are available, 
patients may receive several lines of TKI therapies. Approximately half of the patients will 
start 2nd line treatment after first line imatinib within 5 years of therapy.5  
In Hungary bosutinib is accessible for patients within its EMA label since 2013 via 
individual reimbursement, and via regular reimbursement since 2017 in 2nd and later lines. 
Imatinib the first TKI for CML has been used since 2001, and generics became marketed in 
2017. Nilotinib and dasatinib are reimbursed both in first- and second line of CML therapy 
since 2014-2015.   
TKIs are the standard of care in the treatment of chronic phase. Imatinib, nilotinib and 
dasatinib are currently reimbursed in Hungary as first line treatment. If resistance or 
intolerance is developed, beside previously listed second generation TKIs even bosutinib or 
ponatinib are recommended by the national Finance Protocol.3, 8 Bosutinib is not reimbursed 
in first line. Ponatinib is available in Named Patient Program (NPP) in later lines.  
Few publications exist on real-world treatment pattern from Western Europe6,7, but there is 
no such data from Hungary so far. Given the population, genetic, cultural, health condition 
and health care system differences on country and geographic region level, it is important to 
investigate real world data regionally.  
 
8. RESEARCH QUESTION AND OBJECTIVES 
The objectives of this study are to describe patient demographics, clinical and disease 
characteristics and treatment patterns of CML in Hungary and evaluate how these key 
features have changed in investigated time period. 
The primary endpoint is overall survival of CML patients treated with tyrosine kinase 
inhibitors in Hungary. 
- 
OS of all enrolled patients  
- 
OS by sequence pattern (where patients meet the inclusion criteria and the available 
data allows the analysis). Sequence patterns according the actual marketing 
authorisation of the investigated products are listed in the Table 1.  
- 
OS by the number of treatment lines 
 
Secondary objectives are  
x the incidence and prevalence of CML in Hungary total, and per year during the 
investigated period 
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x patient demographics (age, gender) of all enrolled CML patients  
x patient comorbidities based on Charlson comorbidity index 
o average number of patients’ comorbidities at baseline (start of the 1L 
treatment) and at different treatment lines (at the point of treatment switch 
regardless of the TKIs) 
o most frequent comorbidities for each investigated TKI total and by treatment 
lines (investigated comorbidities listed in Table 2.) 
o average number of patients’ comorbidities at the start of different treatment 
lines (1L, 2L, 3L etc) by investigated TKIs regardless of the previous 
treatment 
o patient number with 0, 1, 2 or more than 2 comorbidities at the start of 
different treatment lines (1L, 2L, 3L etc) by investigated TKIs regardless of 
the previous treatment 
x distribution of the investigated TKI therapies by treatment lines: 1L, 2L, 3L, 4L etc.  
x description of real-life treatment sequences as listed in the Table 1. 
x description of the length of each therapeutic line by investigated TKIs during real-life 
use and dose-intensity in each treatment line by TKIs 
The use of tyrosine kinase inhibitors in the study is on label in accordance with the EMA and 
the Hungarian marketing authorisation. 
9. RESEARCH METHODS  
9.1. Study design  
The study is a retrospective, non-interventional study to evaluate Chronic Myeloid Leukemia 
treatment landscape and real-life treatment outcomes in Hungary using the database of the 
National Health Insurance Fund of Hungary. The NHIF database is a nationwide insurance 
system covering close to 100% of the Hungarian population, which collects patient ID and 
ICD-10 code information about all in- and out-patient visits, as well as about all prescription 
of drugs which are reimbursed in Hungary. All data are anonymized at data extraction, and 
we use non-identifiable data at further analyses. 
9.2. Setting 
In our study, we retrospectively examine the characteristics of CML treatment, treatment 
patterns, and duration of treatments, focusing on tyrosine kinase inhibitor treatments by 
analysis on a NHIF database. From 01 January 2011, all patients treated with tyrosine kinase 
inhibitors (imatinib, dasatinib, nilotinib, bosutinib, ponatinib) will be included in the study 
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until the date of data closure (expected until 30 June 2020), this is approximately 1000-1200 
patients from all Hungarian Hematology centers. Data collection starts 2 years before 
(01 January 2009). The analysis period, the years of 2009-2010, will be used as reference 
years in order to detect only the real starting therapies from 2011(Figure 1). 
Figure 1. Study design 
 
9.2.1. Inclusion criteria 
Patients must meet all of the following inclusion criteria to be eligible for inclusion in the 
study: 
1. Female and male patients diagnosed with chronic myeloid leukemia 
2. Patients receiving tyrosine kinase inhibitor therapy under the terms of the current 
marketing authorization 
9.2.2. Exclusion criteria 
Patients meeting any of the following criteria will not be included in the study: 
1. Patients receiving TKI for non-CML diagnoses 
9.3. Variables 
 
Variable 
Role 
Data source(s) 
Operational 
definition 
Age 
Demographic 
characteristics 
Medical record 
Date of birth 
Sex 
Demographic 
characteristics 
Medical record 
Male /Female 
Retrospective data collection period 
01 Jan 2009 – 30 June 2020 
Study period 
01 January 2011– 30 June 2020 
Pre-exploratory 
period 
01 January 2009 –  
31 December 2010 
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Incidence 
Disease 
characteristic 
Medical record 
Number of patients 
newly diagnosed 
with CML during 
the defined period 
Length of treatment 
by lines and total 
Disease 
characteristic 
Medical record 
Time from 1st CML 
TKI prescription to 
time to prescription 
of another CML TKI  
Prevalence 
Disease 
characteristic 
Medical record 
Number of all CML 
patients during the 
defined study period 
Overall survival 
Disease 
characteristics 
Medical record 
Time from first 
diagnosis of CML 
until death 
Comorbidities at 
baseline 
Patient 
characteristics 
Medical record 
Comorbidities coded 
based on the ICD-10 
(listed in Table 2.) at 
the start of first TKI 
treatment for CML. 
Comorbidities at 
different treatment 
lines 
Patient 
characteristics 
Medical record 
Comorbidities coded 
based on the ICD-10 
(listed in Table 2.) at 
switch of TKI 
treatment for CML 
2nd line therapy 
Treatment 
characteristic 
Medical record 
Use of another CML 
TKI therapy after 1st 
line  
1st line therapy  
Treatment 
characteristic 
Medical record 
1st prescription of 
any CML TKI after 
first CML diagnosis 
Length of treatment 
by lines 
Treatment 
characteristics 
Medical record 
Lengths of treatment 
analysed in each line 
Number of treatment 
lines 
Treatment pattern 
Medical record 
Number of therapy 
lines used TKI for 
CML 
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TKI distribution by 
therapeutic lines 
Treatment pattern 
Medical record 
Distribution of TKI 
therapies among all 
patients in the same 
line of therapy 
 
9.4. Data sources  
National Health Insurance Fund’s prescribing and in/outpatient database will be used for the 
analysis. The database is nationwide, electronic and includes all treated patients. From 01 
January 2011, all patients treated with tyrosine kinase inhibitors (imatinib, dasatinib, 
nilotinib, bosutinib, ponatinib) will be included in the study until the date of data closure 
(expected until 30 June 2020). Data collection starts 2 years before the analysis period, the 
years of 2009-2010 will be used as reference years in order to detect only the real starting 
therapies from 2011. 
9.5. Study size 
Approximately 1000-1200 patients’ data will be analysed who were treated with TKI 
(imatinib, dasatinib, nilotinib, bosutinib, ponatinib) for CML between 01 January 2011 until 
the date of data closure (expected until 30 June 2020) will be included in the study. Data 
collection starts 2 years before the analysis period, the years of 2009-2010 will be used as 
reference years in order to detect only the real starting therapies from 2011. 
9.6. Data management  
The mathematical algorithm required for analysis is designed and provided by RxTarget 
Statistical Programming and Analysis Ltd. using SQL programming language based on a 
preliminary study plan. The algorithm is run by experts at NHIF using primary social 
security number-level data from selected patients. Anonymized data is provided by NHIF in 
an aggregated form without any individual identification parameter based on a specific 
permit, with the strict consideration of data protection rules. Descriptive statistics will be 
applied for the variables, and no hypothesis is tested.  
National Health Insurance Fund’s prescribing and in/outpatient database will be used for the 
analysis. The database is nationwide, electronic and includes all treated patients. The 
National Health Insurance Fund provides access to the database to run predefined algorithm. 
The database is owned by the National Health Insurance Fund. 
Descriptive statistics will be applied for the variables. This includes means, median, range, 
percentage etc. The data of all patients treated with tyrosine kinase inhibitors for chronic 
myeloid leukemia in Hungary will be studied. 
 
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9.7. Data analysis  
Descriptive statistics will be applied for the variables. This includes means, median, range, 
percentage etc. The data of all patients treated with tyrosine kinase inhibitors for chronic 
myeloid leukemia in Hungary will be studied.  
Hungary provides universal healthcare for its citizens, thanks to the single-payer public 
system, the NHIF database contains all prescription claims data of all reimbursed medicinal 
products, all outpatient and inpatient data from all Hungarian patients. 
For the analysis we use electronically stored data from the NHIF database, which display 
demographic data, previous treatments’ and concurrent treatments’ data, coded by ICD-10, 
ICHI and drug TTT codes using a predefined algorithm. Data are provided in anonymized 
form by the NHIF.  
The demographics, treatment lines and treatment sequences with tyrosine kinase inhibitors 
will be investigated. Patients’ comorbidities will also be investigated. 
1. Epidemiology: age, sex, treatment lines, incidence, prevalence, mortality. For 
studying the epidemiology based on the NHIF database the following definitions will 
be used: 
 
Patient population is defined as patient is coded with ICD-10 C92 between 
January 2009 and June 2020, has data either in outpatient or in inpatient system 
and/or have a TKI (imatinib, bosutinib, dasatinib, nilotinib or ponatinib) 
prescribed. The analysis period defined as January 2011- June 2020 (January 
2009-December 2010 used as pre-exploratory period.)  
 
Incidence is defined as patients newly diagnosed during a given period. 
 
Point prevalence is defined as patients who were already diagnosed before the 
first day of the given period (up to 31 December 2008) and were still living on the 
first day of the given period. They are patients who are still diagnosed on the first 
day of the given period (cross-sectional view). 
 
Period prevalence is defined as patients who were already diagnosed before the 
first day of the given period (up to 31 December 2008) or were newly diagnosed 
during a given period and were still living on the first day of the given period. 
They are the sum of incident and point prevalent patients (longitudinal-section 
view). 
 
Dead patient is defined as patient who was diagnosed before the first day of the 
given period (up to and including 31 December 2008) or during the given period 
and died during the given period. 
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 
Number of patients treated: patients who were diagnosed and also received TKI 
treatment at least once during the investigated period, and the TKI treatment was 
prescribed with C92 ICD-10. The data are also presented in line setting: the first 
target product (TKI) received is the 1st line treatment, the second target product 
(TKI) is the 2nd line treatment, and so on.  
2. Length of each treatment line, overall survival (OS)  
 
Medication (TKIs) persistence will be analyzed in the whole investigated 
population and based on treatment lines. Patients will be enrolled who had first 
prescription of TKI during the investigated period. Data will be available both 
censored at death and not censored. Median and 95% CI will also be used to 
calculate persistence. 
o Persistence of the target product: the patient's therapy is stopped when the 
target product (TKI) is depleted according to our calculations 
o Persistence of total CML therapy: the patient's therapy is stopped when the 
patient uses none of the target product (TKI) 
 
Length of treatment line will be calculated and demonstrated with Kaplan-Meier 
curve. Progression considered as change of therapy line or death.  
 
Switch in treatment lines determined when the prescribed TKI for CML changed. 
Therapy switch can be established due to suboptimal treatment response, 
treatment failure or treatment intolerance. The background of the TKI switch 
cannot be analyzed using the NHIF’s database.  
 
Overall survival rate: the probability that a patient is still alive for a certain period 
of time (% of patients). OS will be demonstrated with Kaplan-Meier curve. The 
method provides information on the survival of patients in a particular sequence 
of treatment. Patients will be enrolled who had first prescription of TKI during the 
investigated period. 
o Overall survival by treatment sequences, as defined in Table 1. based on 
the actual marketing authorization of the target TKIs 
Table 1. Treatment sequence options.  
  
1L 
2L 
3L 
4L 
5L 
1 
imatinib 
nilotinib 
dasatinib 
bosutinib 
ponatinib 
2 
ponatinib 
bosutinib 
3 
ponatinib 
dasatinib 
bosutinib 
4 
bosutinib 
dasatinib 
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5 
bosutinib 
dasatinib 
ponatinib 
6 
ponatinib 
dasatinib 
7 
dasatinib 
nilotinib 
bosutinib 
ponatinib 
8 
ponatinib 
bosutinib 
9 
bosutinib 
nilotinib 
ponatinib 
10 
ponatinib 
nilotinib 
11 
ponatinib 
bosutinib 
nilotinib 
12 
nilotinib 
bosutinib 
13 
bosutinib 
nilotinib 
dasatinib 
ponatinib 
14 
ponatinib 
dasatinib 
15 
dasatinib 
ponatinib 
dasatinib 
16 
nilotinib 
ponatinib 
17 
nilotinib 
dasatinib 
bosutinib 
ponatinib 
 
18 
ponatinib 
bosutinib 
 
19 
bosutinib 
dasatinib 
ponatinib 
 
20 
dasatinib 
nilotinib 
bosutinib 
ponatinib 
 
21 
ponatinib 
bosutinib 
 
22 
bosutinib 
nilotinib 
ponatinib 
 
23 other 
 
Table 1. contains predefined treatment sequence options based on the products EMA label. 
However real-world sequences may differ due to the reimbursement, NPP, etc. in Hungary. 
Other defined as all other sequence not listed in the table and will be detailed based on the 
results of the analysis.   
3. Comorbidities (based on Charlson comorbidity index10), number of comorbidities on 
each line: 
 
We determine what comorbidities existed in patients at the time of diagnosis of 
CML. In addition, the distribution of CML patients without comorbidity, with 1 
or 2 or more comorbidities will be analyzed. 
 
Investigation of the comorbidities is based on the Charlson comorbidity index as 
following: 
Table 2. Definitions of comorbidities 
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Condition 
Definition upon ICD-10  
Ischemic heart disease 
I2000-I2590 
Congestive heart failure  
I50 
Arrythmiac condition (including AF) 
I44, I45, I47, I48, I49 
Hypertonia 
I10, I11, I12, I13, I15 
Peripheral vascular disease  
I70, I73, R02, Z958, Z959 
Cerebral vascular accident 
I60, I61, I62, I63, I65, I66, G450, G451, 
G452, G458, G459, G46, I64, G454, 
I670, I671, I672, I674, I675, I676, I677 
I678, I679, I681, I682, I688, I69 
Dementia 
F01, F02, F03, F051 
Pulmonary disease (lower tract) 
J4 
Connective tissue disorder  
M32, M34, M332, M053, M058, M059, 
M060, M063, M069, M050, M052, 
M051, M353 
Peptic ulcer  
K25, K26, K27, K28 
Liver disease  
K7 
Severe liver disease 
K729, K766, K767, K721 
Diabetes 
E10-14 
Diabetes complications  
E102, E112, E132, E142 E103, E113, 
E133, E143 E104, E114, E134, E144 
Paraplegia 
G81 G041, G820, G821, G822 
Renal disease  
N03, N052, N053, N054, N055, N056, 
N072, N073, N074, N01, N18, N19, N25 
Other cancer 
C 
Metastatic cancer 
C77, C78, C79, C80 
HIV 
B20, B21, B22, B23, B24 
Thromboembolic events  
I26, I800-I8290 
Metabolic disorders 
E7800,  E7810,  E7820, E7830, E7840, 
E7850, E10-E14,  
 
4. Dose intensity: The average doses of the investigated TKIs will be analysed by 
therapeutic lines regardless of the previous and following treatment. 
 
9.8. Limitations of the research methods 
Since the NHIF database only contains reimbursed prescription claims data, non-reimbursed 
claims (e.g. clinical trial patients or privately reimbursed treatment which is uncommon in 
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Hungary). The database does not contain laboratory data (e.g. neutropenia, anemia, etc.), 
patient parameters (e.g. body mass index), patient symptoms (e.g. fatigue) or pathological or 
molecular features of CML (depth of treatment response g. CCR, MR, MR4.0, MR4.5, etc.) 
The database does not contain information on adverse events. The database does not include 
data on the background of therapy switch (suboptimal treatment response, treatment failure or 
treatment intolerance) hence the progression free interval cannot be investigated only the 
length of therapy per lines. 
Biases:  
Selection bias: Given the retrospective data collection, the study population enrolled in this 
study is based on treating physician clinical decision and selection. 
Information bias: Data provided by the NHIF database based on electronic health records 
coded, thus it has limitations, and certain information of pathological or molecular features of 
CML is not coded. 
9.9. Other aspects 
Not applicable.  
10. PROTECTION OF HUMAN SUBJECTS 
10.1. Patient information  
This study involves data that exist in anonymized structured format and contain no patient 
personal information.  
 
10.2.  Patient consent 
As this study involves anonymized structured data, which according to applicable legal 
requirements do not contain data subject to privacy laws, obtaining informed consent from 
patients by Pfizer is not required. 
10.3. Institutional review board (IRB)/Independent ethics committee (IEC) 
There must be prospective approval of the study protocol, protocol amendments, and other 
relevant documents (e.g., informed consent forms if applicable) from the relevant IRBs/IECs.  
All correspondence with the IRB/IEC must be retained.  Copies of IRB/IEC approvals must 
be forwarded to Pfizer. 
The study protocol approved by Hungarian National Institute of Pharmacy and Nutrition, and 
by Medical Research Council Ethical Committee 
10.4. Ethical conduct of the study 
The study will be conducted in accordance with legal and regulatory requirements, as well as 
with scientific purpose, value and rigor. 
 
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The study protocol approved by Hungarian National Institute of Pharmacy and Nutrition, and 
by Medical Research Council Ethical Committee. 
  
11. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS  
This study involves data that exist as structured data by the time of study start. 
 
In these data sources, individual patient data are not retrieved or validated, and it is not 
possible to link (i.e., identify a potential association between) a particular product and 
medical event for any individual.  Thus, the minimum criteria for reporting an adverse event 
(AE) (i.e., identifiable patient, identifiable reporter, a suspect product, and event) cannot be 
met. 
Hungarian DSU is informed about the study.  
 
12. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS 
In the event of any prohibition or restriction imposed (e.g., clinical hold) by an applicable 
competent authority in any area of the world, or if the party responsible for collecting data 
from the participant (RxTarget Statistical Programming and Analysis Ltd.) is aware of any 
new information which might influence the evaluation of the benefits and risks of a Pfizer 
product, Pfizer should be informed immediately.   
Peer reviewed journal publication is planned with the authorship of the investigators and 
statistics partner.  
 
13. REFERENCES 
1. 'HPHWHU-HWDO$NUyQLNXVP\HORLGOHXNpPLDNRUV]HUĦGLDJQRV]WLNiMDpVNH]HOpVH
Orvosi Hetilap Volume 157: Issue 37  https://doi.org/10.1556/650.2016.30521  
2. Hochhaus A et al. European LeukemiaNet 2020 recommendations for treating chronic 
myeloid leukemia Leukemia 2020  https://doi.org/10.1038/s41375-020-0776-2  
3. Gaál-Weisinger et al. Újdonságok és tapasztalatok a krónikus mieloid leukémia 
tirozinkináz-gátló kezelésében; Magyar Onkológia 61:67–74, 2017 
4. Pfirrmann et al. Prognosis of long-term survival considering disease-specific death in 
patients with chronic myeloid leukemia; Leukemia volume 30, pages48–56(2016) 
5. García-Gutiérrez et al. Tyrosine Kinase Inhibitors Available for Chronic Myeloid 
Leukemia: Efficacy and Safety Front Oncol. 2019; 9: 603 
6. Breccia et al. How many chronic myeloid leukemia patients who started a frontline 
second-generation tyrosine kinase inhibitor have to switch to a second-line treatment? 
A retrospective analysis from the monitoring registries of the italian medicines agency 
(AIFA); Cancer Medicine. 2020;00:1–6.  
 
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7. Hoffman et al, The EUTOS population-based registry: incidence and clinical 
characteristics of 2904 CML patients in 20 European Countries; Leukemia (2015) 29, 
1336–1343 
8.   9  (0 UHQGHOHW D ILQDQV]tUR]iVL HOMiUiVUHQGHNUĘO 
https://net.jogtar.hu/getpdf?docid=A1000031.EUM&targetdate=fffffff4&printTitle=
31/2010.+%28V.+13.%29+E%C3%BCM+rendelet&referer=http%3A//net.jogtar.hu/jr
/gen/hjegy_doc.cgi%3Ffdocid%3D00000001.TXT 
9. García-Gutiérrez et al. Tyrosine Kinase Inhibitors Available for Chronic Myeloid 
Leukemia: Efficacy and Safety Front Oncol. 2019; 9: 603. 
10. Sundararajan et al. New ICD-10 version of the Charlson Comorbidity Index predicted 
in-hospital mortality Journal of Clinical Epidemiology 57 (2004) 1288–1294 
 
14. LIST OF TABLES  
Table 1. Treatment sequence options. 
Table 2. Definitions of comorbidities 
15. LIST OF FIGURES 
Figure 1. Study design 
ANNEX 1. LIST OF STAND ALONE DOCUMENTS 
None 
ANNEX 2. ADDITIONAL INFORMATION 
Not applicable. 
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