The Russian Registry of Patients With Severe Asthma to Collect Anonymous Long-term Evidence
Conditions: Severe Asthma
Sponsor: Interregional Public Organization, Russian Respiratory Society

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RSAR Registry Protocol  
 
D-code: D3250R00040 
 
Tracking number: ESR-17-
13479 
 
 
 
Version 1.2 
 
 
Date 07.2018 г. 
 
 
 
 
 
 
 
 
 
 
 
 
Russian Severe Asthma Registry: Protocol 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 

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Content 
List of abbreviations……………………………………………………………………………4 
RESPONSIBLE PARTIES……………………………………………………………………..5 
PROJECT DELIVERY COLLABORATORS…………………………………………………5 
    RSAR CORE STEERING COMMITTEE……………………………………………………...7 
    PROTOCOL SYNOPSIS……………………………………………………………………….10 
    MILESTONES……………………………………………………………………………….....11 
1.0. BACKGROUND & RATIONALE ......................................................................................13 
1.1. Background...........................................................................................................................13 
1.2. Rationale ...............................................................................................................................15 
2.0. OBJECTIVES.......................................................................................................................16 
2.1. Primary Objective(s).............................................................................................................16 
2.2. Secondary Objective(s).........................................................................................................16 
3.0. METHODOLOGY ...............................................................................................................21 
3.1. Registry Design...................................................................................................................222 
3.2. Draft Country Initiation ......................................................................................................222 
3.3. Data Collection ...................................................................................................................233 
3.4. Patient Population...............................................................................................................233 
3.5. Inclusion Criteria ................................................................................................................244 
3.6. Exclusion Criteria ..............................................................................................................255 
3.7. Registry Follow-up ...............................................................................................................25 
3.8. Consent Procedures.............................................................................................................255 
4.0. DATABASE .......................................................................................................................255 
4.1. Data Acquisition .................................................................................................................255 
4.2. Data Management ...............................................................................................................255 
4.3. Registry Coding ..................................................................................................................266 
4.4. Statistic analysis….………………………………………………………………..……….27 
4.5. Main analysis ……………………………………………………………………………....27 
4.6. Further analysis…………………………………………………………………………..…28 
4.7. Quality control………………………………………………………………………….......28 
4.8. Limitations of study methods………………………………………………………………29 

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5. 0. OTHER ASPECTS OF THE STUDY …….………………………………………………30 
5.1. Data quality assurance ………..……………………………………………………………30 
5.2. Data registration……………………………………………………………………………31 
5.3. Data ownership ...................................................................................................................311 
5.4. Data access and subordination............................................................................................311 
 6 ADVERSE EVENTS/REACTIONS DATA COLLECTION AND REPORT…………...….33 
6.1. 
Definitions…………………………………………………………………………………...….33 
6.1.1. Definition of adverse event (AE)…………….……………………………………….…..33 
6.1.2. Definition of serious adverse  event (SAE)……………………………………….……...34 
6.1.3. Definition of adverse reaction (AR)……………………………………………………...34 
6.2. Adverse events data collection…………….……………………………………………….34 
6.3. Reporting on the adverse events……………………………………………………………36 
6.3.1. Reporting on the adverse events spontanious reports…………………………………….36 
6.3.2. Recording of the adverse events spontaneous reports……………….…………………...36 
7 Publication plan……….............................................................................................................37 
8. REFERENCES ........................................................................................................................38 
9. APPENDIX: Core Variables....................................................................................................40 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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List of abbreviations 
BA – Bronchial asthma  
RSAR – Russian severe asthma registry 
SA - severe bronchial asthma 
GINA - Global Initiative for asthma (Global Strategy for Asthma Management and Prevention) 
eCRF - electronic case report form 
ICS - inhaled glucocorticosteroids 
LABA - long acting β-agonists 
LAMA – long-acting antimuscarinic agents 
COPD - chronic obstructive pulmonary disease 
EDS - electronic data logging system 
LLC "RSMI" - Limited Liability Company "Regional United System of Medical Informatization" 
SNOMED CT - the dictionary of the systematized nomenclature of medical clinical terms 
IHTSDO - organization for the development of international health terminology 
RAACI - Russian Association of Allergology and Clinical Immunology 
QMS - Quality Management System 
SOP - standard operating procedure 
NEC - National Ethics Committee 
RRS - Russian Respiratory Society 
CBD - The central database  
IPF - idiopathic pulmonary fibrosis 
EMC - emergency medical care 
Treatment and prophylactic institution 
ACQ-5 - Asthma Control Questionnaire (questionnaire for asthma control, 5-question version) 
ACT - Asthma Control Test (Asthma Control Test) 
OCS - oral corticosteroids 
LTRA - a leukotriene receptor antagonist 
 
 
 
 
 
 

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RESPONSIBLE PARTIES 
1. Limited liability company "Regional United Medical Informatization System" (LLC "RSMI") 
within the framework of the project of the Russian Severe Asthma Registry (RSAR) takes 
responsibilities to develop and implement software for the work of physicians-investigators 
within the RSAR creating a database of patients with severe bronchial asthma (SA) on the 
territory of the Russian Federation on an already existing software company product, named 
"Medical online platform ROSMED.INFO" protected according to the current legislation of 
Russian Federation.  
2. The limited liability company "Regional United Medical Informatization System" within the 
framework of the project RSAR assumes the responsibility to perform the functions of a 
personal data operator of physicians and patients participating in the study. 
3. Limited liability company "Regional United Medical Informatization System" within the 
RSAR project assumes the responsibility for management and administration, including 
information and technical support, of the project during the whole period of the study. 
4. NPO "Russian Respiratory Society" within the project of RSAR assumes the obligation to 
contribute to the development of indicators of the Electronic Database, to supervise the 
development of principles and parameters of patient questioning, to create reference materials 
for patients and/or their legal representatives, to supervise the development of  CRF, 
repeat/monitoring visits and other clinical parameters, correlating with the issues of 
prophylaxis, management, dynamic clinical monitoring of the health status and rehabilitation 
process of patients with severe asthma, but not limited to these areas of activity. 
5. Russian Association of Allergology and Clinical Immunology (RAACI) within the project of 
RSAR assumes the obligation to contribute to the development of indicators of the Electronic 
Database, to supervise the development of principles and parameters of patient questioning, to 
create reference materials for patients and/or their legal representatives, to supervise the 
development of  CRF, repeat/monitoring visits and other clinical parameters, correlating with 
the issues of prophylaxis, management, dynamic clinical monitoring of the health status and 
rehabilitation process of patients with severe asthma, but not limited to these areas of activity. 
 
PROJECT DELIVERY COLLABORATORS  
LLC RSMI specializes in conducting medical observational non-interventional prospective 
multicenter studies. 
LLC "RSMI" owns the patented Russian software product "Medical online platform 
ROSMED.INFO", which serves as a base for development and maintenance of observational 
studies (registries) on various nosologies, including severe asthma. 
NPO "Russian Respiratory Society" (IPO "RRS") is a non-profit public organization that unites on 
a physician of various specialties engaged in the management of patients with various 
pulmonological diseases. Among the members of the NPO "RRS" there are leading Russian 
opinion leaders, the main freelance specialists of the Ministry of Health of the Russian Federation, 

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the main non-staff regional specialists in the field of respiratory / allergic diseases, who possess 
extensive experience in development and conductance of clinical trials. The activities of NPO RRS 
focus on the establishment of best practices and standards in pulmonology, aimed on improvement 
of the quality of research in real practice for all stakeholders, including patients, clinical practice 
specialists, representatives of the pharmacological industry and law enforcement / regulatory 
bodies.  

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RSAR CORE STEERING COMMITTEE 
Russian research working groups are a network of researchers working together to identify 
unsatisfied research objectives through non-randomized controlled trials and to implement high-
quality academic research in this field. The main members of the RSAR Steering Committee 
jointly conduct the expertise, using scientific data and experience working with databases and 
research, forming the necessary elements of the work for the initiative group of the Registry 
(RSAR). 
RSAR Steering Committee is headed by Belevsky AS, MD, professor of the pulmonology 
department of the Higher Educational Institution of Higher Professional Education "Russian 
National Research Medical University named after N.I. Pirogov "of the Ministry of Health, 
Chairman of the Moscow branch of the Russian Respiratory Society, President of the Russian 
Respiratory Society, President of the Association of Russian-Speaking Experts in Respiratory 
Medicine and Nenasheva N M, MD, professor of the Federal state budget educational institution of 
post-graduate professional education Russian medical academy of continuous professional 
education. 
Below are the names of the main experts, council members who will take part in the 
implementation of the Registry (RSAR). 
 
Responsible position within 
the register 
Organization name 
Person name 
Chief Scientific Curator 
Higher 
Educational 
Institution 
of 
Higher 
Professional 
Education 
"Russian National Research 
Medical University named 
after N.I. Pirogov "of the 
Ministry of Health 
Belevsky 
Andrey 
Stanislavovitch 
Chief Scientific Curator 
Federal 
state 
budget 
educational 
institution 
of 
post-graduate 
professional 
education Russian medical 
academy 
of 
continuous 
professional education 
Nenasheva 
Natalya 
Mikhailovna 
Scientific adviser 
FSBO "Research Institute of 
Pulmonology of FMBA of 
the Russian Federation" 
Avdeev Sergey Nikolaevitch 
Scientific adviser 
Higher Educational 
Institution of Higher 
Professional Education 
Aisanov Zaurbek 
Ramazanovitch 

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"Russian National Research 
Medical University named 
after N.I. Pirogov "of the 
Ministry of Health 
Scientific adviser 
Scientific Research Institute 
of Pulmonology of the First 
St. Petersburg State Medical 
University named after 
academician I.P. Pavlov 
Titova Olga Nikolaevna 
Scientific adviser 
Department of pulmonology 
of Federal State Budget 
Institution of Higher 
Education “North-West State 
Medical University named by 
I.I. Mechnikov” of Ministry 
of Health of the Russian 
Federation 
Emelyanov Alexander 
Viktorovich 
Scientific adviser 
FSBO SSC Institute of 
Immunology of FMBA of 
Russia 
Ilyina Natalia Ivanovna 
Scientific adviser 
FSBO SSC Institute of 
Immunology of FMBA of 
Russia 
Kurbacheva Oksana 
Mikhailovna 
Scientific adviser 
Federal State Funded 
Educational Institution of 
Higher Education I.M. 
Sechenov First Moscow State 
Medical University under the 
Ministry of Health of the 
Russian Federation (I.M. 
Sechenov First MSMU) 
Geppe Natalia Anatolievna 
Scientific adviser 
Federal 
State 
Funded 
Educational 
Institution 
of 
Higher 
Education 
I.M. 
Sechenov First Moscow State 
Medical University under the 
Ministry of Health of the 
Russian 
Federation 
(I.M. 
Malakhov Alexander 
Borisovich 

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Sechenov First MSMU) 
 

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PROTOCOL SYNOPSIS 
 
The Russian registry of patients with severe asthma to collect anonymous long-term evidence. 
The Russian Severe Asthma Registry is a Russian initiative to collect anonymous long-term 
evidence for patients with severe asthma in Russia. The RSAR initiative is realized under the efforts 
of the Interregional Public Organization "Russian Respiratory Society" and LLC "RSMI" with the 
sponsorship of "AstraZeneca Pharmaceuticals" LLC. 
The developed RSAR electronic database is a Russian software product that meets the current 
requirements of the Russian legislation in the field of working with personal data and the 
implementation of similar observational studies. 
Participating researchers also agree to grant access and share anonymous data at the patient 
level as part of the work to implement the RSAR initiative. Participants will provide high-quality 
data for the development of data sets for research, approved by the Russian Respiratory Society 
(RPO), which has priority in owning and implementation in scientific field of the gained data. Based 
on ethical, legal and regulatory authorizations, anonymous data will be collected in the Central 
Database (CDB) on respiratory diseases (referred to here as the RSAR database) to create sets of 
important data and the necessary analysis. CDB is part of the software "Medical online platform 
ROSMED.INFO". 
 
 

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MILESTONES 
Period 01/2018 – 12/2018 
Invitation of physicians-investigators to the project, the 
initiation of the RSAR work 
03/2018 
Project working group formation of curators, sponsors, 
medical experts 
 
Programming of the individual patient case report form 
(child (from 12 years) and adult versions) 
 
The beginning of filling in eCRF by the physicians-
investigators  
03/2018 
Project management, filling of eCRF by investigators 
03/2018-12/2018 
Organization of the database and user’s personal 
information protection  
 
03/2018-12/2018 
Data base administration 
03/2018-12/2018 
Data entry in CRF by investigators 
03/2018-12/2018 
Analytic report 
07/2018 and 
12/2018 
 
Period 01/2019 – 12/2019 
Project management, filling of eCRF by investigators 
01/2019-12/2019 
Organization of the database and user’s personal 
information protection 
 
 
01/2019-12/2019 
Data base administration 
01/2019-12/2019 
Data entry in eCRF by investigators 
01/2019-12/2019 
Analytic report 
06/2019 and 
12/2019 
 
Period 01/2020 – 12/2020 
Project management, filling of eCRF by investigators 
01/2020-12/2020 
Organization of the database and user’s personal 
information protection 
 
 
01/2020-12/2020 
Data base administration 
01/2020-12/2020 
Data entry in eCRF by investigators 
01/2020-12/2020 
Analytic report 
06/2020 and 
12/2020 
 
Period 01/2021 – 12/2021 
Project management, filling of eCRF by investigators 
01/2021-12/2021 
 

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Organization of the database and user’s personal 
information protection 
 
 
01/2021-12/2021 
Data base administration 
01/2021-12/2021 
Data entry in eCRF by investigators 
01/2021-12/2021 
Analytic report 
06/2021 and 
12/2021 
 
Period 01/2022 – 12/2022 
Project management, filling of eCRF by investigators 
01/2022-12/2022 
Organization of the database and user’s personal 
information protection 
 
 
01/2022-12/2022 
Data base administration 
01/2022-12/2022 
Data entry in eCRF by investigators 
01/2022-11/2022 
Analytic report 
06/2022 and 
12/2022 
 
 
Total taking into 
account all receipts 
 
 
1.0. BACKGROUND & RATIONALE 
 
1.1. BACKGROUND 
 
Severe asthma 
BA is a heterogeneous disease characterized by chronic inflammation of the upper respiratory 
tract. BA affects 5-15% of people worldwide and its prevalence has increased in the last decade 
[1]. Asthma management to achieve optimal control and prevention of exacerbations using a step 
approach in pharmacotherapy is detailed in national and international guidelines [2]. Nevertheless, 
the question of precise statistical data on the true incidence of severe asthma remains open. In the 
study “NIKA" [19], an assessment of the level of asthma control in 1,000 patients from 26 
outpatient clinics in 12 cities of the Russian Federation was carried out. The level of control was 
assessed clinically and using specialized questionnaires ACQ-5 and ACT. As a reference method 
of assessment, the evaluation of symptoms and spirometry parameters were performed in 
accordance with the GINA criteria. In general, controlled BA was noted in 23% of patients, partial 
control and uncontrolled asthma - in 35% and 42%, respectively. When diagnosing the level of 
control, physicians made mistakes in 49% of cases. The use of the ACQ-5 and ACT tests produced 
a higher and approximately comparable quality of the control evaluation (64% and 60% of 

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adequate assessments), but the ACT had a systematic error in overestimating the level of control of 
asthma compared to the GINA criteria. Despite the availability and use of preventive treatment, 
the costs associated with asthma are increasing, and affect both individuals and health facilities. 
Regardless of the improved understanding of the nature of the disease, the factors that affect the 
loss of control are still unclear and largely remain hypothetical. Part of the difficulties lies in 
determining the severity of asthma, assessing its symptoms and their intensity. 
  
The program of the study of severe asthma revealed various subgroups of severe asthma on 
the basis of changing clinical manifestations, pathophysiological mechanisms and biomarkers [4)]. 
In this study, 438 patients with asthma were studied. The authors found that patients with severe 
asthma tend to be older with a longer illness, daytime symptoms, intensive use of emergency 
therapy, sinusitis and pneumonia. Despite the fact that lung function was reduced in these patients, 
most patients had reversibility of bronchial obstruction after taking the bronchodilator [4]. A better 
understanding of the mechanisms of BA should make an obvious improve in patients’ 
management. 
 
Biomarkers and phenotypes in SA management prognosis of treatment response. 
Patients with BA of mild to moderate severity can control symptoms with increasing doses 
of inhaled glucocorticosteroids (ICS) in combination with long-acting β-agonists (LABA) or 
leukotriene antagonists. In patients with more severe asthma and frequent exacerbations, this 
treatment may not be sufficient to control symptoms and prevent exacerbations. Despite the 
growing range of medicines and improved design of inhalers and patient care, deaths continue to 
increase due to asthma, with an increase of 17% between 2014 and 2015 only in Great Britain [6]. 
The novel methods of treatment can help to fight this tendency. However, new therapies are often 
expensive, and there is a need to identify patients who can get the most benefit from such 
treatment. 
Biomarkers assessment now is an important tool used to achieve optimal management of 
patients with BA, especially, SA. Biomarkers can be used to study the function of organs or other 
health parameters [7], providing information on the severity of the disease and the predicted 
outcomes of treatment, as well as on choosing the most effective treatment for particular patients. 
For example, patients with severe BA and significant eosinophilia have a greater risk of 
exacerbating [8]. Eosinophils can affect the mucous of the upper respiratory tract, provoking 
epithelial damage and changes in the structure of the upper respiratory tract in asthma, thus 
affecting the severity of the disease. Studies have shown that peripheral blood eosinophilia can be 
used as a biomarker to predict the effectiveness of anti-IL-5 therapy in the prevention of 
exacerbations [9, 10, 11]. Recent data suggest that other variables, as like eosinophils, can predict 
asthma exacerbations. These include local eosinophilia, as well as nasal polyps and concomitant 
diseases, including diabetes mellitus [12]. 
Like the number of eosinophils, an increase in the exhaled nitric oxide fraction (FeNO) helps 
to predict the exacerbations of asthma (13). An increase in FeNO is considered a clinical 
biomarker of inflammation. Nevertheless, the values of FeNO are affected by many associated 

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factors, including tobacco smoking, obesity and the use of glucocorticosteroids [7]. There is a need 
for a better understanding of when FeNO plays the role of a biomarker in BA. In particular, a 
combination of data on FeNO and eosinophils of blood can help in predicting who will benefit 
greatly from the biological therapy. Moreover, a significant proportion of patients with asthma 
also have an allergic sensitization. The presence of allergen-specific IgE along with exposure to 
the allergen are known risk factors for the severity of asthma, which along with the content of 
FeNO and eosinophils of blood allows to predict the response to treatment against IgE [7]. 
 
Identification of biomarkers can improve understanding of the phenotype of severe asthma. 
This progress in understanding the characteristics of the disease can lead to improved management 
of SA patients. 
Given the new opportunities in prevention, diagnosis and treatment, the study of the 
epidemiology and clinical features of the course of severe asthma is an urgent task of modern 
medicine. The creation of the first Russian Severe Asthma Registry will serve to monitor and 
evaluate the efficacy, safety of prescribing therapy for patients with severe asthma, to isolate BA 
phenotypes and to unite regional specialists in the fight against this disease. 
 
1.2. Rationale. 
The development of the Russian Severe Asthma Registry is aimed on supervising current 
problems that can be encountered when using separate registries for this nosology. Standardization 
of data collection will help to streamline interoperable sources of data on severe asthma across 
Russia, as well as to establish an accurate process for researchers to gain access to the Registry, 
which will collect data and use them in SA patient’s management. Data on biomarkers such as 
FeNO, eosinophils, and IgE will be an important resource in the RSAR, helping to identify 
patients who are more likely to respond to biological agents. 
An example of a successfully implemented observational study is the National Register of 
Patients with Idiopathic Pulmonary Fibrosis in the Russian Federation, a prospective observational 
study of idiopathic pulmonary fibrosis (IPF) in the Russian Federation, which was initiated in 
2016 by the Russian Respiratory Society in conjunction with the Regional United Medical 
Informatization System. This innovative project was developed to study the features of 
epidemiology and the course of IPF, classified as rare diseases (ICD-10 code J84.1 - idiopathic 
pulmonary fibrosis) in the Russian Federation. It allows to obtain accurate epidemiological data on 
this nosology, to cooperate specialists from various specialties: pulmonologists, morphologists, 
radiation diagnostics specialists, and other experts at the federal and regional levels to improve the 
diagnosis and management of IPF. The Registry allows to achieve significant improvement in the 
physician’s awareness about IPF and to reveal their interest in this problem. So, on the 01.09.2017, 
185 doctors from 58 regions of the Russian Federation take part in the Registry, of which: 
• 25 major freelance specialists-pulmonologists of the Ministry of Health of the Russian 
Federation; 
• 57 scientists (professors, MD, PhD); 

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• 51 head of profile departments of state federal, regional and city health care institutions. 
 
The registry improved the detection of IPF: currently there are 519 patients in, while there 
are total number of about 1000 IPF patients according to epidemiology in the Russian Federation. 
About 35% of patients in the IPF Registry are of working age. The functioning of the IPF Registry 
led to an improvement in the quality of medical care for patients with IPF. Within the framework 
of IPF Registry, 236 online consultations / opinions of federal or regional experts were conducted. 
During the work of the IPF Registry, the number of patients receiving specific antifibrotic therapy, 
which is the treatment of choice, has increased according to current recommendations: 97% of 
patients (59 of 61) receive nintedanib, registered in Russia with indication IPF. The IPF Registry is 
of high scientific and practical value and of great social significance for the diagnosis and 
treatment of this life-threatening disease. 
The development of the Russian Severe Asthma Registry (RSAR) with a planned number of 
patients (CRFs) of 7,000 involving researchers from more than 30 cities has the potential to 
become an important Russian platform to research and a get a better understanding of the 
heterogeneity of the BA. the same as the rationale for proper use and monitoring the impact of BA 
treatment with new drugs. 
 
2.0. OBJECTIVES 
The RSAR objective is to develop a single automated system for monitoring the SA patient’s 
management in Russia, to evaluate the efficacy and safety of pharmacotherapy prescriptions for 
patients with severe asthma, to determine the phenotypes of severe asthma, and to unite regional 
specialists in the fight against this disease. 
 
2.1. Primary Objective(s) 
The key objective of establishing the RSAR initiative is to: 
• Percentage of patients with severe asthma according frequency of exacerbations (1, 2, ≥3 
exacerbations) at the time of study enrollment; 
2.2. Secondary Objective(s) 
For the overall sample and by subgroups as appropriate, the secondary objectives are to:  
• Percentage of patients with severe asthma according frequency of exacerbations (1, 2, ≥3 
exacerbations) at the 1 year of follow-up; 
• Percentage of patients with severe asthma according frequency of exacerbations (1, 2, ≥3 
exacerbations) at the 2 year of follow-up; 
• Percentage of patients with severe asthma according frequency of exacerbations (1, 2, ≥3 
exacerbations) at the 3 year of follow-up; 
• Percentage of patients with severe asthma according frequency of exacerbations (1, 2, ≥3 
exacerbations) at the 4 year of follow-up; 

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• Percentage of patients with severe asthma according concomitant diseases (number of 
observations, the mean value, the standard deviation) at the time of study enrollment; 
• Percentage of patients with severe asthma according concomitant diseases (number of 
observations, the mean value, the standard deviation) at the 1year of follow-up; 
• Percentage of patients with severe asthma according concomitant diseases (number of 
observations, the mean value, the standard deviation) at the 2 year of follow-up; 
• Percentage of patients with severe asthma according concomitant diseases (number of 
observations, the mean value, the standard deviation) at the 3 year of follow-up; 
• Percentage of patients with severe asthma according concomitant diseases (number of 
observations, the mean value, the standard deviation) at the 4 year of follow-up; 
• Percentage of patients with severe asthma according to parameters: age (the mean value, 
the standard deviation) at the time of study enrollment; 
• Percentage of patients with severe asthma according to parameters: sex at the time of study 
enrollment; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of 
parameters: IgE (IU/ml) (the mean value, the standard deviation, the minimum value, 
median, maximum value) at the time of enrollment; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of 
parameters: IgE (IU/ml) (the mean value, the standard deviation, the minimum value, 
median, maximum value) at the 1years of follow-up; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of 
parameters: IgE (IU/ml) (the mean value, the standard deviation, the minimum value, 
median, maximum value) at the 2 years of follow-up; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of 
parameters: IgE (IU/ml) (the mean value, the standard deviation, the minimum value, 
median, maximum value) at the 3 years of follow-up; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of 
parameters: IgE (IU/ml) (the mean value, the standard deviation, the minimum value, 
median, maximum value) at the 4years of follow-up; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of eosinophil 
levels in absolute values in complete blood count (number of observations, the mean 
value, the standard deviation, the minimum value, median, maximum value) at the time of 
enrollment; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of eosinophil 
levels in absolute values in complete blood count (number of observations, the mean value, 
the standard deviation, the minimum value, median, maximum value) at the 1 year of 
follow-up; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of eosinophil 
levels in absolute values in complete blood count (number of observations, the mean value, 
the standard deviation, the minimum value, median, maximum value) at the 2 year of 
follow-up; 

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• 
Percentage of patients with severe asthma with different phenotypes in terms of eosinophil 
levels in absolute values in complete blood count (number of observations, the mean value, 
the standard deviation, the minimum value, median, maximum value) at the 3 year of 
follow-up; 
• 
Percentage of patients with severe asthma with different phenotypes in terms of eosinophil 
levels in absolute values in complete blood count (number of observations, the mean value, 
the standard deviation, the minimum value, median, maximum value) at the 4 year of 
follow-up; 
• Percentage of patients with severe asthma in the parameters: of body mass index (kg/m2), 
at the time of study enrollment; 
• Percentage of patients with severe asthma in the parameters: of smoking (smoker's index 
(pack-years) at the time of study enrollment; 
• Percentage of patients with severe asthma in the parameters: of professional history at the 
time of study enrollment; 
• Percentage of patients with severe asthma in the parameters: of family history at the time 
of study enrollment; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the time of study 
enrollment; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the time of study 
enrollment; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the time of study 
enrollment; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the time of study 
enrollment; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator  in patients with severe asthma at the 1 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 1year of follow-up; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 1 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 1year of follow-up; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 2 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 2year of follow-up; 

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• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 2 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 2year of follow-up; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 3 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 3year of follow-up; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 3 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 3year of follow-up; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 4 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) before bronchodilator in patients with severe asthma at the 4 year of follow-up; 
• Parameters of FEV1 (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 4 year of follow-up; 
• Parameters of FVC (liters, percentage of predicted) (the mean value, the standard 
deviation) post bronchodilator in patients with severe asthma at the 4 year of follow-up; 
• ; 
• Percentage of patients with uncontrolled severe asthma based on the analysis of the 
questionnaire ACQ-6 at the time of study enrollment; 
• Percentage of patients with uncontrolled severe asthma based on the analysis of the 
questionnaire ACQ-6 at the 1 year of follow-up; 
• Percentage of patients with uncontrolled severe asthma based on the analysis of the 
questionnaire ACQ-6 at the 2 year of follow-up; 
• Percentage of patients with uncontrolled severe asthma based on the analysis of the 
questionnaire ACQ-6 at the 3 year of follow-up; 
• Percentage of patients with uncontrolled severe asthma based on the analysis of the 
questionnaire ACQ-6 at the 4 year of follow-up; 
• Mean number of exacerbations (the mean value, the standard deviation) requiring 
medical attention (outpatient prescription of systemic corticosteroids) in patients with 
severe asthma at the time of study enrollment; 
• Mean number of exacerbations (the mean value, the standard deviation) requiring medical 
attention (outpatient prescription of systemic corticosteroids) in patients with severe 
asthma at the 1year of follow-up; 
• Mean number of exacerbations (the mean value, the standard deviation) requiring medical 
attention (outpatient prescription of systemic corticosteroids) in patients with severe 
asthma at the 2 year of follow-up; 

20 | Page 
 
 
 
• Mean number of exacerbations (the mean value, the standard deviation) requiring medical 
attention (outpatient prescription of systemic corticosteroids) in patients with severe 
asthma at the 3 year of follow-up; 
• Mean number of exacerbations (the mean value, the standard deviation) requiring medical 
attention (outpatient prescription of systemic corticosteroids) in patients with severe 
asthma at the 4 year of follow-up; 
• Mean number of hospitalizations (the mean value, the standard deviation) in patients 
with severe asthma at the time of inclusion in the study; 
• Mean number of hospitalizations (the mean value, the standard deviation) in patients with 
severe asthma at the time of inclusion in the 1 year of follow-up; 
• Mean number of hospitalizations (the mean value, the standard deviation) in patients with 
severe asthma at the time of inclusion in the 2 year of follow-up; 
• Mean number of hospitalizations (the mean value, the standard deviation) in patients with 
severe asthma at the time of inclusion in the 3 year of follow-up; 
• Mean number of hospitalizations (the mean value, the standard deviation) in patients with 
severe asthma at the time of inclusion in the 4 year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) 
taking high doses of ICS/LABA, ICS/LABA+LAMA as maintenance therapy, biologics 
at the time of study enrollment; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
high doses of ICS/LABA, ICS/LABA+LAMA as maintenance therapy, biologics at the 1 
year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
high doses of ICS/LABA, ICS/LABA+LAMA as maintenance therapy, biologics at the 2 
year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
high doses of ICS/LABA, ICS/LABA+LAMA as maintenance therapy, biologics at the 3 
year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
high doses of ICS/LABA, ICS/LABA+LAMA as maintenance therapy, biologics at the 4 
year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) 
taking OCS as a maintenance therapy at the time of study enrollment; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
OCS as a maintenance therapy at the 1 year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
OCS as a maintenance therapy at the 2 year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
OCS as a maintenance therapy at the 3 year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) taking 
OCS as a maintenance therapy at the 4 year of follow-up; 

21 | Page 
 
 
 
• Percentage of patients with severe asthma (the mean value, the standard deviation) who 
have been changed therapy (step up, step down by GINA) to 1 year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) who 
have been changed therapy (step up, step down by GINA) to 3 year of follow-up; 
• Percentage of patients with severe asthma (the mean value, the standard deviation) who 
have been changed therapy (step up, step down by GINA) to 4 year of follow-up; 
• Percentage of patients with severe asthma who called for emergency medical care for 
asthma (number of observations, the mean value, the standard deviation, median) at the 1 
year of follow-up; 
• Percentage of patients with severe asthma who called for emergency medical care for 
asthma (number of observations, the mean value, the standard deviation, median) at the 2 
year of follow-up; 
• Percentage of patients with severe asthma who called for emergency medical care for 
asthma (number of observations, the mean value, the standard deviation, median) at the 3 
year of follow-up; 
• Percentage of patients with severe asthma who called for emergency medical care for 
asthma (number of observations, the mean value, the standard deviation, median) at the 4 
year of follow-up; 
• Percentage of patients with severe asthma who had disability sheets for asthma 
(number of observations, the mean value, the standard deviation, median) at the 1year of 
follow-up; 
• Percentage of patients with severe asthma who had disability sheets for asthma (number of 
observations, the mean value, the standard deviation, median) at the 2 year of follow-up; 
• Percentage of patients with severe asthma who had disability sheets for asthma (number of 
observations, the mean value, the standard deviation, median) at the 3year of follow-up; 
• Percentage of patients with severe asthma who had disability sheets for asthma (number of 
observations, the mean value, the standard deviation, median) at the 4 year of follow-up; 
 
 
 
 
 
 
 
3.0. METHODOLOGY 
 

22 | Page 
 
 
 
3.1. Registry Design  
The Russian Severe Asthma Registry is a prospective multicenter, non-interventional 
observational study for patients with severe bronchial asthma (SA). 
All patients included in the RSAR platform will be periodically observed during 
routine visits to the hospital with a follow-up of up to five years. 
In the RSAR conductance there is no provision for any intervention in routine clinical 
practice, including the use of the study therapy / treatment methods or special research 
methods. From the day the project begins, the physician will collect data on all patients 
with SA who have visit as outpatient or hospitalized patient and who meet the 
inclusion criteria for in this study. 
The study includes a retrospective part - an analysis of the medical records of patients 
available at the time of their inclusion in the study. 
Patients with a confirmed diagnosis of SA (according to inclusion criteria) will be 
included in the study sequentially and observed for 5 years. 
The period of patient’s inclusion - from 03.2018 till 11.2022. 
The observation period is from 03.2018 till 11.2022. 
The approximate period of the Registry work is from 03.2018 to 12.2022. 
The target sample size is up to 7,000 patients with SA over a period of 5 years. 
 
3.2. Draft Cities Initiation 
The participation of cities and recruitment of patients in the RSAR is expected: 
Period, years 
Number of 
participating cities 
(health facilities) 
Number of SA 
patients CRFs 
03.2018-12.2018 
30 (100 health 
facilities) 
2000 
01.2019-12.2019 
30 (100 health 
facilities)) 
2000 
01.2020-12.2020 
30 (100 health 
facilities)) 
1000 
01.2021-12.2021 
30 (100 health 
facilities) 
1000 

23 | Page 
 
 
 
01.2022-11.2022 
30 (100 health 
facilities)) 
1000 
 
3.3 Data Collection 
The main data source within the RSAR will be an electronic database of patients developed 
on the basis of the "Medical online platform ROSMED.INFO", which is the own development of 
LLC "RSMI". 
The attending physicians of patients with SA will enter information online in the electronic 
database. As investigation centers will be used health facilities of federal and regional levels, 
which include specialized pulmonological and allergic departments. These centers have the 
opportunity to include the largest number of patients with SA in the study, and they also have 
extensive experience in the management and monitoring of such patients. The total number of 
health facilities is 100. The centers participating in the study will collect data on all patients 
diagnosed with SA who have signed written informed consent to participate in the study. Data 
collection will be carried out on a regular basis during routine patient visits to a doctor or in case 
of hospitalization. In the work period of this project, no special additional procedures for 
collecting information will be used. The information will be collected from outpatient cards and / 
or case histories, based on data received by the physician during routine examination of the 
patient. Visitors of www.rosmed.info site can not participate in the RSAR study without first being 
invited by the attending physician.  
 
3.4. Patient Population 
Patients receiving step 4 and 5 treatment (according to GINA, 2017) in accordance with the 
uncontrolled asthma severity (J.45) in health facilities in accordance with local regulatory / ethical 
requirements. The goal is to include up to 7,000 patients in RSAR throughout Russia during the 
entire study period. 
Signed informed consent will be collected from patients in order to use data in accordance 
with RF legislation, and to gain approval of the RSAR study by the Independent Interdisciplinary 
Ethical Review Committee of the Clinical Studies (Committee) - (http://ethicuni.ru). 
The role of the Committee is to verify and approve the scientific significance of research 
objectives. The purpose of the Committee is to ensure that the research database is clinically 
appropriate and continues to bring real benefits to patients, public health and health organization 
system. 
 
The study will collect the following data on patients with SA: 
• Personal data. 
• Patient demographics. 

24 | Page 
 
 
 
• Anamnesis of the disease, including previous exacerbations, allergic status and current 
status monitoring. 
• Concomitant diseases, including atopic dermatitis, allergic and non-allergic rhinitis, 
chronic rhinosinusitis with or without polyps. 
• Medications prescribed for the treatment of asthma, including data on patient adherence to 
prescribed treatment, where applicable and assessment of the inhalation technique. 
• Treatment outcomes, including asthma control status (control of GINA 2017), quality of 
life and professional history. 
• Spirometry data. 
• Biomarkers (blood eosinophils, sputum eosinophils, IgE, and FeNO, where possible). 
• Patient’s basic therapy, including use of OCS and biological agents. 
• The economic burden of asthma in patients (disability sheets, ambulance calls, etc.). 
• Evaluation of the frequency and severity of BA exacerbations. 
 
The data including these estimates will be entered into the electronic database of RSAR for 
storage and subsequent impersonal analytics. Data from any existing registries of patients with 
severe asthma may also be entered.  
For compatibility, the existing data will be sorted in accordance with the standard data 
collection fields / codes established by the RSAR monitoring group. 
3.5. Inclusion Criteria 
• Patients aged 12 years or older. 
Patients with confirmed diagnosis of severe asthma. 
• Patients receiving treatment according to GINA step 5 or uncontrolled for 4 step. 
Uncontrolled patients are defined as having symptoms of severe asthma1 or frequent 
exacerbations2. 
Signed informed consent. 
                                                
1 Severe symptoms of BA (Guideline of European Respiratory Society (ERS)/American Thoracic 
Society (ATS)) (2): 
(a) BA with uncontrolled symptoms; АСТ< 20, ACQ ˃1,5; 
(b Limited air-flow rate, for example: FEV1 <80 % of the norm (along with FEV1/FES at the lower 
limit of the norm or less) after wash-out period from the  bronchodilators; 
(c) Severe exacerbation and hospitalization, being in the ICU or on the mechanical ventilation of lungs 
over the past year. 
2 Frequent severe exacerbations of BA (guidelines ERS/ATS) (2): 
Frequent severe exacerbations of BA (2 or more courses of systemic glucocorticoids over the past 
year). 
 

25 | Page 
 
 
 
3.6. Exclusion Criteria 
•  Intermittent, mild, moderate BA, before verification of the diagnosis. 
•  COPD. 
•  Diseases of the respiratory system, such as tuberculosis, sarcoidosis, IPF, lung cancer. 
•  Vasculitis, systemic connective tissue diseases. 
•  Neoplasm. 
•  Written refusal of the patient to participate in the study after signing an informed consent. 
 
3.7. Registry Follow-up  
Since the study is in the form of a Registry - non-interventional observational study - there is 
no planned intervention in the common clinical practice of patient management, the number of 
follow-up visits will be based on existing recommendations and protocols for managing patients 
with asthma in the Russian Federation and the patient's needs. It is assumed that the patient will 
visit health facilities once in 3 months. The frequency of visits depends on the initial level of 
control of asthma in the patient, the response to treatment. 
 
3.8. Consent Procedures  
Participants will be provided with full information about the planned study, their rights and 
opportunities, after which it will be offered to sign the informed consent, which is a prerequisite 
for the patient's participation in the Registry. 
 
4.0. DATABASE 
 
4.1. Data Acquisition 
With each physician-investigator a civil law agreement will be concluded that regulates the 
work of the physician within the framework of the project. A cooperation agreement will be 
concluded between the project technical executor, LLC RSMI, and the supervising organization of 
the IPO RRS, which will ensure the right of IPO RRS to legally own the accumulated database on 
patients with severe asthma. 
 
4.2. Data Management 
Data from patients with SA will be entered into the electronic CRF by physicians-
investigators within a limited time after receiving the diagnostic / consultation results. The CRF is 
an integrated part of the Universal Medical Complex of Medical Organization and Informatization 
for the collection, dynamic clinical and epidemiological surveillance and analysis of data in the 

26 | Page 
 
 
 
remote access mode "ROSMED.INFO", quality control and reliability of the information entered 
will be checked online by the project manager of LLC " RSMI" within the framework of existing 
SOPs and quality management standards. 
The data of SA patients CRFs will be stored electronically in a secure database, with an 
obligatory database backup procedure, as well as with a preliminary assessment of the security 
threats for their elimination (RSMI regulatory document - "Security Threat Model"). 
Backup information is stored on the servers (databases, data catalogs on file servers, general 
catalogs of departments and departments). 
In parallel, the data will be copied on paper carriers, their storage will be carried out in water 
and fireproof safes. 
Instructions for the operation of the data manager of the RSAR include the full procedure for 
working with personal data and are available for audit. 
A separate data management plan describes all the functions, processes and specifications 
for data collection, retrieval, sending, cleaning and validation. Electronic CRFs will include a 
programmed version for instant feedback, if data are not available, go beyond acceptable limits, 
are illogical and potentially erroneous. This minimizes general data entry errors. A collaborative 
manual data validation process will be conducted based on plan parameters. In the electronic 
research data recording system (EDS), special requests will be generated, requiring further 
explanations. 
High data quality standards will be maintained, the processes and procedures used 
systematically will ensure the highest possible accuracy of the data submitted for analysis. The 
data quality will be improved through a series of programmed checks to automatically detect 
abnormal data or data beyond the specified limits. All data modifications will be registered in the 
audit log. 
 
4.3. Registry Coding  
The project work group consisting of representatives of the supervising organization and technical 
specialists of RSMI LLC will agree on a standardized set of basic and long-term indicators, and 
will hold regular meetings to ensure long-term expert input through the development, expansion of 
the register and the achievement of research objectives. 
The technical executor of the project, LLC RSMI, should provide the opportunity, if necessary, to 
convert the accumulated database into a format that corresponds to the standardized clinical codes 
and terms contained in the dictionary of the systematized nomenclature of medical clinical terms 
(SNOMED CT), which allows to recognize the clinical sequence of ICD and read the encoding, 
which will be able to present the data at the detailed level required for the purpose of coding the 
register. SNOMED CT was developed by the International Health Terminology Organization 
(IHTSDO), and is currently available in English and Spanish versions. 
 

27 | Page 
 
 
 
4.4. Statistics analysis  
Primary and secondary statistical indicators will be presented using descriptive statistics methods. 
Qualitative variables will be presented in the form of incidence and percentage. The quantitative 
variables will be represented by numerical values, standard deviation indicators, minima and 
maxima, median and interquartile range. The frequency and severity of adverse events / reactions 
will be documented according to the Medical Dictionary of Regulatory Terminology, version 16.1. 
When analyzing the outcome of the disease among patients on therapy (drug), statistical analysis 
will be performed in a subgroup of newly identified patients. Evaluation of the outcome of SA can 
be determined by achieving a sufficient number of patients in a subgroup of newly identified 
patients and patients undergoing therapy (SA). The lack of comparison between groups of patients 
is due to the inaccuracy of these therapies in the history and treatment approaches. 
In the course of the analysis, the standard statistical characteristics of morbidity, prevalence of the 
disease (SA) and their dependence on the basic demographic indicators (sex, age) will be assessed. 
The statistical analysis of the endpoints will be performed for patients with a diagnosis period of 
no more than 6 months from the date of inclusion in the register (a subgroup of newly identified 
patients) and also when the required amount of statistical data is collected within the register 
database. 
The analysis will use standard methods of descriptive, frequency, logistic statistical analysis. 
Hypotheses of the study. The main goal of the study is to obtain statistical estimates of the target 
epidemiological characteristics, formally asking questions about hypotheses of the study in this 
case is not applicable. After receiving the estimates, they are expected to be compared with similar 
ones, known in the foreign and domestic literature and official statistics. 
Within the Registry, measures should be taken to collect data on the maximum number of patients 
within the claimed sample. In the absence of information within the fields of the individual 
registration card, the validating authority should separate information on the statuses "negative 
value", "no data", "not investigated". 
The data of patients dropped out of the register during the observation will be analyzed and used to 
calculate the primary points, if the number of completed visits allows, the data can be used to 
analyze part of the parameters of the observation period. The initial characteristics of patients 
dropped out of the register before its completion will be compared with the characteristics of 
patients with a fully completed observation period, taking into account the proportionality of the 
data (the number of "dropped out" patients). 
 
4.5. Main analysis. 
The aggregate statistics for continuous variables will include the number of observations (N), the 
mean value, the standard deviation (SD), the minimum value, Q1 (25th percentile), median, Q3 
(75th percentile), maximum value, interquartile range. Tables of categorical variables will 
represent all possible categories and will display the number of observations for each category, as 
well as percentages. Precision for percent is one decimal point, if the denominator is less than 100 
(in all columns), in this case, percentages are indicated by integers. In general, the percentages will 
be calculated based on the total number of patients in the analyzed population, regardless of 

28 | Page 
 
 
 
whether they have missing values or not. The category "Missing" will be displayed when at least 
one patient falls into this category. The CRF contains several nested questions (that is, questions 
that require more detailed information only in a subset of patients with a specific value for another 
question, "if yes" questions); for these variables, percentages will be based on patients with a 
corresponding value for a higher-level issue, rather than using all patients in the population as 
reference values. 
 
4.6. Further analysis 
In the case of the availability of data on patient, which are observed in parallel in other 
registries, it is necessary to perform an analysis for this group separately from the rest of the 
patients. In the event of a discrepancy between the indicators of other registers and this study, the 
latter is determinative. 
 
4.7. Quality control 
The Analytical Working Group and the Technical Operator and the Personal Data Operator will 
check the data for completeness and correctness, inform the local executors about probable errors 
and omissions in the data when filling CRFs by the doctors. Obvious corrections will be made at 
the level of administrators and managers of the system who are employees of LLC "RSMI" with 
notification to the curators of the register. 
The Quality Management System (QMS) of RSMI LLC standardizes the procedures for creating 
and maintaining patient databases on the basis of a universal software package for medical 
organization and information for the collection, dynamic clinical and epidemiological surveillance 
and analysis of data in remote access mode ROSMED.INFO. QMS ensures the fulfillment of the 
customer's requirements and the conformity of the processes and their results with the legislation 
of the Russian Federation. 
LLC "RSMI" guarantees the availability of personnel, production environment and appropriate 
infrastructure for the implementation of QMS. 
LLC "RSMI" within the framework of the QMS ensures that the organization's knowledge base, 
the level of sufficient competence of the employees involved in the work process and their 
awareness of the standards of the quality management system are adequate to the work objectives 
and objectives. 
LLC "RSMI" guarantees the availability of functioning internal and external communications that 
ensure the operation of the quality management system. The QMS of the organization regulates 
the analysis of requirements related to the company's products and services. QMS LLC RSMI 
includes all stages of development and maintenance of the software product and databases, 
including the stages of statistical processing of the results obtained through the integrated online 
statistical processing module. 
 

29 | Page 
 
 
 
4.8. Limitations of study methods. 
The following errors must be taken into account when planning methods for recruiting patients and 
their follow-up observation: 
- Wrong information; 
- Incorrect inclusion of the patient in the study; 
- Errors in the periods of entering information; 
- Removal of the patient at the stage of the beginning of the period of dynamic observation. 
In order to reduce the likelihood of these errors within the QMS (quality management system), it is 
planned to conduct audits for compliance of the RSAR data with the study protocol, the 
requirements of the study organizers and the legislation of the Russian Federation. The program 
includes built-in internal validation tools for the entered data. To minimize the risks of mistaken 
inclusion of patients, the process of registration of patients in the study will be extremely 
consistent. All patients who meet the inclusion criteria, regardless of location (research base) will 
necessarily be included in the RSAR. Patients participating in interventional clinical trials will not 
be included. For the entire population entered in the RSAR, the initial characteristics (primary 
endpoints) will be examined and analyzed. At each base included in the study, a patient screening 
log will be kept, including information on the field, age, date of birth, the date of diagnosis of AE 
of serious gravity, the reason for including the patient / reason for not including the patient in the 
register, the date of signing the informed consent form for participation in the research, reasons for 
refusing to participate in the register. 
The study monitors will have the opportunity to check the sequence of patients' inclusion in the 
study. The investigators and organizers of the RSAR will make every effort to minimize 
unreasonable drop-out of patients from the register, within which regular contact will be made 
with the patient / his legal representative, in case of dropout, the cause will necessarily be 
established (with documentary evidence, about death). A signal for an emergency contact with the 
patient / legal representative will be the miss of another planned visit within the framework of the 
visit. The contact form and its result will be registered in accordance with the established 
procedure (SOP LLC RSMI). 
In order to minimize the dropout of patients, the following efforts will be made: 
- Work with databases where patients are recruited; 
- Minimizing the difficulties of participation in the register for patients; 
- Constant contact of the researcher with the patient. 
To study the effects of dropping out of patients during the observation process, parameters such as 
the number of patients left in% and the reasons for their departure will be summarized and 
analyzed. Population characteristics will be summarized for the retired patients, compared with the 
characteristics of patients who have reached the end of the observation period. The period of time 
for which the patient has left the observation ahead of schedule will be studied and analyzed. 
To exclude the shift in the periods of entering information in the form of the patient's IRC, 
questions of a clarifying character will be present, with reference to a certain frequency of the 
event, a time interval, etc. 
 

30 | Page 
 
 
 
5. 0. Other aspects of the study 
 
5.1. Data quality assurance  
The quality assurance guarantee will cover the following areas: 
- guarantee of data quality assurance; 
- guarantee of quality assurance of all procedures that are relevant to the RSAR; 
- guarantee of software quality assurance and computer systems. 
In order to guarantee the quality of the data, measures will be taken to prevent, detect and correct 
the following types of errors: 
- Interpretation or coding errors; 
- errors in data entry, accuracy of their transfer and transformation; 
- semantic errors; 
Activities (steps) to ensure the quality of information will include: 
- trainings (training of those responsible for collecting information); 
- checking the completeness of the information provided (the presence of an immediate feedback 
mechanism with the clinical center, where patients are included in the study and observed); 
- checking consistency of data (comparing data from different centers and at different time 
intervals); 
- local audit in each center (checking of the screening logs, procedures, data samples); 
- special audits (for the centers that cause the greatest fear of inaccurate information entry and are 
characterized by the greatest number of errors); 
In order to ensure the quality of all data on the register, the following will be done: 
1. Appointment of the person responsible for the quality of the data in each center included in the 
study; 
2. Scheduled audits of data quality; 
3. Activities to maintain and improve the level of competence of staff; 
4. Checks security systems and data integrity; 
5. Guarantee of the validity of computer systems and software, their compliance with quality and 
safety standards, compliance with the legislation of the Russian Federation; 
6. Information Systems Security Plan; 
7. Differentiation of access rights to the patient / legal representative, physician, system 
administrator, database operator. 
 
Quality assurance of audit can be carried out by representatives of the organizer of the register, and 
also other authorized regulating bodies. The quality control auditor has access to all medical 
records related to the research, the researcher's medical files, correspondence and documentation, 
informed consent of this study. 
 

31 | Page 
 
 
 
5.2. Data registration 
CRFs for individual patients will be provided to the curators of the project on paper 
and in digital form. 
RSAR will consist of a two-level collection of standardized data, as described below: 
● A list of the main variables (defined by the process within the Medical online platform 
ROSMED.INFO): it will consist of approximately 100 basic variables. 
● Extended variable list: this will make all variables useful for scientific research and maximum 
data collection and create an optimal list of variables. Long-term variables will be collected 
through standardized joint modules. The name of several: asthma control (ACQ6), a professional 
history questionnaire, concomitant diseases, a history of vaccinations and biomarkers of severe 
asthma. 
 
5.3. Data ownership 
Based on the results of the study, biostatistical analyzes (customized) of the RSAR data 
obtained on an annual basis and interim reports every six months will be compiled. 
A number of publications are planned on the basis of the statistical analysis of the research 
data, the authors' team, the internal editing and review procedures will be decided within the 
working group on the publication policy. The timing of publications and their content will be 
regulated by the steering committee, the curators of the study. 
The rights to intellectual property belong to the Interregional Public Organization "Russian 
Respiratory Society". 
 
5.4. Data access and subordination 
To begin work of RSAR, it is necessary to obtain approval from the independent ethical 
committee (NEC). 
 
To gain NEC approval it is necessary to provide following documents: 
1. The study protocol. 
2. Patient's voluntary informed consent form and Information form for the patient. 
3. Biography of scientific curators / experts. 
4. Documents confirming the legality of the collection, storage and processing of personal 
data of participants (doctors and researchers). 
5. List of clinical centers participating in the study. 
6. Public contract-offer (User agreement), documentation in the framework of the policy 
regarding the organization and processing of personal data. 
7. Case Report Form (eCRF). 

32 | Page 
 
 
 
8. Documentation that confirms the agreement between the supervising organization and the 
technical contractor of the project for joint work. 
 
The initiation of the work of the Registry is possible only in case all the necessary legal 
documents are available, and the NEC approves it in accordance with Russian and international 
legal norms. The same situation applies to the mechanism for introducing changes and 
amendments. 
To participate in the study, the patient/legal representative must sign an informed consent for 
participation in the study. 
Each signature must be dated personally by the signer and retained for the duration of the 
study, as well as the form of informed consent and any other documents relevant to the patient. A 
copy of the signed informed consent, as well as any other additional information about the patient, 
must be provided directly to the patient or his legal representative. 
The patient should be informed that his personal data will be used in accordance with 
Federal Law No. 152 "On Personal Data". The patient should also be explained the level of 
disclosure within the framework of possible audits by the organizers, curators, research sponsors 
and technical support parties. 
Identification and authentication measures should ensure that unique characteristic 
(identifier) will be performed to access objects and access objects, a comparison of the identifier 
presented by the subject (object) with a list of assigned identifiers will be made to verify that the 
identifier presented to the subject is authentic (authenticated). 
 
Access control measures should provide management of rights and privileges of access 
subjects, delineate access of access subjects to access objects based on the set of access 
control rules established in the information system, and ensure compliance monitoring of 
these rules. 
Measures to protect computer personal data carriers (means of processing (storing) personal data, 
removable computer personal data carriers) should exclude the possibility of unauthorized access 
to computer media and personal data stored on them, as well as unauthorized use of removable 
personal data carriers. 
Measures to register security events should ensure the collection, recording, storage and protection 
of information on security events in the information system, as well as the ability to view and 
analyze information about and respond to such events. 
Anti-virus protection measures must ensure that computer programs or other computer information 
is detected in the information system for unauthorized destruction, blocking, modification, copying 
of computer information or neutralizing information protection means, as well as responding to the 
detection of these programs and information. 
Measures to control (analyze) the protection of personal data should ensure that the level of 
protection of personal data processed in the information system is monitored by carrying out 
systematic measures to analyze the security of the information system and to test the operation of 
the personal data protection system. 

33 | Page 
 
 
 
Measures to protect the virtualization environment should prevent unauthorized access to and 
manipulate personal data processed in the virtual infrastructure and / or virtual infrastructure 
components, including virtual infrastructure management tools, virtual machine monitor 
(hypervisor), storage system (including the storage of images of virtual infrastructure), data 
networks through elements of a virtual or physical infrastructure, guest operating systems, virtual 
containers, the system and the replication network, terminal and virtual devices, as well as the 
backup system and the copies it creates. 
Measures for the protection of technical means must exclude unauthorized access to stationary 
facilities that process personal data, facilities that support the operation of the information system 
(hereinafter means of operation), and to the premises in which they are permanently located, the 
protection of technical means from external influences, and also the protection of personal data 
presented in the form of informative electrical signals and physical fields. 
Measures to protect the information system, its facilities, communication systems and data 
transmission should ensure the protection of personal data in the interaction of the information 
system or its individual segments with other information systems and information and 
telecommunications networks through the application of the architecture of the information system 
and design solutions aimed at ensuring the safety of personal data. 
Measures to manage the configuration of the information system and personal data protection 
systems should provide management of changes in the configuration of the information system 
and personal data protection system, analyze the potential impact of the planned changes on the 
security of personal data, and document these changes. 
These measures to ensure the security of personal data are implemented in the system of personal 
data protection for all objects and entities of access at the hardware, system, application and 
network levels, as well as in the environment of virtualization and cloud technologies. 
When using information security tools certified in accordance with the requirements of 
information security in the informatization system of personal data "Rosmed.info" to ensure the 3 
levels of protection of personal data, the following should be applied: 
• Means of computer technology no lower than Class 5; 
• Intrusion detection systems and anti-virus protection tools of at least Class 4 protection; 
• Internetwork screens of at least 3 protection classes. 
 
6. Adverse events/reactions data collection and report 
6.1 Definitions 
6.1.1 Definition of adverse event (AE). 
Adverse event (AE) is any untoward change in state of health of patient or clinical 
investigation/trial subject administered a pharmaceutical/studied product and which does not 
necessarily have to have a causal relationship with this treatment. AE can be any unfavorable 
symptom (for example, nausea, chest pain), sign (for example, tachycardia, enlarged liver) or 
abnormal examination result (for example, abnormal laboratory finding, change in ECG), the time 

34 | Page 
 
 
 
of occurrence of which does not exclude causal relationship with the use of a pharmaceutical 
product, whether or not related to the use of a pharmaceutical product. 
The term AE is used to indicate both serious and non serious adverse events. 
The data on special situation should also be collected and reported: the use of a pharmaceutical 
product during pregnancy or lactation (whether the pregnancy outcome is known or not), lack of 
treatment efficacy, overdose, abuse, misuse, off-label use, suicidal attempt or completed suicide, 
suspected drug interaction and suspected infectious agent transmission. 
 
6.1.2 Definition of serious adverse event (SAE). 
Serious adverse event is AE, that occurs at any stage of the trial (i.e. introductory stage, 
observation stage) and meets one or more of the following criteria: 
• Results in death; 
• Is life-threatening (in this context, a reaction can be defined as life-threatening if it places 
the patient at immediate risk of death from the reaction as it occurred; it does not include a 
reaction that, had it occurred in a more severe form, might have caused death). 
• Requires inpatient hospitalization or prolongation of existing hospitalization; 
• Results in persistent or significant disability/incapacity; 
• Is a congenital anomaly/birth defect;  
• Is any other clinically significant medical event, that can be menacing to the patient or 
requires medical treatment to prevent the previously-mentioned conditions. The 
compliance of AE with the criteria of seriousness can be determined using medical and 
scientific consideration. 
Any suspected unintentional transmission of an infectious agent is also defined as SAE and may 
be subject to express reporting in some countries. An infectious agent is any microorganism, virus 
or infectious particle (for example, a prion protein that is a carrier of transmissible spongiform 
encephalopathy), regardless of pathogenicity. 
6.1.3 Definition of adverse reaction (AR) 
Adverse reaction (AR) is AE, related to the use of pharmaceutical/studied product and implying at 
least probable interrelation with the use of suspected  pharmaceutical/studied product.  
Adverse reaction may occur by use of the pharmaceutical product in accordance with instructions 
for medical use or not in accordance with it, and also by impact, associated with the occupation. 
6.2 Adverse events data collection 
In view of the non-interventional nature of this study, active collection of safety data will not be 
performed. It applies to collection of both primary safety data – (directly from patients) and 
secondary data (analysis of patient’s medical records, available at the time of their enrolment into 
the trial), in which the safety of prescribed drug therapy with glucocorticoids is being studied.  

35 | Page 
 
 
 
Nevertheless, if during the visit of the patient the investigator finds out  
the AE, occurred in this trial and on the background of the pharmaceutical product intake, it is 
necessary to ascertain whether there is or there is not a cause-effect relationship with the 
pharmaceutical product, collect and report information in accordance with regulatory 
requirements and timing for pharmacovigilance in the postmarketing period for spontaneous 
report. 
For each adverse event it is necessary to record the following variables: 
• a term for describing of the adverse event; 
• date of occurrence and completion of the adverse event; 
• severity of the adverse event; 
• compliance of the adverse event with the criteria of seriousness; 
• the investigator's assessment of the existence of a cause-effect relationship between the 
adverse event and the use of a pharmaceutical product (yes 
• or not); 
• Measures, taken in relation to the pharmaceutical product; 
• The outcome. 
It is extremely important, that all the staff, participating in the trial, are 
familiar with the contents of this section. The principal investigator is 
responsible for ensuring that all the staff, involved in the trial, are familiarized with the 
spontaneous report processing procedures (the term spontaneous report implies voluntary transfer 
by a health worker or the consumer to the Regulatory Authority, holder of the registration 
certificate), as well as with national regulatory requirements for pharmacovigilance in Russia. 
 
Adverse events assessment 
All AE (both serious and non serious), spontaneously reported by patients oridentified by the 
investigator, will be assessed for the presence or absence 
of causal relationship with pharmaceutical product and should be recorded and evaluated in 
accordance with the following definitions: 
Degree of severity 
To estimate the severity of AE concerning its intensity, the following three-level scale will be 
used:  
• Mild: the presence of signs or symptoms that do not affect daily activities. 
• Medium: the event is of sufficient intensity to affect daily activities. 
• Severe: impossibility to work or perform daily activities (unacceptable event). 
Important! The severity of events is not the equivalent of seriousness and is used to describe the 
intensity of an event (for example, a strong headache may not be of a serious clinical significance) 
*. 

36 | Page 
 
 
 
* See the seriousness criteria in the SAE definition or the item is defined by 
criteria in section 6.1.2. 
 
Causality Assessment between  the medicinal product and Adverse Event 
The investigator necessarily assesses the relationship between the use of the pharmaceutical 
product and the occurrence of each adverse event by answering "yes" or "no" to the question: 
"Do you think that there is a reasonable probability that this event could be caused by the therapy 
used (for the drug in the glucocorticoid therapy)?». 
 
6.3 Reporting on the adverse events 
6.3.1 Reporting on the adverse events spontaneous reports  
Monitoring of safety will be performed according to local pharmacovigilance requirements, 
applicable in standard medical practice on the territory of the Russian Federation. 
If one of the investigators becomes aware of AE, which is estimated to have a causal relationship 
with the pharmaceutical product of AstraZeneca company, information on such AE should be 
collected and recorded in the primary documentation and in the form of an AE report (which is 
part of the eCRF). 
All AR and serious adverse reaction (SAR), including fatal events, should be collected and the 
information should be transmitted in accordance with regulatory requirements and timing for 
pharmacovigilance in the postmarketing period for spontaneous report.  
If the causal relationship is estimated as doubtful in the report (AE or SAE), that report should be 
included  in the final report. 
Information about all adverse events should be summarized and represented in the final clinical 
trail report. 
 
6.3.2 Recording of spontaneous the adverse events  
When recording adverse events, identified in the trial, it is necessary to be guided by the following 
principles: the investigator should report on adverse events by the 
pharmacovigilance procedures according to local regulatory requirements. 
Method of presenting information on AR/SNR, obtained in the spontaneous reporting: 
1. 
 In writing to the Federal Service for Surveillance in Healthcare by contacting: Russian 
Federation, 109074, Moscow, Slavyanskaya pl., 4, p. 1 At the same time, it is necessary 
to use a special form located at: 
http://www.roszdravnadzor.ru/i/upload/files/1308641445.19876-26263.doc 
2. 
 To the relevant pharmaceutical company, i.e. company, in whose name 
a registration certificate of the pharmaceutical product has been issued, according to local 
regulatory requirements. 
 

37 | Page 
 
 
 
7. Publication Plan 
Dissemination plan for research results and communications on the results obtained. The results of 
the study, annual reports will be compiled. 
A number of publications are planned on the basis of the statistical analysis of the research data, 
the authors' team, the internal editing and review procedures will be decided within the working 
group on the publication policy. The timing of publications and their content will be regulated by 
the Core Steering Committee, the curators of the study. 
Intellectual property rights belong to the executors of the project: 
1) Interregional Public Organization "Russian Respiratory Society". 
2) Russian Association of Allergology and Clinical Immunology. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8. References 
1. Martinez FD, Vercelli D. Asthma. Lancet 2013; 382: 1360-72. 
2. Global Initiative on Asthma. Global strategy for asthma management and prevention. 
www.ginasthma.com. 

38 | Page 
 
 
 
3. Hekking PP, Wener RR, Amelink M, Zwinderman AH, Bouvy ML, Bel EH. The 
prevalence of severe refractory asthma. (2015) J Allergy Clin Immunol. 135(4):896-902. 
4. Kim SH, Kim TW, Kwon JW, Kang HR, Lee YW, Kim TB, Kim SH, Park HW, Park SW, 
Chang YS, Cho YS, Park JW, Cho YJ, Yoon HJ, Cho SH, Choi BW, Moon HB, Min KU. 
Economic costs for adult asthmatics according to severity and control status in Korean 
tertiary hospitals. (2012) J Asthma.49(3):303-9. 
5. Moore WC, Bleecker ER, Curran-Everett D, Erzurum SC, Ameredes BT, Bacharier L et al 
(2007) Characterisation of the severe asthma phenotype by the national Heart, Lung, and 
Blood Institute’s Severe Asthma Research Program. J Allergy Clin Immunol 1 119:405-
413. 
6. Asthma UK  https://www.asthma.org.uk/. 
7. Berry A and Busse WW. Biomarkers in asthmatic patients: Has their time come to direct 
treatment? (2016) JACI 137:1317-24. 
8. Price DB, Rigazio A, Campbell JD, Bleecker ER, Corrigan CJ, et al., Blood eosinophil 
count and perspective annual asthma disease burden: a UK cohort study. (2015) The 
Lancet Respiratory Medicine. 
9. Pavrod ID, Korn S, Howarth P, Bleecker ER et al. Mepolizumab for severe eosinophlic 
asthma (DRAM): a multicentre, double-blind, placebo controlled trial. (2012) 
Lancet380:651-9. 
10. Bel EH, Wenzel SE, Thompson PJ et al Oral gluticorticoid-sparing effect of mepolisumab 
in eosinophilic asthma. (2014) N Egnl J Med 371:1189-97. 
11. Ortega H, Li H, Suruki R, Albers F et al Cluster analysis and characterization of response 
of mepolizumab. A step closer to personalized medicine for patients with severe asthma. 
(2014) Ann Am Thorac Soc 11:1011-7. 
12. Price DB, Wilson AM, Chisholm A, Rigazio A, Thomas M, and King C (2016) Predicting 
frequent asthma exacerbations using blood eosinophil count and other patient data 
routinely available in clinical practice. (2016) Journal of asthma and Allergy 9: 1-12. 
13. Dweik RA, Sorkness RL, Wenzel S et al. Use of exhaled nitric oxide measurement to 
identify a reactive, at-risk phenotype among patients with asthma. (2010) Am J Reps Crit 
Care Med 181:1033-1041. 
14. Rodrigo GJ, Neffen H, Castro-Rodriguez JA. Efficacy and safety of subcutaneous 
omalizumab vs placebo as add-on therapy to corticosteroids for children and adults with 
asthma: a systematic review (2011) Chest 139:28-35. 
15. Hanania NA, Alpan O, Hamilos DL, et al, Omalizumab in severe allergic asthma 
inadequately controlled with standard therapy: a randomized trial (2011). Ann Intern Med. 
154:573-582. 
16. Glicklich RE, Dreyer NA, eds. Registries for evaluating patient outcomes: A User’s Guide. 
3rd ed. 2014. 
17. Sweeney J, Chris C Patterson, Andrew Menzies-Gow, Rob M Niven, Adel H Mansur, 
Christine Bucknall, Rekha Chaudhuri, David Price, Chris E Brightling, Liam G Heaney, on 
behalf of the British Thoracic Society Difficult Asthma Network. Comorbidity in severe 

39 | Page 
 
 
 
asthma requiring systemic corticosteroid therapy: cross-sectional data from the Optimum 
Patient Care Research Database and the British Thoracic Difficult Asthma Registry (2016). 
Thorax 2015-207630. 
18. Okoli C & Pawlowski SD. The Delphi method as a research tool: an example, design 
considerations and applications. (2004) Inf. Manage. 42: 15–29. 
19. Архипов В.В., Григорьева Е.В., Гавришина Е.В. Контроль над бронхиальной астмой 
в 
России: 
результаты 
многоцентрового 
наблюдательного 
исследования 
НИКА/Пульмонология - 2011.-N 6.-С.87-93. 
 

40 | Page 
 
 
 
 
9. APPENDIX: Main variables 
 
 
Category 
Variable’s Fields Names 
Response options 
(if appliable) 
1 
Inclusion 
Criteria 
Is the patient suffering from 
uncontrolled asthma and taking 
medium-to-high doses of ICS? 
Please check one of the following: 
1. At the stage 5 GINA 
2. (a) Uncontrolled in Stage 4: There 
are symptoms of severe asthma 
2. (b) Uncontrolled in stage 4: there 
are exacerbations requiring OCS 
 
No/Yes 
2 
Inclusion 
Criteria 
The patient meets the criteria for the 
inclusion in RSAR 
No/Yes 
3 
Detailed 
description of 
the patient 
Visit date 
DD / MM / YYYY 
4 
Detailed 
description of 
the patient 
Date of Birth 
Age at the moment of examination 
DD / MM / YYYY  
Full age (calculated 
automatically) 
5 
Detailed 
description of 
the patient 
Gender 
Male/female 
6 
Detailed 
description of 
the patient 
Race 
Caucasian / Southeast 
Asian / Northeast Asian / 
African / Mixed / Other 
7 
Detailed 
description of 
ППТ 
Decimal 
number 
(calculated automatically) 

41 | Page 
 
 
 
the patient 
8 
Detailed 
description of 
the patient 
BMI 
Decimal 
number 
(calculated automatically) 
9 
Detailed 
description of 
the patient 
Height 
Decimal number 
10 
Detailed 
description of 
the patient 
Weight 
Decimal number 
11 
Detailed 
description of 
the patient 
Was the bronchial thermoplastics 
given to the patient? 
No/Yes 
12 
Occupation 
What 
is 
the 
current 
patient’s 
occupation? 
Free text entry 
 
Occupation 
Occupational risks 
 
-  at the moment;  
- in anamnesis. 
13 
Anamnesis 
What is current smoking status of a 
patient? 
Never smoked / Former 
smoker / Currently 
smokers 
14 
Anamnesis 
-Number of cigarettes smoked daily? 
(if marked "ex-smoker", "currently 
smokes") 
Number 
15 
Anamnesis 
-Years of smoking? (please indicate 
the period of time during which the 
patient smoked continuously) 
Number 
16 
Anamnesis  
-Pack-Years 
Number (calculated 
automatically) 
17 
Anamnesis 
-Years, 
passed 
after 
you 
quit 
smoking? 
(please specify the time period from 
which the patient stopped smoking) 
Number 

42 | Page 
 
 
 
18 
Anamnesis 
At what age did the symptoms of 
asthma start to appear in the patient? 
Full years or months, if <1 year 
Number 
19 
Anamnesis  
Number of exacerbations requiring 
treatment 
with 
systemic 
glucocorticosteroids in the last 12 
months? 
Number 
20 
Anamnesis 
The total number of episodes of 
invasive pulmonary ventilation? 
Number 
21 
Anamnesis 
Total number of ambulance calls due 
to asthma in the last 12 months? 
Number 
22 
Anamnesis 
Total number of hospitalizations due 
to asthma in the last 12 months? 
Number 
23 
Anamnesis 
Indicate 
the 
number 
disability 
episodes in the last 12 months (for 
BA). 
Number 
24 
Significant 
concomitant 
diseases 
Atopic dermatitis  
Atopic disease: yes, if atopic 
dermatitis is noted 
Never / in the past / 
currently 
25 
Significant 
concomitant 
diseases 
Allergic rhinitis 
Atopic disease: yes, if allergic rhinitis 
is noted 
Never / in the past / 
currently 
26 
Significant 
concomitant 
diseases 
Non-allergic rhinitis 
Never / in the past / 
currently 
27 
Significant 
concomitant 
diseases 
Chronic rhinosinusitis with polyps 
Never / in the past / 
currently 
28 
Significant 
concomitant 
diseases 
Chronic rhinosinusitis without polyps 
Never / in the past / 
currently 

43 | Page 
 
 
 
29 
Treatment of 
significant 
concomitant 
diseases 
Atopic dermatitis  
Allergic rhinitis 
Non-allergic rhinitis 
Chronic rhinosinusitis with polyps 
Chronic rhinosinusitis without polyps 
Indicate treatment of 
significant concomitant 
diseases 
30 
Significant 
concomitant 
diseases 
Indicate concomitant diseases in the 
patient 
obesity, 
- Type 2 diabetes, 
- Arterial hypertension, 
- IHD, 
- COPD, 
- CHF, 
- CRF; 
other. 
31 
Treatment of 
significant 
concomitant 
diseases 
obesity, 
- Type 2 diabetes, 
- AH, 
- IHD, 
- COPD, 
- CHF, 
- CRF; 
other. 
Indicate treatment of 
significant concomitant 
diseases 
32 
Blood/ 
sputum 
What was the largest number of 
eosinophils of blood (over the last 
year)? 
Decimal number 
33 
Blood/ 
sputum 
- Date of the maximal number of 
eosinophils of blood (for the last 
year) 
DD / MM / YYYY 

44 | Page 
 
 
 
34 
Blood/ 
sputum 
-Was 
the 
greatest 
number 
of 
eosinophils of blood recorded during 
exacerbation? 
No/Yes 
35 
Blood/ 
sputum 
What was the maximal number of 
eosinophils of the blood? (for the last 
year and beyond the exacerbation) 
Decimal number 
36 
Blood/ 
sputum 
Date of the maximal number of 
eosinophils of blood (for the last year 
and without exacerbation) 
DD / MM / YYYY 
37 
Blood/ 
sputum 
Current (last) value of eosinophils 
Decimal number 
38 
Blood/ 
sputum 
-Last 
date 
of 
eosinophils 
measurement 
DD / MM / YYYY 
39 
Blood/ 
sputum 
What was the maximal number of 
eosinophils in sputum (over the last 
year)? (in percentages) 
Decimal number 
40 
Blood/ 
sputum 
- Date of the maximal number of 
eosinophils of blood (for the last 
year) 
DD / MM / YYYY 
41 
Blood/ 
sputum 
What is the current IgE value (last)? 
Decimal number 
42 
Blood/ 
sputum 
- Date of current IgE measurement 
(latest) 
DD / MM / YYYY 
43 
Blood/ 
sputum 
Was the patient's periostin level 
measured? 
- Yes; 
- No; 
45 
Diagnostics  
Was chest radiography performed? 
Normal/ Abnormal/Was 
not performed 
46 
Diagnostics 
Was chest computer tomography 
performed? 
Normal/ Abnormal/Was 
not performed 
47 
Diagnostics 
-Date of chest computer tomography 
DD / MM / YYYY 
48 
Diagnostics 
Was densitometry done? 
No/Yes 
49 
Diagnostics 
Date of densitometry 
DD / MM / YYYY 

45 | Page 
 
 
 
50 
Lung function 
FEV1 before broncholytic 
Decimal number 
51 
Lung function 
FEV1 after broncholytic 
Decimal number 
52 
Lung function 
Functional Vital capacity before 
broncholytic 
Decimal number 
53 
Lung function 
Functional Vital capacity after 
broncholytic 
Decimal number 
54 
Lung function 
Prognosed FEV1 
Decimal number 
(calculated automatically) 
55 
Lung function 
FEV1 before broncholytics (% of 
prognosed) 
Decimal number 
(calculated automatically) 
56 
Lung function 
FEV1 after broncholytics (% of 
prognosed) 
Decimal number 
(calculated automatically) 
57 
Lung function 
Prognosed FVC 
Decimal number 
(calculated automatically) 
58 
Lung function 
FVC before broncholytics (% of 
prognosed) 
Decimal number 
(calculated automatically) 
59 
Lung function 
FVC after broncholytics (% of 
prognosed) 
Decimal number 
(calculated automatically) 
60 
Lung function 
The ratio of FEV1 / FVC before 
bronchodilator 
Decimal number 
(calculated automatically) 
61 
Lung function 
The ratio of FEV1 / FVC after 
bronchodilator 
Decimal number 
(calculated automatically) 
62 
Lung function 
Spirometry 
DD / MM / YYYY 
63 
Lung function 
Was the test for methacholine PC20 / 
histamine/exercise performed? 
No/Yes 
64 
Lung function 
-Date of PC20 test 
DD / MM / YYYY 
65 
Lung function 
- PC20 result 
Decimal number 
(calculated automatically) 
66 
Lung function 
An exhaled nitric oxide test was 
performed? 
No/Yes 

46 | Page 
 
 
 
67 
Lung function 
- Date of analysis for expired nitric 
oxide 
DD / MM / YYYY 
68 
Lung function 
- Results of the analysis for expired 
nitric oxide 
Decimal number 
(calculated automatically) 
69 
Allergic tests 
(ALL) 
Was the environmental allergens test 
performed? 
Determination of specific 
IgE in blood/Scarification 
test/Was not done 
70 
Allergic tests 
(determination 
of specific IgE 
in blood) 
- 
Date of determination of 
specific IgE in blood 
DD / MM / YYYY 
71 
Allergic tests 
(determination 
of specific IgE 
in blood) 
- Was specific IgE in blood positive 
for year-round allergens? 
No/Yes 
72 
Allergic tests 
(determination 
of specific IgE 
in blood) 
+ Indicate the year-round allergens to 
which specific IgE in blood was 
positive (select all applicable) 
 
Dust 
mite 
(eg 
D. 
Pteronyssinus) / cat's hair / 
mixture of molds / dog 
hair / aspergillus / other 
(please specify) 
73 
Allergic tests 
(determination 
of specific IgE 
in blood) 
- Was specific IgE in blood positive 
for seasonal allergens? 
No/Yes 
74 
Allergic tests 
(determination 
of specific IgE 
in blood) 
+ Indicate the seasonal allergens to 
which specific IgE in blood was 
positive (select all applicable) 
 
Trees pollen 
Weeds pollen 
Grasses pollen 
75 
Allergic tests 
(Scarification 
test (ST)) 
-ST date 
DD / MM / YYYY 
76 
Allergic tests 
(Scarification 
test (ST)) 
- Was the ST positive for year-round 
allergens? 
No/Yes 

47 | Page 
 
 
 
77 
Allergic tests 
(Scarification 
test (ST)) 
Indicate year-round allergens (for ST) 
(select all applicable) 
Dust 
mite 
(eg 
D. 
Pteronyssinus) / cat's hair / 
mixture of molds / dog 
hair / aspergillus / other 
(please specify) 
78 
Allergic tests 
(Scarification 
test (ST)) 
- Was the ST positive for seasonal 
allergens? 
No/Yes 
79 
Allergic tests 
(Scarification 
test (ST)) 
+ Indicate the seasonal allergens to 
which the ST was positive (select all 
applicable) 
 
Trees pollen 
Weeds pollen 
Grasses pollen 
80 
Asthma 
symptom 
control 
Do patients experience symptoms 
during the day? (more than twice a 
week) 
No/Yes 
81 
Asthma 
symptom 
control 
Does the patient have any limitation 
of physical activity due to asthma? 
For what period of time? 
No/Yes 
82 
Asthma 
symptom 
control 
Does patient awake  
For what period of time? 
No/Yes 
83 
Asthma 
symptom 
control 
Does patient need to use asthma 
symptom relief drugs more than 2 a 
week? 
No/Yes 
84 
Asthma 
symptom 
control 
Is the patient’s lung function (PEF or 
FEV1) < 80% of prognosed or best 
per 
sonal result (if known)? 
No/Yes 
85 
Drugs to 
manage 
asthma 
Does patient use currently oral GCS? 
No/Yes – 
Dose 
- Duration of use 
- Registered adverse 

48 | Page 
 
 
 
effects of OCS 
86 
Drugs to 
manage 
asthma 
Did patient use OCS earlier? 
No/Yes – 
Dose 
- Duration of use 
- Registered adverse 
effects of OCS 
87 
Drugs to 
manage 
asthma 
-Date of OCS use start 
DD / MM / YYYY 
88 
Drugs to 
manage 
asthma 
Does patient use currently combined 
therapy 
(ICS+LABA)? 
(please, select from the list) 
No 
budesonide + formoterol 
fluticasone furoate + 
vilantherol 
fluticasone propionate + 
salmeterol 
beclomethasone + 
formoterol 
other 
89 
Drugs to 
manage 
asthma 
Does the patient currently take ICS + 
LABA 
as 
a 
fixed 
or 
free 
combination? 
- Fixed combination 
- Free combination 
90 
Drugs to 
manage 
asthma 
- Date of onset of combined 
ICS+LABA therapy 
DD / MM / YYYY 

49 | Page 
 
 
 
91 
Drugs to 
manage 
asthma 
Is the patient currently taking ICS 
(only)? 
(please select from the list) 
No 
triamcinolone acetonide 
mometasone furoate 
fluticasone propionate 
fluticasone furoate 
ciclesonide 
flunysonide 
budesonide 
beclomethasone 
other 
92 
Drugs to 
manage 
asthma 
- Date of start / end of ICS intake 
DD / MM / YYYY 
93 
Drugs to 
manage 
asthma 
Is the patient currently taking LABA 
(only)? 
(please select from the list) 
No 
formoterol 
salmeterol 
indacaterol 
olodaterol 
other 
94 
Drugs to 
manage 
asthma 
- Date of start / end of LABA intake 
DD / MM / YYYY 
95 
Drugs to 
manage 
asthma 
Is the patient currently taking LAMA 
(only)? 
(please select from the list) 
No 
aclidinium 
tiotropium 
umeclidinium 
glycopyrronium 

50 | Page 
 
 
 
other 
96 
Drugs to 
manage 
asthma 
- Date of start / end of LAMA intake 
DD / MM / YYYY 
97 
Inhalation 
technique 
assessment. 
 
Appropriate 
Inappropriate (if so, the next 
question) 
Crucial mistakes 
Present 
Absent 
 
98 
Drugs to 
manage 
asthma 
Is the patient currently taking 
theophylline? 
(please select from the list) 
No 
theophylline 
aminophylline 
other 
99 
Drugs to 
manage 
asthma 
- Date of start / end of theophylline 
intake 
DD / MM / YYYY 
100 
Drugs to 
manage 
asthma 
Is the patient currently receiving a 
leukotriene 
receptor 
antagonist 
(LTRA)? 
(please select from the list) 
No 
zafirlukast 
montelukast 
other 
101 
Drugs to 
manage 
asthma 
- Date of start / end of LTRA intake 
DD / MM / YYYY 
102 
Drugs to 
manage 
Is the patient currently receiving 
treatment 
targeted 
on 
No/Yes 

51 | Page 
 
 
 
asthma 
immunoglobulin E (Anti-IgE)? 
(omalizumab is prescribed) 
 
103 
Drugs to 
manage 
asthma 
Date of start / end of Anti-IgE intake? DD / MM / YYYY 
104 
Drugs to 
manage 
asthma 
Is the patient currently receiving 
treatment targeted on IL-5 (Anti-IL-
5)? 
 (please select from the list) 
No 
reslisumab 
mepolizumab 
benalizumab 
dupilumab (?) 
tezepelumab (?) 
other 
(new biotechnological 
preparations will be added 
after approval and start of 
use in Russia) 
105 
Drugs to 
manage 
asthma 
Date of start / end of Anti-IL5 intake?  DD / MM / YYYY 
106 
Drugs to 
manage 
asthma 
Does the patient currently receive 
antibiotic 
treatment 
with 
the 
macrolide group? 
(please select from the list) 
No 
azithromycin 
clarithromycin 
erythromycin 
roxithromycin 
fidaxomycin 
telithromycin 
other 
107 
Drugs to 
manage 
Date of start / end of  macrolide  DD / MM / YYYY 

52 | Page 
 
 
 
asthma 
intake? 
108 
Compliance 
Is there a non-compliance with the 
treatment regimen? 
No 
Yes: 
- dosage; 
- frequency of reception; 
- absence of all prescribed 
medications; 
- other 
109 
Management 
plan 
Are there other factors affecting the 
symptoms of severe asthma? 
- "interruptions" in state 
preferential drug 
provision; 
- Other 
110 
Management 
plan 
Current patient management plan? 
(Select all that apply) 
-Discharged for outpatient 
treatment of asthma 
-Current optimization of 
treatment 
- Prescription of biological 
therapy 
(specific 
drugs 
can be found in the list of 
active medicines) 
-Bronchial thermoplastics 
-Supporting 
oral 
glucocorticosteroids 
-Other (please specify) 
111 
Management 
plan 
Recommendations on asthma therapy 
(drug (s), dose, regimen) at the 
current visit: 
 
5 rows to enter 
- 
- 
- 
- 
- 

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112 
Management 
plan 
Supposed date of next visit  
A reminder for the doctor 
and patient: 
- For two weeks, 
- for 1 week, 
- for 1 day. 
113 
 
What are the sources of preparations 
for baseline therapy in the patient? 
- Self-acquisition; 
 - State preferential drug 
provision: 
1) Federal  
2) Regional  
4) 
In 
hospital 
drug 
provision 
5) 
High 
technology 
medical care; 
6) Territorial programs; 
7) Other. 
114 
Tolerability 
Do patients have AE due to the 
therapy for asthma? 
-Indicate 
the 
suspected 
drug. 
-Fill in the AE registration 
form (at each visit and the 
form on AE should be 
attached to the company’s 
drugs: 
1) symbicort turbuhaler 
(budesonide + formoterol) 
2) pulmicort suspension 
(budesonide) 
115 
Tolerability 
Did 
the 
patient 
take 
part 
in 
randomized clinical trials to study 
monoclonal antibodies use?  
- No 
- YES: 
 Name of study? 
 
 
 
 
 
 
 
 
 
 

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