Portuguese Severe Asthma Registry: Getting Answers for Severe Asthma Patients
Portuguese Severe Asthma Registry: Getting Answers for Severe Asthma Patients
Asthma currently affects 358 million individuals worldwide, posing a substantial burden on
 health care systems. In particular patients with severe asthma have higher morbidity,
 mortality and asthma-related costs than non-severe patients. The management of severe asthma
 is still an unmet need and improving the disease-related knowledge is important to optimize
 care pathways. Registries provide an opportunity to phenotypically describe a cohort of
 patients in real-world settings. We hypothesize whether patient profiling based on data in
 the Portuguese Severe Asthma Registry (RAG - Registo de Asma Grave) may contribute to
 identify predictors of disease control and therapeutic response.

 This study aims to (Coprimary Objectives): 1) Identify multidimensional phenotypes associated
 with health outcomes and therapeutic responses, based on demographic characteristics,
 clinical features and biomarkers; 2) Explore novel composite endpoint measures of disease
 control and evaluate its association with the different severe asthma profiles.

 This is a cross-sectional, observational, multicenter, real-world study. The study population
 are the patients of all ages with severe asthma included in the RAG, until Dec 2021. It is
 estimated that 150 patients will be enrolled, in approximately 12 sites throughout Portugal,
 which is expected to be a representative sample of Portuguese patients with severe asthma.
 Eligible patients will be invited to integrate RAG by clinicians at scheduled clinic
 appointments. The criteria for patients' inclusion in the RAG is based on the definition of
 Severe Asthma by GINA guidelines, based on step of treatment, adherence and comorbidities
 management. An additional inclusion criterion is the patient's signed consent to have his/her
 data included in the registry.

 The main data source of this project is the data collected by RAG, an electronic Case Report
 Form. Descriptive and inferential statistics will be used to characterize and compare the
 characteristics across different sub-groups. Advanced data-driven statistical methods, such
 clustering analysis and latent class analysis, will be used for phenotype classification.
 Multivariate logistic regression modelling and Classification and Regression Tree analysis
 will be considered.

 To address the potential limitations, the RAG has database specifications concerning data
 definitions and parameters and data validation rules enabling collection of data in the same
 manner for every patient, with specific and consistent data definitions. To minimize errors
 related to data completeness and consistency, several validation rules have been implemented
 and periodic data audits are planned. To avoid unnecessary burden within the clinical
 workflow, data will be collected at the time of routine medical appointments by the clinician
 and data entry personnel will assist on this task.
BACKGROUND Asthma currently affects 358 million individuals worldwide, posing a substantial
 burden on health care systems. Patients with severe asthma have higher morbidity, mortality
 and asthma-related costs than non-severe patients. Asthma phenotype definition is
 particularly important in patients with severe disease and who are not controlled with usual
 therapy. The management of severe asthma is challenging, involving treatment of
 comorbidities, optimization of medication adherence, and the choice of the best medical
 treatment for each patient, which remains one of the greatest difficulties. In the last
 decades, efforts have focused on the classification of different subsets of asthma patients
 according to its epidemiology, immunology, biomarkers, response to specific
 pharmacotherapies, and long-term prognosis. These are broadly called phenotypes: a set of
 clinical features of a specific genetic pattern in a specific environment. The main goal of
 the phenotype philosophy is the development of targeted and personalized pharmacological
 approaches. Allergic and nonallergic asthma are very similar in their clinical presentation
 and are distinguished by the presence or absence of clinical allergic reaction and in vitro
 Immunoglobulin E (IgE) response to specific aeroallergens. Although they both show several
 distinct clinical features and different biomarkers, there are no ideal biomarkers to
 stratify asthma phenotypes and guide therapy in clinical practice. A detailed and systematic
 clinical history, including comorbidities, spirometry with bronchodilator test, a skin or
 blood test panel for specific IgE (sIgE) to common regional airborne allergens, and a
 peripheral blood eosinophil count are very useful for establishing phenotypes. This
 distinction has prognostic and therapeutic implication, including the use of biologic
 therapies. It is not easy to choose between the biologics to be the first-choice treatment,
 and head-to-head comparison studies between them do not exist. Hence, clinical observational
 studies of real-world large patient populations should contribute to the knowledge on how to
 select the best biologic treatment for an individual patient.

 Research networks are playing a critical role in the advances in severe asthma. They provide
 both multicenter severe asthma studies and real-life severe asthma patient registers. REAG,
 Rede de Especialistas em Asma Grave, is an open collaborative network of asthma specialists
 (allergists, pediatricians, and pulmonologists) who manage severe asthma patients in
 Portuguese hospitals. The foundational principle of REAG is the informal peer collaboration
 among colleagues with different medical specialties and backgrounds, maintaining a
 nonhierarchical organization and consensual decision processes to improve sharing of medical
 experience, data, and knowledge. Since 2011, this network of experts has been working towards
 a better care of severe asthma patients by (1) promoting a better coordination between
 medical specialties for early diagnosis and referral of severe asthma patients; (2)
 describing and implementing harmonized procedures to adopt in severe asthma healthcare; and
 (3) improving scientific knowledge on severe asthma in Portugal. In 2013, REAG conducted a
 12-month study on patients with severe asthma under biological treatment. This was the first
 national effort of standardizing outcome assessment. In this study, REAG showed that in spite
 of being treated with omalizumab, 1/3 of the patients needed unscheduled medical care because
 of asthma and 29% had to start using or had to increase the dosage of oral corticosteroid
 (OCS). We could speculate whether before starting omalizumab the asthma control in these
 patients was even worse or if the treatment with omalizumab was ineffective and should be
 discontinued, but due to data constraints, we could not confirm these hypotheses. In face of
 the need to gather evidence on severe asthma in Portugal, in 2018, REAG developed and
 implemented the Portuguese Severe Asthma Registry (Registo de Asma Grave Portugal - RAG).

 Disease registries are recognized as powerful tools to improve disease-related knowledge.
 They consist of organized systems that use observational study methods to collect uniform
 data aiming at evaluating specific outcomes for a heterogeneous population defined by a
 particular disease. Registries promote the harmonization of the healthcare delivery by
 physicians, the improvement of clinical processes, and are useful in severe asthma systematic
 evaluation, enabling the assessment of the effect of different therapies in the context of a
 single disease. They also provide an opportunity to improve the understanding of different
 phenotypes of asthma and their clinical implications, reported in a study based on the
 British Thoracic Society Severe Asthma Registry, which demonstrated the differences in
 severity of asthma in adult patients and the differences in inflammatory markers in
 late-onset asthma (Newby 2014). Another study on the Australian Severe Asthma Web-Based
 Database demonstrated that treatable traits in severe asthma patients can be identified using
 registry data and that they can be related with severe outcomes. The Portuguese Severe Asthma
 Registry - RAG is a national web-based disease registry of adult and pediatric patients with
 severe asthma. It was created in line with the International Severe Asthma Registry (ISAR)
 and with Severe Heterogenous Asthma Research collaboration, Patient-centered collaboration
 (SHARP). Specifically, RAG collects data with potential to improve the healthcare delivery by
 identifying the best treatment practices and standardizing the management of the disease
 control.

 Patients with severe asthma included in RAG will be considered to 1) identify
 multidimensional phenotypes associated with health outcomes and therapeutic responses, based
 on demographic characteristics, clinical features and biomarkers and 2) Explore novel
 composite endpoint measures of disease control and evaluate its association with the
 different severe asthma profiles. Additionally, to explore predictors of future risk in
 different asthma profiles

 METHODS This is a multicenter, cross-sectional, observational real-world study; based on data
 collected from the Portuguese Severe Asthma Registry, the RAG.

 The main data source of this project is the data collected by RAG, an electronic Case Report
 Form (eCRF) specially designed for the study. Data collection will follow the Documentation
 of procedures (see section "Activities description" - Activity 1 Setup and Management). Only
 authorized physicians/investigators will have access to RAG through a unique login and
 password. Data entry will be performed by each physician, assisted by data entry personnel,
 during scheduled medical appointments. Additionally, to complete missing data, medical
 records may be consulted. (see section "Activities description" - Activity 3 Data
 collection). Data collectors will be trained in a structured manner. The investigator will
 allow study-related monitoring, audits, providing direct access to source data documents. The
 data collected by the RAG includes demographic data; asthma care information; comorbidities;
 atopy and inflammation biomarkers; diagnostic tests and study assessments; asthma control;
 therapy (see section "Activities description" - Activity 3 Data collection).

 Methods are described in detail in following paragraphs (Activities 1-6).

 Activity 1. Setup and Management (18 months) This activity will be responsible for the
 management of the entire project, including the setup and coordination, and financial
 support.

 The first task comprises setup activities and coordination, including:

 1. Development and management of the documentation of procedures, containing all the
 registry policies, protocols, procedures, and quality requirements, as well as a
 complete data dictionary listing all the data elements to be collected and their
 definitions

 2. Publication of the summary protocol in ClinicalTrials.gov and, and at the end of the
 study, publication of the results summary in the same public registry

 3. Recruitment of the hospitals and physicians:

 1. Identify the eligible hospitals specialized in severe asthma, through REAG

 2. Identify physicians in each eligible hospital, and through REAG

 3. Appraise potential hospital and physician characteristics to ensure a
 representativeness samples of Portuguese severe asthma patients, focusing in the
 setting, training, volume of severe asthma cases, ability to recruit patients,
 internal resources, availability of internet connectivity and prior performance,
 including reliability and accuracy of data entry

 4. Approval from the administration boards of the recruitment sites

 5. Kick-off meeting with physicians from all participating sites.

 4. Definition of the strategies to retain hospitals and physicians, by regular standardized
 training meetings, site audit and retraining visits, feedback, telephone helpline

 5. Preparation of the data sources

 The main data source for this project is the RAG, an eCRF. The preparation of the RAG
 for this project includes the:

 1. Creation of new profiles (with independent logins) for data management

 2. eCRF version update with extra variables and functionalities for the harmonization
 with ISAR and SHARP

 3. Creation of data dictionary that contains detailed descriptions of each variable
 used by the registry

 6. Establishment of contracts and collaborative agreements with the involved stakeholders:
 Contract Research Organization (CRO), Investigators, software developers

 7. Writing and production of 3 Internal Progress Summaries (each 3 months) containing
 summaries on the registry growth, trends, onsite visits, data completeness and cleaning

 8. Writing and production of a Final Report on patients' enrollment, data collection and
 cleaning.

 The outputs of this activity will be 3 progress summaries, 1 final report

 Activity 2. Patients' enrolment (12 months) Patients' recruitment is the essential element in
 the operation of the registry. It is estimated that 150 severe asthma patients will be
 enrolled, in approximately 12 sites throughout Portugal. Enrollment will be competitive, with
 a minimum of 10 patients and a maximum of 30 patients per site. Eligible patients will be
 invited to integrate RAG by physicians at scheduled medical appointments. Patients will be
 informed that participation on RAG is free and voluntary and that they may, in any moment and
 without penalty, withdraw the registry or verify and/or delete their data. Patients will also
 be informed on the purposes of RAG, the data collected, and the implications of participating
 in this registry. The informed consent form will be automatically generated at the time of
 inclusion. Only patients that agree, by a clear affirmative consent given by a written
 statement will be included in RAG.

 Recruitment and retention strategies will be applied according with the definition
 established in the previous tasks.

 The output of this activity will be the inclusion of at least 150 new patients with severe
 asthma in RAG.

 Activity 3. Data collection (12 months) This activity aims to collect data in a uniform
 manner for every patient. Data collection will follow the Documentation of procedures
 established in the setup task. Data entry will be performed by each physician, assisted by
 data entry personnel, during scheduled medical appointments. Additionally, to complete
 missing data, medical records may be consulted.

 The data collected though the eCRF of the RAG includes 7 domains: 1) Demographic data:
 gender, month and year of birth, birthplace, place of residence, body mass index, education
 years, smoking habits, occupation, family history of asthma and of asthma-related death,
 personal history of respiratory infections during early childhood, environmental exposures;
 2) Asthma care information: age at asthma diagnosis, age at severe asthma classification,
 first year of specialized asthma follow-up, medical specialty of the attending physician; 3)
 Comorbidities; 4) Atopy and Inflammation biomarkers: Atopy (serum IgE, allergic
 sensitization, type(s) of diagnostic test used to confirm allergic sensitization);
 Inflammation biomarkers (Fractional exhaled Nitric Oxide - FeNO, blood eosinophils, sputum
 eosinophils, sputum neutrophils); 5) Diagnostic tests and study assessments: Lung function
 tests (FEV1, FVC, MEF, residual volume, specific airway resistance, carbon monoxide diffusion
 capacity, bronchial challenge test); Imaging (X-ray, thorax CT scan, sinus CT scan, bronchial
 endoscopy, bone densitometry); Arterial blood gases; 6) Control: Asthma-related healthcare
 utilization in previous 12 months or since the last appointment, when at follow-up visit
 (number of routine primary care medical appointments, routine hospital care medical
 appointments, nonscheduled medical appointments, emergency department visits, hospital
 admissions, intensive care unit admissions, need for mechanical ventilation, school or labor
 absenteeism); Asthma control assessment according to GINA recommendations (frequency of
 daytime symptoms, activity limitations due to asthma, any night awakening due to asthma,
 frequency of use of reliever medications for asthma, respiratory function, number of
 exacerbations in last year/week); Asthma control self-questionnaires (CARAT - Control of
 Allergic Rhinitis and Asthma Test and ACT - Asthma Control Test); 7) Therapy: Asthma
 medication OCS, ICs, LTRAs, LABAs, SABAs, LAMAs, SAMAs, xanthines, immunosuppressors,
 immunotherapy, monoclonal antibodies, antibiotics, therapy adherence, inhalation technique);
 Other medication (proton pump inhibitor, anti-depressive/anxiolytics, intranasal steroids,
 antihistamines, long-term oxygen therapy, non-invasive ventilation).

 To ensure the quality of the data collection, data collectors will be trained in a structured
 manner. Furthermore, a data monitor will review samples of data to identify potential sites
 at higher suspicion for inaccuracy or intentional errors, such as discrepancies between
 enrolment and logs, missing data, and overly high or low enrolment and onsite periodic audits
 will be conducted for the identified sites.

 Security features compliant with the European GDPR and required procedures according to this
 legislation are incorporated into the RAG. RAG does not record any identifiable personal data
 from patients (e.g., date of birth is replaced by the month and year of birth, no ID numbers
 are registered, and patients' names are pseudo-anonymized by replacing with a code number).

 The outputs of this activity will be a complete database from a representative sample of at
 least 150 patients.

 Activity 4. Data cleaning (12 months) This activity aims to correct data problems and prepare
 the database for analysis.

 A data monitor will be responsible for data cleaning to assure validity and quality of the
 data in the registry. Data checks to assess sample size and compare data entered into the
 registry against predefined rules will be conducted, by checking and correcting incorrect or
 out-of-range values, responses that are logically inconsistent with other responses in the
 database, and duplicate patient records. When missing values are detected a reminder will be
 sent to the data collector to check and correct them.

 To improve data quality, automated simple data checks are specified in the database of RAG
 for presentation at the time of data entry. To detected unexpected discrepancies and abnormal
 trends a periodic manual data cleaning will be performed.

 Tracking of the data entered and data cleaned will be reported. The outputs will be a
 database ready for data analysis integrating all patients registered in RAG until December
 2020.

 Activity 5. Data analysis (6 months) The aim of data analysis is the identification of
 patients' profiles and its association with disease control measures.

 Descriptive statistics will be used to characterize all collected variables. The normality of
 each variable will be investigated with Kolmogorov-Smirnoff and visual analysis of
 histograms. Relative and absolute frequencies will be used for categorical and mean, median,
 standard deviation, maximum, minimum, interquartile range for continuous variables.
 Inferential statistics will also be conducted to compare the characteristics across different
 sub-groups using chi-square tests, one-way analysis of variance or Kruskal-Wallis tests.
 Correlations with Pearson's coefficient or Spearman's rho will also be used to measure the
 association between characteristics. Advanced data-driven statistical methods, such as
 distance-based (clustering analysis) and model-based (latent class analysis), will be used
 for phenotype classification. The importance of the variables that best distinguish between
 the obtained phenotypes will then be explored. Multivariate logistic regression modelling and
 Classification and Regression Tree (CART) analysis will be considered. Other appropriate
 statistical methods can also be applied.

 Activity 6. Manuscript writing and Dissemination (10 months) The aim of this activity is to
 disseminate the project, including the scientific writing.

 The results from this project will be disseminated through the participation on a scientific
 international meeting and the publication of a full-text original article in an international
 journal indexed in the Web of Science.

 The outputs will be the publication of a full-text original article and of a conference
 abstract.

 LIMITATIONS Real-world studies, presented as a pragmatic approach to everyday clinical
 practice, are fundamental to assess the therapeutic responses and clinical outcomes in
 patients with severe asthma. However, this type of studies may have some limitations.

 The first is the risk of divergent approaches adopted by each recruiting site. To address
 this limitation the RAG includes database specifications concerning data definitions and
 parameters and data validation rules that were determined through consensus by the physicians
 of the REAG. As so data will be collected in the same manner for every patient, with specific
 and consistent data definitions. To minimize errors related to data completeness and
 consistency, several logical and validation rules have been implemented and periodic data
 audits are planned.

 This study relies on physicians' active involvement, as they are responsible for making the
 decision about the inclusion of a patient in RAG and are responsible for inserting patients'
 data. To avoid unnecessary burden within the clinical workflow, data will be collected at the
 time of routine medical appointments, several features to support healthcare providers on
 severe asthma care are implemented in RAG and data entry personnel will assist on this task.
 Importantly, as suggested by the members of REAG, RAG includes the automatic generation of
 clinical notes based on the inputted data that can be pasted into the institutional
 electronic clinical record of the patient, avoiding duplication of effort.

 An additional challenge will be the retention of sites/physicians. The participation in the
 RAG should not be an overload on the usual care that physicians provide to their patients and
 features have been implemented to reduce the burden of participation. Additionally, the
 participation in the RAG may be seen as an opportunity to increase the communication of the
 clinician with their patient, and a to contribute to the knowledge on severe asthma.
 Retention strategies such as regular standardized training meetings, site visits, feedback
 and reminders, will be applied.

 Informed consent and data protection Informed consent forms were prepared according to age -
 under 6, between 6 and 15, between 16 and 17 and above 17 years old - in compliance to the
 European General Data Protection Regulation (GDPR). The informed consent form must be
 downloaded, dated and signed at the time of inclusion. The informed consent forms are
 automatically generated in triplicate, in order to provide one copy to the patient, one to
 the investigator and another to be included in the institutional clinical process of the
 patient.

 Security features compliant with the European GDPR and required procedures according to this
 legislation are incorporated into the RAG. RAG does not record any identifiable personal data
 from patients (e.g., date of birth is replaced by the year of birth, no ID numbers are
 registered, and patients' names are pseudo-anonymized by replacing with a code number).
Inclusion Criteria:

 -  be under treatment on step 4 or 5 according to GINA recommendations (GINA 2018);

 -  have verified the optimization of treatment adherence and comorbidities management;

 -  provide the signed consent to have his/her data included in the registry

 Exclusion Criteria:

 -  patients without given consent to participate will be excluded.