Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT04714567 |
| Other study ID # |
10886 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 1, 2021 |
| Est. completion date |
December 2022 |
Study information
| Verified date |
November 2022 |
| Source |
Sociedade Portuguesa de Pneumologia |
| Contact |
Cláudia Ch Loureiro, MD, PhD |
| Phone |
919795255 |
| Email |
cl_loureiro[@]hotmail.com |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational [Patient Registry]
|
Clinical Trial Summary
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.
Description:
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).
