https://orcid.org/0000-0001-7876-4850
Abstract
Background and purpose of the study
The utility measure is a method to quantify health-related quality of life according to the preference values that patients attach to their health status. This study aimed to estimate the utility measure of patients with controlled and uncontrolled severe asthma (SA) in Spain, separately. Additionally, other characteristics (sociodemographic, clinical, and healthcare resource use [HCRU]) were also assessed for both SA populations.
Methods
This cross-sectional study included 159 patients with SA in Spain. Data were collected from medical records and directly from the patients during the study visit. Asthma Control Questionnaire (ACQ)-5 was used to classify patients with controlled and uncontrolled SA.
Results
Most of the patients were female (72.0% uncontrolled SA and 63.6% controlled SA). The mean (SD) EuroQol-5D (EQ-5D-5L) score was 0.88 (0.14) and 0.70 (0.25) in controlled and uncontrolled SA, respectively. The mean (SD) Asthma Quality-of-Life-5D (AQL-5D) score was 0.93 (0.09) and 0.85 (0.09) in controlled and uncontrolled SA, respectively. Emergency visits (19.2 vs. 2.7%) and hospitalizations (7.7% vs. no hospitalization) were more common among uncontrolled SA than controlled SA. Mean (SD) number of visits to primary care and pneumologists in uncontrolled SA vs. controlled SA was 4.1 (2.8) vs. 2.5 (3.0) and 3.7 (3.5) vs. 2.8 (2.2), respectively.
Conclusion
The study provides data on utility measures among patients with SA in Spain for the first time. Patients with uncontrolled SA had lower HRQoL and higher HCRU than patients with controlled SA. Therefore, the implementation of measures that improve HRQoL among patients with uncontrolled SA is highly recommended.
KEY POINTS FOR DECISION MAKERS
Despite the existence in Spain of validated asthma questionnaires, the impact of severe asthma on quality of life, depending on whether it is controlled or not, had never been assessed.
This study, which included 159 patients, was conducted to fill the gap above by obtaining two utility measures for quality of life, a generic one using the EQ-5D questionnaire (which can be used for comparison with other chronic conditions) and an asthma-specific one using the AQL-5D questionnaire.
Patients with uncontrolled SA had a lower utility measure than patients with controlled disease and, therefore, a lower quality of life. In addition, patients with uncontrolled SA also had higher use of healthcare resources.
These results highlight that the implementation of measures that improve the quality of life among patients with uncontrolled SA is highly recommended.
Background
Severe asthma (SA) is a heterogeneous condition identified by a variety of molecular, biochemical, and inflammatory characteristics and structure-function impairments (Citation1). According to the Spanish National Guideline for the Management of Asthma (GEMA) 5.2 criteria, asthma can be classified based on its severity (intermittent, mild persistent, moderate persistent, or severe persistent) or the level of asthma control (controlled, partly controlled, or uncontrolled) (Citation2). The European Respiratory Society and the American Thoracic Society (ERS/ATS) in 2014 defined SA as a score of ACT < 20 during high-dose ICS therapy with an additional controller or during OCS therapy for more than six months per year. The Global Initiative by Asthma (GINA) 2022 report, clarified that SA is an asthma that is uncontrolled despite high-dose ICS-LABA, or that requires high-dose ICS-LABA to remain controlled (Citation3). Severe uncontrolled asthma is defined as the asthmatic disease that persists poorly controlled despite treatment with a combination of inhaled corticosteroid (ICS)/long-acting beta2 agonist (LABA), at high doses of ICS in the previous 12 months, or oral glucocorticoids (OCS) for at least six months of the same period.
Despite the fact that SA diagnosis can be easily established and rigorous, optimized follow-up treatment is available, 75% of patients with SA do not achieve adequate symptom control (Citation4), and present with significant morbidity and mortality, along with treatment associated psychological and socioeconomic burdens (Citation5). These burdens can be attributed to severe symptoms, frequent and life-threatening exacerbations, increased comorbidity burden, and the intense pharmacological treatment associated with SA (Citation6).
The impact of severe asthma extends beyond these measures and impedes a person’s health-related quality of life (HRQoL). Of note, HRQoL is an independent predictor of clinical outcomes in asthma, such as exacerbations, urgent doctor visits, and presentations at emergency departments. Health-related utilities are defined as the degree of preference for reaching a certain health status, normally expressed with values between 0 (death) and 1 (healthy life). In the context of health economic evaluation, preference-based measures (PBMs) are used to represent the quality-of-life impact component of the quality-adjusted life-year (QALY) in cost-utility analyses (Citation6). The instrument is the measure of choice for many health technology assessment bodies, including the National Institute of Health and Care Excellence (NICE) in England (Citation7).
Concerns about the relevance and sensitivity of generic PBMs in some conditions, such as asthma, have prompted the development of a number of condition-specific PBMs. Moreover, while it is recognized that generic PBMs sometimes may miss or underestimate important health-related quality of life (HRQoL) changes, from the perspective of economic evaluation, the focus is whether the measure “is sensitive enough.” The increasing emphasis on PROs in health care decision making has prompted greater rigor in the evidence to support the instruments used, to ensure the instrument assesses the relevant and important aspects of the target concept of measurement.
One of the ways to obtain utilities is through the use of indirect methods with the application of generic HRQoL questionnaires, such as EuroQoL 5 dimensions (EQ-5D) (Citation8). The GEMA 5.2 guidelines and the GINA recommend two questionnaires for the evaluation of asthma control, namely the ACT and the ACQ (Citation2,Citation3).
A cross-sectional study in Spanish hospitals reported that among patients with uncontrolled SA, mean ACQ (SD) score was 3.8 (1.0) and 54.2% had high levels of total serum IgE, indicating inadequate asthma control (Citation9). Another Spanish study showed that factors like advanced age, lower educational level, and poor control of asthma are significantly associated with a worse HRQoL in all the dimensions assessed by the EQ-5D scale. The baseline severity of the asthma and having been admitted to hospital are related to a worse HRQoL (Citation10).
Both questionnaires ACT and the ACQ are validated in the Spanish population; however, the reliability of both questionnaires for assessing utility in patients with SA is limited. Other questionnaires, such as the Asthma Quality of Life Questionnaire (AQLQ), are based on patient-related outcomes and have specific objectives for measuring HRQoL in patients with asthma (Citation11,Citation12). This questionnaire is well-validated in Spain.
Generally, for the cost-utility analyses, utility values used by the National Institute for Health and Care Excellence (NICE) are adapted, but the transferability of results is considered a limitation in economic evaluations. A review by Knies et al. (Citation13) discusses the international transferability of utilities derived from EQ-5D questionnaires. The authors found considerable differences in national EQ-5D value sets and discouraged the uncritical application of utilities from other countries to the individual setting. These large differences also reflect methodological differences between valuation studies which made speculations in the field challenging (Citation14). The limited use of the questionnaires in clinical practice made it quite difficult to obtain local data about utility measures. This study was undertaken to fill this gap.
The objective of this study was to estimate the measure of utility associated with patients with SA in Spain, depending on whether it is controlled or not. In addition, this study contrasts two utility measures for HRQoL in patients with SA. One of the utility measures was generic using EQ-5D-5L (provides data that can be used in comparison with other chronic conditions) and the other was disease-specific, using AQL-5D (assesses a specific disease).
Methods
This non-interventional, cross-sectional, multicenter cohort study was conducted among patients with SA attending Spanish sites. The only study visit performed coincided with one of those performed by the patients as part of routine follow-up for their disease, without interfering with the usual clinical practice of the phyallergologists). No diagnostic or therapeutic interventions outside of routine clinical practice were applied.
Patients with SA who participated in the study, were assigned into two balanced cohorts regarding the level of asthma control: controlled and uncontrolled SA (1:1). The sample size of the study aimed to estimate the utility measure associated with patients with severe asthma in Spain, depending on whether they are controlled or not. Based on this, 73 uncontrolled and 75 controlled severe asthma patients were needed to allow us to estimate the utilities of AQL-5D with an error of 0.05 and 0.025 and assuming a deviation of 0.1 and 0.21 points, respectively.
On the study visit, data from patient electronic medical records containing demographic, medical, treatment, and diagnostic documentation, as well as laboratory assessments, were collected for 12 months, as well as directly from the patients during the study visit. Additionally, PROs were detailed by patients in paper questionnaires.
In the study, 159 adults (age ≥18 years) with SA defined according to the GEMA 5.0 guideline were included consecutively. To classify patients into each cohort, the ACQ-5 questionnaire was used, and patients were classified into controlled SA: ACQ-5 score <1 (with maximum 1 exacerbation/year) and uncontrolled SA: ACQ-5 score ≥1 or with two or more exacerbations/year with chronic airflow limitation despite receiving a high-dose combination of ICS/LABA or OCS for at least six months/year. Patients with mental illness or cognitive impairment or diagnosed with chronic obstructive pulmonary disease, cystic fibrosis, lung cancer, or pulmonary fibrosis, or patients with any oncological disease receiving treatment or at an advanced stage, were excluded from the study. Patients included in the study fulfilled all the inclusion criteria and signed the informed consent provided by their physicians, who, at a single study visit, collected all the variables defined in the protocol.
Quantitative data were described with valid N, mean, and standard deviation (SD). Categorical variables were described by frequencies and related percentages per class level. Treatments for asthma were codified using Anatomical Therapeutic Chemical (ATC) codes. Two general linear models (GLM) for the continuous EQ-5D-5L utility and AQL-5D utility were estimated using continuous and/or categorical predictors, with a p-value < 0.1 at the univariate level. All analyses were performed using SAS Enterprise Guide version 7.15. Also, all analyses were stratified by controlled/uncontrolled SA.
Results
Sociodemographic and clinical characteristics
The mean (SD) age of the patients with controlled and uncontrolled SA was 54.5 (13.7) years and 53.6 (14.5), respectively. More than two-thirds of the patients (n = 108, 67.9%) were female (72.0% uncontrolled and 63.6% controlled). The mean (SD) of body mass index (BMI) was 29.3 (5.5) kg/m2 in patients with uncontrolled SA and 28.4 (5.2) kg/m2 in controlled SA. Most patients had done primary (n = 46, 31.3%) or secondary (n = 45, 30.6%) studies, and 39.3% (n = 57) of patients were employed. Regarding smoking status, 3.8% (n = 6) of patients reported being smokers and only 2.5% (n = 4) reported being passive smokers. Among smokers and ex-smokers, the mean (SD) number of packs per year was 17.9 (13.8). Comorbidities were present in the majority (n = 143, 89.9%) of patients (92.7% of uncontrolled SA and 87.0% of controlled SA). The pathologies with the highest prevalence (>20%) were nasal polyposis (n = 43, 27%), hypertension (n = 38, 23.9%), gastroesophageal reflux (n = 35, 22%), obesity (n = 34, 21.4%), and allergic rhinitis (n = 33, 20.8%).
The mean (SD) number of years since the diagnosis of SA in patients with uncontrolled and controlled SA was 6.7 (7.3) and 4.7 (3.5), respectively. When reviewing the exhaled nitric oxide fraction level (FeNO), the mean (SD) in patients with uncontrolled SA was 46.4 (32.5) ppb, and in controlled SA was 36.7 (35.3) ppb. The mean serum IgE (SD) level in patients with uncontrolled SA was 382.6 (414.4) and in controlled SA was 355.4 (621.2). The percentage and the total of eosinophils in patients with controlled SA were 3% and 135.4 cel/µƖ, respectively. Similarly, in patients with uncontrolled SA, percentage and the total of eosinophils were 3.8% and 254.2 cel/µƖ, respectively ().
Table 1. Sociodemographic and clinical characteristics of patients with controlled and uncontrolled SA.
Utility measure
The mean (SD) utility calculated in patients with SA from the EQ-5D-5L questionnaire (generic questionnaire) was 0.88 (0.14) in patients with controlled SA and 0.70 (0.25) in patients with uncontrolled SA. The mean (SD) utility calculated with the AQL-5D (disease-specific questionnaire) was 0.93 (0.09) in the patients with controlled SA and 0.85 (0.09) in the patients with uncontrolled SA (). The Spearman rank correlation coefficient showed a moderate linear relationship between the AQL-5D and EQ-5D-5L, rs = 0.502 (p < 0.0001) ().
Figure 1. The mean (SD) utility (EQ-5D-5L and AQL-5D) in patients with controlled and uncontrolled SA. AQL-5D: Asthma Quality of Life Utility Index-5 Dimensions; EQ-5D: EuroQoL 5 dimensions; SA: severe asthma; SD: standard deviation.
Figure 2. The Spearman rank correlation coefficient between the AQL-5D and EQ-5D-5L.
Univariate and multivariate linear regression analyses
Age, female gender, occupational status, education, BMI, study cohort, years since asthma diagnosis, number of exacerbations (mild, moderate, and severe), and comorbidities were statistically significant in the EQ-5D-5L univariate analysis. The multivariate analysis showed that having controlled SA was the only statistically significant variable related to the EQ-5D-5L utility, with less utility in patients with uncontrolled SA (B = −0.2, p = 0.0082) (see Additional File 1).
In the AQL-5D univariate analysis, family history and study cohort were statistically significant. The multivariate analysis showed that having controlled SA was the only statistically significant variable related to the AQL-5D utility, with less utility in patients with uncontrolled SA (B = −0.1, p = 0.0001) (see Additional File 2).
HRQoL
Impairment in all dimensions of the EQ-5D-5L among patients with controlled and uncontrolled SA is presented in . The percentage of impairment in the pain/discomfort dimension was 72% in uncontrolled SA vs. 44.2% in controlled SA. The percentage of impairment anxiety/depression category was 65.9% in uncontrolled SA vs. 35.1% in controlled SA. The dimension that was affected least by SA was the self-care dimension, both in patients with uncontrolled SA (19.5%) and patients with controlled SA (5.2%).
Figure 3. Percentage of patients with controlled and uncontrolled SA who reported affected dimensions of the EQ-5D-5L descriptive system.
The overall mean (SD) of the AQLQ score in patients with controlled and uncontrolled SA was 6.0 (1.1) points and 4.7 (1.2) points, respectively. The mean (SD) in patients with controlled vs. uncontrolled SA in symptoms was 6.1 (1.1) vs. 4.7 (1.3), activity limitations 5.9 (1.1) vs. 4.7 (1.3), emotional functions 6.1 (1.3) vs. 4.9 (1.5), and environmental stimuli 5.6 (1.5) vs. 4.8 (1.6), respectively ().
Figure 4. Mean AQLQ-5D scores (total and in all domains) of patients with controlled and uncontrolled SA.
Healthcare resource utilization
The percentage of patients with exacerbations was 50.6 and 14.9% in the patients with uncontrolled and controlled SA, respectively. Exacerbations were classified according to their severity (mild, moderate, and severe). The percentage of patients with uncontrolled SA who presented with mild exacerbations was 17.3% (9.5% controlled SA), with moderate exacerbations was 28.4% (4.1% controlled SA), and with severe exacerbations was 16.0% (2.7% controlled SA). The overall (mild, moderate, and severe) mean exacerbation per patient was 2.3 in patients with uncontrolled SA vs. 1.3 in patients with controlled SA.
presents the use of healthcare resources in the previous 12 months. More than 75% (n = 114, 75.5%) of patients had visits related to SA. Only few patients (n = 28, 18.5%) with SA reported visits to Primary Care (8 [10.8%] uncontrolled SA vs. 20 [26%] controlled SA). The mean (SD) number of visits to Primary Care was 4.1 (2.8) in patients with uncontrolled SA and 2.5 (3.0) in patients with controlled SA. Most of the patients (n = 113, 74.8%) with SA reported visits to the pneumologist (71.4% [n = 55] of uncontrolled SA patients vs. 78.4% [n = 58] of controlled SA patients), and the mean (SD) number of visits was 3.7 (3.5) in patients with uncontrolled SA and 2.8 (2.2) in controlled SA. Of the visits made to pneumologists by the uncontrolled SA, 10.2% (n = 21) were for worsening asthma and 22.4% (n = 46) were consultations related to medication to treat asthma, as adverse effects.
Table 2. Healthcare resource use of patients with controlled and uncontrolled SA in the previous 12 months.
Regarding emergency visits and hospitalizations, only 11.2% (n = 17) of the patients attended the emergency room, and 3.9% (n = 6) were hospitalized in the previous 12 months. Emergency visits and hospitalizations were reported in 19.2% (n = 15) and 7.7% (n = 6) of the patients with uncontrolled SA and in 2.7% (n = 2) and 0% (no hospitalizations) of the patients with controlled SA. There were no admissions to the intensive care unit.
Discussion
This cohort study assessed two utility measures, EQ-5D-5L (generic) and AQL-5D (asthma-specific), among 159 patients with controlled and uncontrolled SA. Asthma, as a respiratory disease, is characterized by inflammation of the airways so that patients with symptoms of the disease also have an associated symptom profile (Citation15,Citation16). Asthma causes symptoms, such as wheezing, shortness of breath, chest tightness, and cough that vary over time in their occurrence, frequency, and intensity. These symptoms are associated with variable expiratory airflow, i.e. difficulty breathing air out of the lungs due to bronchoconstriction (airway narrowing), airway wall thickening, and increased mucus. The symptomatology of these patients substantially reduces their HRQoL (Citation17,Citation18). This impact is more significant in patients with SA than in patients with mild asthma. Thus, measuring the HRQoL of patients with asthma gives us an idea of their overall health impairment.
This study measured the HRQoL of SA patients using EQ-5D-5L and AQL-5D quality of life questionnaires, from which the corresponding utility values were derived. To our knowledge, this the first real-world study that reported data on utility measures in Spanish patients with SA. The AQL-5D is a utility index scale generated from the AQLQ (Citation19). The EQ-5D-5L is a descriptive index with five dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression). Each dimension is represented by five different levels (from experiencing no problems to extreme problems) (Citation20,Citation21). These two questionnaires (EQ-5D-5L and AQL-5D) have been widely used to measure HRQoL in patients with asthma. Combining the dimension-specific levels across dimensions yields distinct health states, which form the basis for a preference-based valuation (utility), which in the case of AQLQ is named AQL-5D. In the study, the correlation between AQL-5D and EQ-5D-5L was moderate/fair (rs = 0.502; p < 0.0001) (Citation22), but it would not be expected to be higher (>0.7) because the EQ-5D-5L measured generic utility and the AQL-5D measured a specific utility.
In EQ-5D-5L and AQL-5D, patients with uncontrolled SA had lower scores, meaning lower utility measurements and therefore worse HRQoL across all dimensions. This has been reported previously in other studies analyzing HRQoL in patients with asthma, using these measures (Citation23–26). Therefore, achieving control in patients with SA could improve the HRQoL (Citation27); this would be key in the daily lives, including productivity, of adults (Citation28). To note, the difference in EQ-5D-5L was >0.18 points between patients with controlled and uncontrolled SA, which is a threshold that has been described as clinically relevant in the literature (Citation29).
Although both utility measures were higher in controlled than in patients with uncontrolled SA, differences in scores between both the cohorts (patients with controlled and uncontrolled SA) seem to be greater in the EQ-5D-5L than in the AQL-5D. Also, SDs of EQ-5D-5L scores were higher in both cohorts of patients than those of the AQL-5D, indicating greater accuracy of the AQL-5D, as suggested in the literature (Citation30). The specific utility measure (AQL-5D) yielded higher mean values in both patient cohorts than the generic one (EQ-5D-5L). These findings are in line with the results of the study by Kontodimopoulos et al. and could be explained by the fact that AQL-5D is specific for asthma symptoms and patients with asthma may adapt to these symptoms, as described previously (Citation13,Citation31).
HRQoL and associated utility values are very relevant clinical outcomes in patients with severe asthma. The EQ-5D, although it is the most widely used tool to measure the HRQoL and associated utility, it is not disease specific. In the present study, an asthma-specific HRQoL instrument, AQLQ, and it’s associated utility measurement, AQL-5, were used to better assess patients with severe asthma. These patients with severe asthma have special characteristics related to their disease control that may make it necessary to use very specific HRQoL tools. The mean age of patients with controlled SA was slightly higher than the mean age of patients with uncontrolled SA. Most of the results agreed with the general characteristics of patients with SA, in both controlled and patients with uncontrolled SA. The distribution of the sample was primarily female, which coincides with the distribution of adult patients observed in other studies (Citation5,Citation32). A high prevalence rate of comorbidities (among both patients with severe controlled and uncontrolled SA) was reported in our study population which is similar to those obtained for asthma populations (Citation5,Citation33). The results reported by other studies show an association between comorbidities and poor asthma control. Pérez De Llano et al. reported that the coexistence of several comorbidities in the same patient (the presence of at least one factor potentially aggravating asthma) is more frequent in cases of poor asthma control (Citation34).
The importance of comorbidities in the evolution and control of asthma is being increasingly discussed. Likewise, factors related to comorbidities that can or should be considered in the routine evaluation of people with asthma are highlighted. Our results suggest that not only patients with SA may have a higher prevalence of comorbidities, but also patients with severe uncontrolled SA may have an even higher prevalence of comorbidities. Thus, it is important to consider prioritizing the treatment of these comorbidities within the asthma management. The prevalence of comorbidities, such as osteoporosis in our study is possibly due to its association with corticosteroid in asthma treatment. Patients who are treated with high doses of corticosteroids (in asthma or other conditions) are at risk of osteoporosis (Citation35). Therefore, treating physicians should employ strategies to prevent and manage osteoporosis (Citation36). Another noteworthy finding is the prevalence of dermatitis since it was lower than the reported prevalence (Citation37), hence these results have relevance.
Similarly, patients with uncontrolled SA had a longer evolution since their diagnosis compared to controlled SA. Also, patients with uncontrolled SA presented with a greater number of exacerbations in the previous 12 months. In general, patients with uncontrolled SA have a higher risk of presenting with exacerbations of greater number and severity compared to patients with controlled SA (Citation38). Patients with uncontrolled SA presented with higher eosinophil levels and higher FeNO levels (Citation38). The biomarkers IgE, eosinophils, and FeNO reflect the characteristics of the underlying inflammatory profile and in particular, the presence of T2 inflammation (Citation39). T2-high asthma is associated with greater healthcare utilization, including more OC use and emergency room visits, as well as worse asthma control (Citation40).
Additionally, we observed a greater use of resources in patients with uncontrolled SA. This follows the trend of multiple studies suggesting greater use of medical and healthcare resources by patients with uncontrolled SA was reported (Citation41–43). The use of healthcare resources has an impact on the investment by the National Healthcare System for the treatment of these patients (Citation44–47). Because of this, it is important to monitor patients with asthma at a population level.
This study is consistent with previously published literature which emphasizes the relation of disease severity with higher exacerbation frequency, hospitalization re-admission, costs, and the risk of subsequent exacerbations (Citation48). In addition, severe exacerbations of asthma were related to the progression of irreversible airflow limitation over time (Citation49). These patients require high-intensity post-exacerbation management. Timely management should be a priority for these patients, to prevent long-term consequences and structural changes in the airways.
HRQoL is one of the most relevant clinical outcomes in patients with severe asthma and the EQ-5D tool, although not disease-specific, is the most widely tool used to measure the HRQoL. Therefore, the development of new tools to measure the QoL in this population should be prioritized and/or developed in real word studies.
There are strengths and limitations to this study. Participants were recruited from different clinical facilities, which enhanced the generalizability and representativeness of the collected data for the asthma population. This study has the advantage of being able to observe clinically patients with controlled SA vs. uncontrolled SA, a subject that cannot be observed in many studies due to difficulties in recruitment. Lastly, although the evidence on COVID-19 and asthma is limited, the outcomes of this study could have been affected by the pandemic’s evolution (Citation50). This could happen in a variety of ways, e.g. the patterns of seeking healthcare attention by the population with asthma may have changed as a result of the centralization of services to respond to COVID-19 or due to changes in perception. However, those changes would similarly affect the SA populations (controlled and uncontrolled) included in this study. Finally, although the association of sociodemographic and clinical variables with utility values was studied, this analysis was not carried out for HRQoL dimensions scores, and this could be an additional limitation of the study.
Conclusion
Patients with uncontrolled SA had a lower HRQoL than patients with controlled SA. Uncontrolled SA patients presented greater healthcare utilization, more emergency room visits, resulting in a higher burden on the healthcare system. Thus, it is recommended to implement measures that improve HRQoL among patients with SA. However, it is also important to attain guideline-defined disease control at the asthmatic population level, because this will allow better performance of healthcare resource management costs. Finally, because comorbidities lead to higher healthcare costs and a lower perception of health status, treatment of comorbidities should be emphasized in patients with SA, especially in patients with uncontrolled SA.
Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Hospital Universitario Dr. Peset, Valencia, Spain.
Consent to participate
Informed consent was obtained from all individual participants included in the study.
Author contributions
Sponsorship for this study and article processing charges were funded by AstraZeneca Farmacéutica Spain. All authors had full access to all of the data in this study and take complete responsibility for the integrity of the data and accuracy of the data analysis.
All authors have made substantial contributions to ALL of the following:
Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work;
Drafting the work or revising it critically for important intellectual content;
Final approval of the version to be published; and
Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Supplemental Material
Download MS Word (70.3 KB)Acknowledgments
The authors would like to thank all the researchers for their participation in the study.
Medical writing and other assistance: the realization of this study has been possible thanks to the funding of AstraZeneca and the logistical and technical support (including medical writing) of IQVIA.
Declaration of interest
Eva Martínez Moragón reports grants, personal fees and non-financial support from AstraZeneca, personal fees and non-financial support from GSK, personal fees and non-financial support from Novartis, personal fees and non-financial support from Chiesi, personal fees from SANOFI, MSD, FAES, Teva and GEBRO. Dr. Luis M. Entrenas Costa reports grants, personal fees and non-financial support from AMGEN, Astra-Zeneca, Bial, Böehringer-Ingelheim, Chiesi, Faes, Ferrer, Gebro, GSK, Menarini, Novartis, Pfizer, Rovi, Sanofi y Teva Joaquín Sánchez-Covisa Hernández and Gema Monteagudo Ruiz are AstraZeneca employees. Anna de Prado Moncusí reports no conflict of interest.
Data availability statement
The datasets generated and/or analyzed during the current study are not publicly available due to all information related to the study is considered confidential until publication but are available from the corresponding author on reasonable request.
Additional information
Funding
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