Browsing by Author "Bousquet, Jean"
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- Adherence to treatment in allergic rhinitis during the pollen season in Europe: A MASK‐air StudyPublication . Bousquet, Jean; Amaral, RitaAdherence to rhinitis treatment has been insufficiently assessed. We aimed to use data from the MASK-airmHealth app to assess adherence to oral antihistamines (OAH), intra-nasal corticosteroids (INCS) or azelastine-fluticasone inpatients with allergic rhinitis. We included regular European MASK-air users with self-reported allergic rhinitis and reporting at least 1 day of OAH,INCS or azelastine-fluticasone. We assessed weeks during which patients answered the MASK-air questionnaire on all days. Werestricted our analyses to data provided between January and June, to encompass the pollen seasons across the different assessedcountries. We analysed symptoms using visual analogue scales (VASs) and the combined symptom-medication score (CSMS),performing stratified analyses by weekly adherence levels. Medication adherence was computed as the proportion of days inwhich patients reported rhinitis medication use. Sensitivity analyses were performed considering all weeks with at most 1 day ofmissing data and all months with at most 4 days of missing data. We assessed 8212 complete weeks (1361 users). Adherence (use of medication > 80% days) to specific drug classesranged from 31.7% weeks for azelastine-fluticasone to 38.5% weeks for OAH. Similar adherence to rhinitis medication was foundin users with or without self-reported asthma, except for INCS (better adherence in asthma patients). VAS and CSMS levelsincreased from no adherence to full adherence, except for INCS. A higher proportion of days with uncontrolled symptoms was observed in weeks with higher adherence. In full adherence weeks, 41.2% days reported rhinitis co-medication. The sensitivityanalyses displayed similar results. A high adherence was found in patients reporting regular use of MASK-air. Different adherence patterns werefound for INCS compared to OAH or azelastine-fluticasone that are likely to impact guidelines.
- Adult asthma scores—development and validation of multivariable scores to identify asthma in surveysPublication . Sá-Sousa, Ana; Pereira, Ana Margarida; Almeida, Rute; Araújo, Luís; Couto, Mariana; Jacinto, Tiago; Freitas, Alberto; Bousquet, Jean; Fonseca, João A.One of the questions in epidemiology is the identification of adult asthma in studies. To develop and validate multivariable scores for adult asthma identification in epidemiological studies and to explore cutoffs to rule in/rule out asthma, compared with asthma diagnosed by a physician after clinical examination and diagnostic tests, blinded to the self-administered questions. We analyzed data (n = 711 adults) from a nationwide population-based study. The predictors were self-administered questions identified in a literature review (the Adult Asthma Epidemiological Score [A2 score]) and from the Global Allergy and Asthma Network of Excellence (GA2LEN) questionnaire (the GA2LEN Asthma Epidemiological Score [GA2LEN score]). Scores were developed using exploratory factor analysis. Internal consistency, discriminative power, and diagnostic accuracy were assessed. The A2 score comprises 8 questions (including “Did a physician confirm you had asthma?”) and the GA2LEN score comprises 6 questions (including “Have you ever had asthma?”). Both had high Cronbach α (0.89 and 0.85, respectively, for the A2 score and the GA2LEN score) and good area under the receiver-operating characteristic curve (90.4% and 89.0%). The scoring is the sum of positive answers. Asthma is present (rule in) for scores of 4 or more (specificity, 99.2%; PPV, 93.3% and 91.7%; accuracy, 89.4% and 87.4%, respectively, for the A2 score and the GA2LEN score). Asthma is excluded (rule out) for A2 scores of 0 to 1 and a GA2LEN score of 0 (sensitivity, 93.1%; NPV, 98.2% and 98.0%; accuracy 89.4% and 82.8%, respectively, for the A2 score and the GA2LEN score). These practical scores can be used to rule in/rule out asthma in epidemiological studies and clinical screening/triage settings. They may help physicians in primary care or other specialties to screen patients with asthma using a simple score with a high level of discrimination and to identify the best candidates to be referred for a diagnostic workup. Moreover, their use may contribute to reducing the inconsistencies of operational definitions of asthma across studies and surveys.
- Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence–Assisted ARIA Care Pathways (ARIA 2024)Publication . Bousquet, Jean; Amaral, Rita; Amaral, RitaThe traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients’ resources and abilities to be experts in their own lives based on their lived experiences. Improving healthcare safety, quality, and coordination, as well as quality of life, is an important aim in the care of patients with chronic conditions. Person-centered care needs to ensure that people’s values and preferences guide clinical decisions. This paper reviews current knowledge to develop digital care pathways for rhinitis and asthma multimorbidity and digitally enabled, person-centered care.1 It combines all relevant research evidence, including the so-called real-world evidence, with the ultimate goal to develop digitally enabled, patient-centered care. The paper includes Allergic Rhinitis and its Impact on Asthma (ARIA), a 2-decade journey, Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, mHealth impact on airway diseases, .From guidelines to digital care pathways, Embedding Planetary Health, Novel classification of rhinitis and asthma, Embedding real-life data with population-based studies, The ARIA-EAACI (European Academy of Allergy and Clinical Immunology) strategy for the management of airway diseases using digital biomarkers, Artificial intelligence, The development of digitally enabled, ARIA person-centered care, and The political agenda. The ultimate goal is to propose ARIA 2024 guidelines centered around the patient to make them more applicable and sustainable.
- Control of allergic rhinitis and asthma test: a systematic review of measurement properties and COSMIN analysisPublication . Vieira, Rafael José; Sousa-Pinto, Bernardo; Cardoso-Fernandes, António; Jácome, Cristina; Portela, Diana; Amaral, Rita; Sá-Sousa, Ana; Pereira, Ana Margarida; Bousquet, Jean; Fonseca, João AlmeidaThe Control of Allergic Rhinitis and Asthma Test (CARAT) is a patient-reported outcome measurement (PROM) assessing the control of asthma and allergic rhinitis (AR) at a 4 week interval. This systematic review aimed to evaluate the measurement properties of CARAT. Following PRISMA and COSMIN guidelines, we searched five bibliographic databases and retrieved studies concerning the development, assessment of properties, validation, and/or cultural adaption of CARAT. The studies' methodological quality, the quality of measurement properties, and the overall quality of evidence were assessed. We performed meta-analysis of CARAT measurement properties. We included 16 studies. Control of Allergic Rhinitis and Asthma Test displayed sufficient content validity and very good consistency (meta-analytical Cronbach alpha = 0.83; 95% CI = 0.80–0.86;I2 = 62.6%). Control of allergic rhinitis and Asthma Test meta-analytical intraclass correlation coefficient was 0.91 (95% CI = 0.64–0.98;I2 = 93.7%). It presented good construct validity, especially for correlations with Patient-reported outcome measures assessing asthma (absolute Spearman correlation coefficients range = 0.67–0.73; moderate quality of evidence), and good responsiveness. Its minimal important difference is 3.5. Overall, CARAT has good internal consistency, reliability, construct validity and responsiveness, despite the heterogeneous quality of evidence. Control of Allergic Rhinitis and Asthma Test can be used to assess the control of asthma and AR. As first of its kind, this meta-analysis of CARAT measurement properties sets a stronger level of evidence for asthma and/or AR control questionnaires.
- Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypesPublication . Amaral, Rita; Bousquet, Jean; Pereira, Ana M.; Araújo, Luís M.; Sá‐Sousa, Ana; Jacinto, Tiago; Almeida, Rute; Delgado, Luís; Fonseca, João A.Background Refined phenotyping of allergic diseases may unravel novel phenotypes. Conjunctivitis as an independent disorder has never been approached. Aim To identify distinct classes of allergic respiratory diseases using latent class analysis (LCA) and distinguish each class using classification and regression tree (CART) analysis. Methods Seven hundred and twenty‐eight adults from the Portuguese general population study ICAR had a structured medical interview combined with blood collection, skin prick tests, spirometry with bronchodilation, and exhaled nitric oxide. LCA was applied to 19 variables. The CART algorithm selected the most likely variables distinguishing LCA‐classes. Results A six‐class model was obtained. Class 1 (25%): nonallergic participants without bronchial or ocular symptoms. Classes 2 (22%) and 3 (11%): nasal and ocular (low levels) symptoms without nasal impairment, monosensitized (Class 2) or polysensitized (Class 3). Class 4 (13%): polysensitized participants with high levels of nasal and ocular symptoms, and nasal impairment. Classes 5 (16%) and 6 (14%): high level of nasal, bronchial and ocular symptoms with nasal impairment (non‐allergic or polysensitized, respectively). Participants in classes 5 and 6 had more bronchial exacerbations and unscheduled medical visits (P < 0.001). Ocular symptoms were significantly higher in classes with nasal impairment, compared to those without impairment (P < 0.001) or no nasal symptom (P < 0.001). CART highlighted ocular symptoms as the most relevant variable in distinguishing LCA‐classes. Conclusion Novel severe phenotypes of participants with co‐occurrence of ocular, nasal and bronchial symptoms, and exacerbation‐prone were identified. The tree algorithm showed the importance of the ocular symptoms in the expression of allergic diseases phenotypes.