Browsing by Author "Sousa-Pinto, Bernardo"
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- 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.
- A systematic review of asthma phenotypes derived by data-driven methodsPublication . Cunha, Francisco; Amaral, Rita; Jacinto, Tiago; Sousa-Pinto, Bernardo; Fonseca, João A.Classification of asthma phenotypes has a potentially relevant impact on the clinical management of the disease. Methods for statistical classification without a priori assumptions (data-driven approaches) may contribute to developing a better comprehension of trait heterogeneity in disease phenotyping. This study aimed to summarize and characterize asthma phenotypes derived by data-driven methods. We performed a systematic review using three scientific databases, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. We included studies reporting adult asthma phenotypes derived by data-driven methods using easily accessible variables in clinical practice. Two independent reviewers assessed studies. The methodological quality of included primary studies was assessed using the ROBINS-I tool. We retrieved 7446 results and included 68 studies of which 65% (n = 44) used data from specialized centers and 53% (n = 36) evaluated the consistency of phenotypes. The most frequent data-driven method was hierarchical cluster analysis (n = 19). Three major asthma-related domains of easily measurable clinical variables used for phenotyping were identified: personal (n = 49), functional (n = 48) and clinical (n = 47). The identified asthma phenotypes varied according to the sample's characteristics, variables included in the model, and data availability. Overall, the most frequent phenotypes were related to atopy, gender, and severe disease. This review shows a large variability of asthma phenotypes derived from data-driven methods. Further research should include more population-based samples and assess longitudinal consistency of data-driven phenotypes.
- Where do we stand with asthma phenotypes derived from data-driven methods? A systematic reviewPublication . Amaral, Rita; Jacinto, Tiago; Sousa-Pinto, Bernardo; Fonseca, JoãoAsthma phenotypes can be refined using methods without a priori assumptions (data-driven). We aimed to describe asthma phenotypes derived with data-driven methods, using variables easily measurable in a clinical setting, and to summarize their consistency.