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Title: Consistent trajectories of rhinitis control and treatment in 16,177 weeks: The MASK-air® longitudinal study
Authors: Sousa-Pinto, Bernardo
Schünemann, Holger J.
Sá-Sousa, Ana
Vieira, Rafael José
Amaral, Rita
Anto, Josep M.
Klimek, Ludger
Czarlewski, Wienczyslawa
Mullol, Joaquim
Pfaar, Oliver
Bedbrook, Anna
Brussino, Luisa
Kvedariene, Violeta
Larenas-Linnemann, Désirée E.
Okamoto, Yoshitaka
Ventura, Maria Teresa
Agache, Ioana
Ansotegui, Ignacio J.
Bergmann, Karl C.
Bosnic-Anticevich, Sinthia
Canonica, G. Walter
Cardona, Victoria
Carreiro-Martins, Pedro
Casale, Thomas
Cecchi, Lorenzo
Chivato, Tomas
Chu, Derek K.
Cingi, Cemal
Costa, Elísio M.
Cruz, Alvaro A.
Del Giacco, Stefano
Devillier, Philippe
Eklund, Patrik
Fokkens, Wytske J.
Gemicioglu, Bilun
Haahtela, Tari
Ivancevich, Juan Carlos
Ispayeva, Zhanat
Jutel, Marek
Kuna, Piotr
Kaidashev, Igor
Khaitov, Musa
Kraxner, Helga
Laune, Daniel
Lipworth, Brian
Louis, Renaud
Makris, Michael
Monti, Riccardo
Morais-Almeida, Mario
Mösges, Ralph
Niedoszytko, Marek
Papadopoulos, Nikolaos G.
Patella, Vincenzo
Pham-Thi, Nhân
Regateiro, Frederico S. 
Reitsma, Sietze
Rouadi, Philip W.
Samolinski, Boleslaw
Sheikh, Aziz
Sova, Milan
Todo-Bom, Ana 
Taborda-Barata, Luis
Toppila-Salmi, Sanna
Sastre, Joaquin
Tsiligianni, Ioanna
Valiulis, Arunas
Vandenplas, Olivier
Wallace, Dana
Waserman, Susan
Yorgancioglu, Arzu
Zidarn, Mihaela
Zuberbier, Torsten
Fonseca, Joao A.
Bousquet, Jean 
Keywords: mobile health; patient-reported outcomes; real-world data; rhinitis
Issue Date: Apr-2023
Publisher: Wiley-Blackwell
Project: EU grants (POLLAR, EIT Health; Structural and Development Funds, Twinning, EIP on AHA and H2020) and educational grants from Mylan-Viatris, ALK, GSK, Novartis and Uriach. 
Serial title, monograph or event: Allergy: European Journal of Allergy and Clinical Immunology
Volume: 78
Issue: 4
Abstract: Introduction: Data from mHealth apps can provide valuable information on rhinitis control and treatment patterns. However, in MASK-air ®, these data have only been analyzed cross-sectionally, without considering the changes of symptoms over time. We analyzed data from MASK-air ® longitudinally, clustering weeks according to reported rhinitis symptoms. Methods: We analyzed MASK-air ® data, assessing the weeks for which patients had answered a rhinitis daily questionnaire on all 7 days. We firstly used k-means clustering algorithms for longitudinal data to define clusters of weeks according to the trajectories of reported daily rhinitis symptoms. Clustering was applied separately for weeks when medication was reported or not. We compared obtained clusters on symptoms and rhinitis medication patterns. We then used the latent class mixture model to assess the robustness of results. Results: We analyzed 113,239 days (16,177 complete weeks) from 2590 patients (mean age ± SD = 39.1 ± 13.7 years). The first clustering algorithm identified ten clusters among weeks with medication use: seven with low variability in rhinitis control during the week and three with highly-variable control. Clusters with poorly-controlled rhinitis displayed a higher frequency of rhinitis co-medication, a more frequent change of medication schemes and more pronounced seasonal patterns. Six clusters were identified in weeks when no rhinitis medication was used, displaying similar control patterns. The second clustering method provided similar results. Moreover, patients displayed consistent levels of rhinitis control, reporting several weeks with similar levels of control. Conclusions: We identified 16 patterns of weekly rhinitis control. Co-medication and medication change schemes were common in uncontrolled weeks, reinforcing the hypothesis that patients treat themselves according to their symptoms.
ISSN: 0105-4538
DOI: 10.1111/all.15574
Rights: openAccess
Appears in Collections:I&D ICBR - Artigos em Revistas Internacionais
FMUC Medicina - Artigos em Revistas Internacionais

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