Author(s):
Sousa-Pinto, Bernardo ; Azevedo, Luís Filipe ; Sá-Sousa, Ana ; Vieira, Rafael José ; Amaral, Rita ; Klimek, Ludger ; Czarlewski, Wienczyslawa ; Anto, Josep M. ; Bedbrook, Anna ; Kvedariene, Violeta ; Ventura, Maria Teresa ; Ansotegui, Ignacio J. ; Bergmann, Karl Christian ; Brussino, Luisa ; CANONICA, GIORGIO WALTER ; Cardona, Victoria ; Carreiro Martins, Pedro ; Casale, Thomas ; Cecchi, Lorenzo ; Chivato, Tomás ; Chu, Derek K. ; Cingi, Cemal ; Costa, Elisio M. ; Cruz, Alvaro A. ; De Feo, Giulia ; Devillier, Philippe ; Fokkens, Wytske J. ; Gaga, Mina ; Gemicioğlu, Bilun ; Haahtela, Tari ; Ivancevich, Juan Carlos ; Ispayeva, Zhanat ; Jutel, Marek ; Kuna, Piotr ; Kaidashev, Igor ; Kraxner, Helga ; Larenas-Linnemann, Désirée E. ; Laune, Daniel ; Lipworth, Brian ; Louis, Renaud ; Makris, Michaël ; Monti, Riccardo ; Morais-Almeida, Mario ; Mösges, Ralph ; Mullol, Joaquim ; Odemyr, Mikaëla ; Okamoto, Yoshitaka ; Papadopoulos, Nikolaos G. ; Patella, Vincenzo ; Pham-Thi, Nhân ; Regateiro, Frederico S. ; Reitsma, Sietze ; Rouadi, Philip W. ; Samolinski, Boleslaw ; Sova, Milan ; Todo-Bom, Ana ; Taborda-Barata, Luis ; Tomazic, Peter Valentin ; Toppila-Salmi, Sanna ; Sastre, Joaquin ; Tsiligianni, Ioanna ; Valiulis, Arunas ; Wallace, Dana ; Waserman, Susan ; Yorgancioglu, Arzu ; Zidarn, Mihaela ; Zuberbier, Torsten ; Fonseca, João Almeida ; Bousquet, Jean ; Pfaar, Oliver
Date: 2022
Persistent ID: http://hdl.handle.net/10362/136401
Origin: Repositório Institucional da UNL
Subject(s): allergic rhinitis; immunotherapy; mobile health; patient-reported outcomes; real-life data analysis; Immunology and Allergy; Immunology; Pulmonary and Respiratory Medicine
Description
Funding Information: MASK-air has been supported by Charit? Universit?tsmedizin Berlin, EU Grants (EU Structural and Development Funds, POLLAR: EIT Health POLLAR, EIT Health Twinning) and educational grants from Mylan-Viatris, ALK, GSK, Novartis and Uriach. Open access funding enabled and organized by Projekt DEAL. Publisher Copyright: © 2022 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology.
Background: Evidence regarding the effectiveness of allergen immunotherapy (AIT) on allergic rhinitis has been provided mostly by randomised controlled trials, with little data from real-life studies. Objective: To compare the reported control of allergic rhinitis symptoms in three groups of users of the MASK-air® app: those receiving sublingual AIT (SLIT), those receiving subcutaneous AIT (SCIT), and those receiving no AIT. Methods: We assessed the MASK-air® data of European users with self-reported grass pollen allergy, comparing the data reported by patients receiving SLIT, SCIT and no AIT. Outcome variables included the daily impact of allergy symptoms globally and on work (measured by visual analogue scales—VASs), and a combined symptom-medication score (CSMS). We applied Bayesian mixed-effects models, with clustering by patient, country and pollen season. Results: We analysed a total of 42,756 days from 1,093 grass allergy patients, including 18,479 days of users under AIT. Compared to no AIT, SCIT was associated with similar VAS levels and CSMS. Compared to no AIT, SLIT-tablet was associated with lower values of VAS global allergy symptoms (average difference = 7.5 units out of 100; 95% credible interval [95%CrI] = −12.1;−2.8), lower VAS Work (average difference = 5.0; 95%CrI = −8.5;−1.5), and a lower CSMS (average difference = 3.7; 95%CrI = −9.3;2.2). When compared to SCIT, SLIT-tablet was associated with lower VAS global allergy symptoms (average difference = 10.2; 95%CrI = −17.2;−2.8), lower VAS Work (average difference = 7.8; 95%CrI = −15.1;0.2), and a lower CSMS (average difference = 9.3; 95%CrI = −18.5;0.2). Conclusion: In patients with grass pollen allergy, SLIT-tablet, when compared to no AIT and to SCIT, is associated with lower reported symptom severity. Future longitudinal studies following internationally-harmonised standards for performing and reporting real-world data in AIT are needed to better understand its ‘real-world’ effectiveness.
