==== Front Clin Transl Allergy Clin Transl Allergy Clinical and Translational Allergy 2045-7022 BioMed Central London 342 10.1186/s13601-020-00342-x Review Treatment of allergic rhinitis during and outside the pollen season using mobile technology. A MASK study Bédard A. 123 Basagaña X. 123 Anto J. M. 1234 Garcia-Aymerich J. 123 Devillier P. 5 Arnavielhe S. 6 Bedbrook A. 7 Onorato G. L. 7 Czarlewski W. 8 Murray R. 982 Almeida R. 10 Fonseca J. A. 1083 Correia da Sousa J. 1112 Costa E. 1384 Morais-Almeida M. 14 Todo-Bom A. 15 Cecchi L. 16 De Feo G. 17 Illario M. 18 Menditto E. 19 Monti R. 20 Stellato C. 21 Ventura M. T. 22 Annesi-Maesano I. 22 Bosse I. 23 Fontaine J. F. 24 Pham-Thi N. 25 Thibaudon M. 26 Schmid-Grendelmeier P. 27 Spertini F. 28 Chavannes N. H. 29 Fokkens W. J. 30 Reitsma S. 30 Dubakiene R. 31 Emuzyte R. 32 Kvedariene V. 33 Valiulis A. 3435 Kuna P. 36 Samolinski B. 37 Klimek L. 38 Mösges R. 39 Pfaar O. 40 Shamai S. 39 Roller-Wirnsberger R. E. 41 Tomazic P. V. 42 Ryan D. 43 Sheikh A. 44 Haahtela T. 45 Toppila-Salmi S. 45 Valovirta E. 46 Cardona V. 47 Mullol J. 48 Valero A. 49 Makris M. 50 Papadopoulos N. G. 5152 Prokopakis E. P. 53 Psarros F. 54 Bachert C. 55568586 Hellings P. W. 5758 Pugin B. 58 Bindslev-Jensen C. 59 Eller E. 59 Kull I. 60 Melén E. 61 Wickman M. 62 De Vries G. 63 van Eerd M. 63 Agache I. 64 Ansotegui I. J. 65 Bosnic-Anticevich S. 6667 Cruz A. A. 6869 Casale T. 70 Ivancevich J. C. 71 Larenas-Linnemann D. E. 72 Sofiev M. 73 Wallace D. 74 Waserman S. 75 Yorgancioglu A. 76 Laune D. 6 http://orcid.org/0000-0001-9226-7762Bousquet J. jean.bousquet@orange.fr 77778798081 the MASK study group 1 grid.434607.20000 0004 1763 3517ISGlobal, Barcelona, Spain 2 grid.413448.e0000 0000 9314 1427CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain 3 grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra (UPF), Barcelona, Spain 4 grid.411142.30000 0004 1767 8811IMIM (Hospital del Mar Research Institute), Barcelona, Spain 5 grid.414106.60000 0000 8642 9959UPRES EA220, Pôle des Maladies des Voies Respiratoires, Hôpital Foch, Université Paris-Saclay, Suresnes, France 6 KYomed INNOV, Montpellier, France 7 grid.157868.50000 0000 9961 060XCHU de Montpellier, Montpellier, France 8 Medical Consulting Czarlewski, Levallois, France 9 Research fellow, OPC, and Director, Cambridge, UK 10 grid.5808.50000 0001 1503 7226Faculdade de Medicina da Universidade do Porto, Lda Porto, Portugal 11 grid.10328.380000 0001 2159 175XLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal 12 grid.10328.380000 0001 2159 175XICVS/3B’s, PT Government Associate Laboratory, Braga/Guimarães, Portugal 13 grid.5808.50000 0001 1503 7226Faculty of Pharmacy and Competence Center on Active and Healthy Ageing of University of Porto (Porto4Ageing), Porto, Portugal 14 grid.421304.0Allergy Center, CUF Descobertas Hospital, Lisbon, Portugal 15 grid.8051.c0000 0000 9511 4342Imunoalergologia, Centro Hospitalar Universitário de Coimbra and Faculty of Medicine, University of Coimbra, Coimbra, Portugal 16 SOS Allergology and Clinical Immunology, USL Toscana Centro, Prato, Italy 17 grid.11780.3f0000 0004 1937 0335Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana, University of Salerno, Salerno, Italy 18 grid.411293.c0000 0004 1754 9702Division for Health Innovation, Campania Region, Federico II University Hospital Naples (R&D and DISMET), Naples, Italy 19 grid.4691.a0000 0001 0790 385XCIRFF, Federico II University, Naples, Italy 20 grid.7605.40000 0001 2336 6580Department of Medical Sciences, Allergy and Clinical Immunology Unit, University of Torino, Mauriziano Hospital, Turin, Italy 21 grid.7644.10000 0001 0120 3326Unit of Geriatric Immunoallergology, University of Bari Medical School, Bari, Italy 22 Medical School Saint Antoine, Epidemiology of Allergic and Respiratory Diseases, Department Institute Pierre Louis of Epidemiology and Public Health, INSERM, Sorbonne Université, Paris, France 23 Allergist La Rochelle, La Rochelle, France 24 Allergist, Reims, France 25 grid.10877.390000000121581279Ecole Polytechnique Palaiseau, IRBA (Institut de Recherche bio-Médicale des Armées), Bretigny, France 26 grid.507708.dRNSA (Réseau National de Surveillance Aérobiologique), Brussieu, France 27 grid.412004.30000 0004 0478 9977Allergy Unit, Department of Dermatology, University Hospital of Zurich, Zurich, Switzerland 28 grid.8515.90000 0001 0423 4662Service Immunologie et Allergie, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland 29 grid.10419.3d0000000089452978Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands 30 grid.5650.60000000404654431Department of Otorhinolaryngology, Amsterdam University Medical Centres, AMC, Amsterdam, The Netherlands 31 grid.6441.70000 0001 2243 2806Clinic of Chest Diseases, Immunology and Allergology, Medical Faculty, Vilnius University, Vilnius, Lithuania 32 grid.6441.70000 0001 2243 2806Clinic of Children’s Diseases, Faculty of Medicine, Vilnius University, Vilnius, Lithuania 33 grid.6441.70000 0001 2243 2806Department of Pathology, Faculty of Medicine and Clinic of Chest Diseases, Immunology and Allergology, Faculty of Medicine, Institute of Biomedical Sciences, Vilnius University, Institute of Clinical Medicine, Vilnius, Lithuania 34 grid.6441.70000 0001 2243 2806Vilnius University Institute of Clinical Medicine, Clinic of Children’s Diseases, Department of Public Health, and Institute of Health Sciences, Vilnius, Lithuania 35 European Academy of Paediatrics, EAP/UEMS-SP), Brussels, Belgium 36 grid.8267.b0000 0001 2165 3025Division of Internal Medicine, Asthma and Allergy, Barlicki University Hospital, Medical University of Lodz, Lodz, Poland 37 grid.13339.3b0000000113287408Department of Prevention of Environmental Hazards and Allergology, Medical University of Warsaw, Warsaw, Poland 38 Center for Rhinology and Allergology, Wiesbaden, Germany 39 grid.6190.e0000 0000 8580 3777Medical Faculty, CRI-Clinical Research International-Ltd, Institute of Medical Statistics, and Computational Biology, University of Cologne, Hamburg, Germany 40 grid.10253.350000 0004 1936 9756Department of Otorhinolaryngology, Head and Neck Surgery, Section of Rhinology and Allergy, University Hospital Marburg, Philipps-Universität Marburg, Marburg, Germany 41 grid.11598.340000 0000 8988 2476Department of Internal Medicine, Medical University of Graz, Graz, Austria 42 grid.11598.340000 0000 8988 2476Department of ENT, Medical University of Graz, Graz, Austria 43 grid.4305.20000 0004 1936 7988Honorary Clinical Research Fellow, Allergy and Respiratory Research Group, The University of Edinburgh, Edinburgh, UK 44 grid.4305.20000 0004 1936 7988The Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK 45 grid.7737.40000 0004 0410 2071Skin and Allergy Hospital, Helsinki University Hospital, and University of Helsinki, Helsinki, Finland 46 grid.1374.10000 0001 2097 1371Department of Lung Diseases and Clinical Immunology, University of Turku, Terveystalo Allergy Clinic, Turku, Finland 47 grid.411083.f0000 0001 0675 8654Allergy Section, Department of Internal Medicine, Hospital Vall d’Hebron, ARADyAL Research Network, Barcelona, Spain 48 grid.5841.80000 0004 1937 0247Rhinology Unit, & Smell Clinic, ENT Department, Hospital Clínic, Clinical & Experimental Respiratory Immunoallergy, IDIBAPS, CIBERES, University of Barcelona, Barcelona, Spain 49 grid.5841.80000 0004 1937 0247Pneumology and Allergy Department CIBERES and Clinical, & Experimental Respiratory Immunoallergy, IDIBAPS, University of Barcelona, Barcelona, Spain 50 grid.5216.00000 0001 2155 0800Allergy Unit “D Kalogeromitros”, 2nd Dpt of Dermatology and Venereology, National & Kapodistrian University of Athens, “Attikon” University Hospital, Athens, Greece 51 grid.5379.80000000121662407Division of Infection, & Respiratory Medicine, Royal Manchester Children’s Hospital Immunity, University of Manchester, Manchester, UK 52 grid.5216.00000 0001 2155 0800Allergy Department, 2nd Pediatric Clinic, Athens General Children’s Hospital “P&A Kyriakou,” University of Athens, Athens, Greece 53 grid.8127.c0000 0004 0576 3437Department of Otorhinolaryngology, University of Crete School of Medicine, Heraklion, Greece 54 grid.414025.60000 0004 0638 8093Allergy Department, Athens Naval Hospital, Athens, Greece 55 grid.410566.00000 0004 0626 3303Upper Airways Research Laboratory, ENT Dept, Ghent University Hospital, Ghent, Belgium 56 grid.12981.330000 0001 2360 039XSun Yat-sen University, International Airway Research Center, Guangzou, China 57 Academic Medical Center, Univ of Amsterdam, Dept of Otorhinolaryngology, Univ Hospitals Leuven, Leuven, The Netherlands 58 European Forum for Research and Education in Allergy and Airway Diseases (EUFOREA), Brussels, Belgium 59 grid.7143.10000 0004 0512 5013Odense University Hospital, Department of Dermatology and Allergy Centre, Odense Research Center for Anaphylaxis (ORCA), Odense, Denmark 60 Thermofisher Scientific, Uppsala, Sweden 61 grid.4714.60000 0004 1937 0626Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Sach´s Children and Youth Hospital, Södersjukhuset, Sweden 62 grid.4714.60000 0004 1937 0626Sachs’ Children and Youth Hospital, Stockholm and Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden 63 grid.8993.b0000 0004 1936 9457Centre for Clinical Research Sörmland, Uppsala University, Eskilstuna, Sweden 64 Peercode BV, Geldermalsen, The Netherlands 65 grid.5120.60000 0001 2159 8361Transylvania University Brasov, Brasov, Romania 66 Department of Allergy and Immunology, Hospital Quirónsalud Bizkaia, Erandio, Spain 67 grid.417229.b0000 0000 8945 8472Woolcock Institute of Medical Research, University of Sydney, Woolcock Emphysema Centre, Sydney Local Health District, Glebe, NSW Australia 68 grid.8399.b0000 0004 0372 8259Nucleo de Excelencia em Asma, Federal University of Bahia, Salvador, Brazil 69 WHO GARD Planning Group, Salvador, Brazil 70 grid.170693.a0000 0001 2353 285XDivision of Allergy/Immunology, University of South Florida, Tampa, FLA USA 71 Clinica Santa Isabel, Servicio de Alergia e Immunologia, Buenos Aires, Argentina 72 Center of Excellence in Asthma and Allergy, Médica Sur Clinical Foundation and Hospital, México City, Mexico 73 grid.8657.c0000 0001 2253 8678Finnish Meteorological Institute (FMI), Helsinki, Finland 74 grid.261241.20000 0001 2168 8324Nova Southeastern University, Fort Lauderdale, FL USA 75 grid.25073.330000 0004 1936 8227Department of Medicine, Clinical Immunology and Allergy, McMaster University, Hamilton, ON Canada 76 grid.411688.20000 0004 0595 6052Department of Pulmonary Diseases, Faculty of Medicine, Celal Bayar University, Manisa, Turkey 77 grid.157868.50000 0000 9961 060XUniversity Hospital, Montpellier, France 78 grid.7429.80000000121866389INSERM U 1168, VIMA : Ageing and Chronic Diseases Epidemiological and Public Health Approaches, Villejuif, France 79 Université Versailles St-Quentin-en-Yvelines, UMR-S 1168, Montigny Le Bretonneux, France 80 Charité, Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin, Germany 81 grid.484013.aDepartment of Dermatology and Allergy, Berlin Institute of Health, Comprehensive Allergy Center, Berlin, Germany 82 Medscript, Paraparaumu, New Zealand 83 MEDIDA, Lda, Porto, Portugal 84 grid.5808.50000 0001 1503 7226UCIBIO, REQUINTE, Faculty of Pharmacy and Competence Center on Active and Healthy Ageing of University of Porto (Porto4Ageing), Porto, Portugal 85 grid.4714.60000 0004 1937 0626Division of ENT Diseases, CLINTEC, Karolinska Institutet, Stockholm, Sweden 86 grid.24381.3c0000 0000 9241 5705Department of ENT Diseases, Karolinska University Hospital, Stockholm, Sweden 9 12 2020 9 12 2020 2020 10 621 3 2020 25 8 2020 © The Author(s) 2020Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Background The analysis of mobile health (mHealth) data has generated innovative insights into improving allergic rhinitis control, but additive information is needed. A cross-sectional real-world observational study was undertaken in 17 European countries during and outside the estimated pollen season. The aim was to collect novel information including the phenotypic characteristics of the users. Methods The Allergy Diary–MASK-air–mobile phone app, freely available via Google Play and App, was used to collect the data of daily visual analogue scales (VASs) for overall allergic symptoms and medication use. Fluticasone Furoate (FF), Mometasone Furoate (MF), Azelastine Fluticasone Proprionate combination (MPAzeFlu) and eight oral H1-antihistamines were studied. Phenotypic characteristics were recorded at entry. The ARIA severity score was derived from entry data. This was an a priori planned analysis. Results 9037 users filled in 70,286 days of VAS in 2016, 2017 and 2018. The ARIA severity score was lower outside than during the pollen season. Severity was similar for all treatment groups during the pollen season, and lower in the MPAzeFlu group outside the pollen season. Days with MPAzeFlu had lower VAS levels and a higher frequency of monotherapy than the other treatments during the season. Outside the season, days with MPAzeFlu also had a higher frequency of monotherapy. The number of reported days was significantly higher with MPAzeFlu during and outside the season than with MF, FF or oral H1-antihistamines. Conclusions This study shows that the overall efficacy of treatments is similar during and outside the pollen season and indicates that medications are similarly effective during the year. Keywords Allergic rhinitisAnti-histaminesCorticosteroidsICTMobile healthMASKTreatmentissue-copyright-statement© The Author(s) 2020 ==== Body Background Observationl real-life studies using mobile technology can complement randomized control trials (RCTs) and improve the positioning of allergic rhinitis (AR) medications in care pathways. MASK-air (Mobile Airways Sentinel NetworK) is an information and communication technology (ICT) system which is centred around the patient. It uses a treatment scroll list which includes all medications customized for each country as well as a visual analogue scale (VAS) to assess rhinitis control [1–3]. Two studies in over 9000 users and 22 countries enabled differentiation between AR treatments [3, 4] and showed that the assessment of daily data was useful in the understanding of treatment patterns. Most allergic rhinitis (AR) patients use on-demand treatment when they are suboptimally controlled. As in resistant hypertension, defined by the number of medications used to control the disease [5], many patients have a worse control when increasing their medications [3, 4]. Differences in efficacy between intranasal corticosteroids (INCS) and intra-nasal MPAzeFlu were observed [3, 4]. These studies were carried out across the year and it is possible that the results differ during and outside the pollen season as the allergen exposure differs and the disease may not be the same in terms of phenotypes [6, 7] and costs [8]. Another MASK study in 12,143 users and 23 countries found that very few patients reporting data for several days were adherent [9]. These studies combined propose novel concepts for AR treatment. However, they failed to show certain key facts including the phenotypic characteristics of the patients at entry and whether the conclusions raised are applicable during and outside the pollen season. The present analysis is a follow-up of previous MASK studies attempting to answer unresolved questions to provide novel real-world data information. A new cross-sectional observational study undertaken in 9037 users and 17 European countries examined AR treatments during and outside the pollen seasons (2016, 2017 and 2018). Two-thirds of the participants were already enrolled in previous studies, but analyses differed. The aim of the study was (i) to assess the participants' characteristics to better assess their phenotypes, (ii) to study whether the same trends in treatment efficacy are found during high and low allergen loads, assessed according to a recent study [10], and (iii) to investigate whether the trends in treatment efficacy were associated with the severity of the disease at entry. The study was focussed on the most commonly used intra-nasal medications containing corticosteroids: Fluticasone Furoate (FF), Mometasone Furoate (MF) and MPAzeFlu [3, 4], reported as monotherapy or co-medication [3, 4, 11]. It also focussed on the most common oral H1-antihistamines (OAH) reported as monotherapy: Bilastine, Cetirizine (CET), Desloratadine (DL), Ebastine, Fexofenadine (FEXO), Levocetirizine (LEVOCET), Loratadine (Lora) and Rupatadine. We did not study OAH reported as co-medication, as they are usually associated with INCS. Untreated days were used as a control group. Methods Users All users of the app in Europe in 2016, 2017 and 2018 were included with no exclusion criteria and according to methods previously described [4, 11] . Setting Users from 17 countries filled in the Allergy Diary (Tables  1 and 2).Table 1 Country and number of users recording Visual Analogue Scale score using MASK-air® during the pollen season Country VAS measurements (days) 1 2 to 7 8 to 14  > 14 Total Austria 144 (57%) 74 14 22 254 Belgium 50 (57%) 26 6 6 88 Czech Republic 9 (29%) 10 2 10 31 Denmark 20 (38%) 18 5 10 53 Finland 109 (43%) 90 20 32 251 France 378 (56%) 222 28 43 671 Germany 205 (38%) 141 54 141 541 Greece 22 (17%) 33 21 53 129 Italy 408 (45%) 294 67 132 901 Lithuania 64 (23%) 82 37 98 281 Netherlands 341 (46%) 276 58 67 742 Poland 251 (45%) 189 35 84 559 Portugal 549 (49%) 439 60 82 1130 Spain 102 (32%) 98 39 78 317 Sweden 16 (40%) 13 6 5 40 Switzerland 428 (61%) 200 27 42 697 UK 101 (40%) 95 39 19 254 Total 3197 (46%) 2300 (33%) 518 (8%) 924 (13%) 6939 Table 2 Country and number of users recording Visual Analogue Scale score using MASK-air® outside the pollen season Country VAS measurements (days) 1 2 to 7 8 to 14  > 14 Total Austria 33 (54%) 15 3 10 61 Belgium 24 (46%) 17 4 7 52 Czech Republic 6 (60%) 0 0 4 10 Denmark 18 (55%) 13 0 2 33 Finland 26 (56%) 18 1 1 46 France 45 (48%) 34 4 10 93 Germany 90 (60%) 37 8 15 150 Greece 38 (31%) 35 15 35 123 Italy 139 (36%) 101 32 109 381 Lithuania 35 (20%) 51 22 67 175 Netherlands 64 (61%) 25 9 7 105 Poland 105 (58%) 53 10 14 182 Portugal 114 (50%) 76 20 19 229 Spain 95 (39%) 79 28 44 246 Sweden 26 (51%) 20 3 2 51 Switzerland 20 (71%) 29 0 0 28 UK 71 (53%) 42 9 11 133 Total 949 (45%) 624 (30%) 168 (8%) 357 (17%) 2098 Ethics and privacy The Allergy Diary is CE1 registered. By using k-anonymity, the data were all anonymized including the data related to geolocalization [12]. MASK-air® is in line with the General Data Protection Regulation (GDPR) EU Directive 95/46/EC [13]. Independent Review Board approval was not required since the study is observational and users agree to having their data analysed (terms of use). Allergy diary (MASK-air®) Geolocalized users self-assessed their daily symptom control using the touchscreen functionality on their smart phone to click on a VAS score (ranging from 0 to 100) for overall symptoms (global VAS). Some users reported VAS scores more than once a day. In previous studies, we found that the highest reported value should be used and we followed this. According to previous studies, severity was defined as “no symptoms” (VAS ranging from 0 to 20), “mild” (20 to 50) and “severe” (≥ 50) [1, 14]. Users input their daily medications using a scroll list which contains all country-specific OTC and prescribed medications available for each country. Both the active ingredient and the marketed OTC and prescribed medications are listed. The list has been populated using IMS data. Days with or without treatment were reported by users. The present study is another MASK study. Some of the raw data used in the other papers (up to December 2017) were used in this study [4]. However, new data have been included, many of the analyses are different and estimated allergen exposure was not previously analyzed. Time of the study We did not study all individual locations as only around 60% of subjects agreed to be geolocalized and we knew only the country of origin in the non-geolocalized users. We therefore estimated the pollen season for each country using Google Trends and terms previously defined [15, 16]. We found that overall, across Europe, the season covered March 15 to the end of June. We have published a series of papers on Google Trends to better understand pollen seasons and the drawbacks of the method [15, 17–23]. They can roughly appreciate the season. On the other hand, pollen counts cannot be used on a daily basis. Moreover, they are not available for all locations. Thus, they cannot be used in the current study. To assess the pollen season precisely, personal samplers should be used but it would be impossible to use them in thousands of patients and, due to privacy, they cannot be used in this study. We estimated the period outside the pollen season as August 1 to December 31. We therefore avoided the early tree pollen season (January-March) and excluded days recorded in Austria and France between August 1 and September 15 to avoid the ragweed pollen season. In a recent paper, the same approach was used to assess impact of pollution on the pollen season [24]. Selection of medications The International Nonproprietary Names (INN) classification was used for drug nomenclature [25]. Monotherapy was defined as days when only one single medication for rhinitis was reported. MPAzeFlu contains two drugs but, being a fixed combination, it was considered as monotherapy. Co-medication was defined as days with two or more medications for rhinitis. Asthma medications were not considered in co-medication. Characteristics at entry According to a previous study, we considered AR symptoms recorded upon the first use of the app (rhinorrhea, sneezing, nasal congestion, nasal itching, ocular symptoms) [26]. On the same day (i.e. at entry), we assessed the ARIA severity score calculated by using the four questions regarding impact on sleep, daily activities, work/school attendance, and bothersome symptoms. Each of these four items was ascribed a score of 1 (“Yes”) or 0 (“No”). The total ARIA score ranged from 0 (no impairment) to 4 (severe impairment). This score was found to correlate with EQ-5D and WPAI-AS using MASK [27] and was used in an epidemiological study [28]. Size of the study In this study, all registered users were included to obtain the best possible estimates for the specified time window. From previous studies, the  numbers tested largely exceed those needed to find significant differences in the full set analysis [4]. Stratification of the users The stratification was determined by season of enrolment (i.e. during or outside the pollen season). Statistical methods A non-Gaussian distribution was found for the data. Non-parametric tests and medians (and percentiles) were used. Analysis of the data All analyses were conducted separately for users who were enrolled and used the app (i) during the pollen season (discarding days reported outside the pollen season by those users) and (ii) outside the pollen season (discarding days reported during the pollen season by those users). All analyses were conducted by comparing the days when app users reported the use of INCS treatment (FF, MPAzeFlu, MF), the use of OAH in monotherapy, and the days when users did not report any treatment (days with other treatment were excluded from the analyses). According to the treatment (FF, MPAzeFlu, MF, OAH in monotherapy or no treatment) reported at entry day (thereafter called Day 1), we compared (i) characteristics reported by the user on Day 1 (i.e. AR symptoms, impact of symptoms and ARIA score), (ii) the distribution of global VAS reported by the users on Day 1, and (iii) the proportion of monotherapy versus comedication reported for the use of that treatment. The comparison analyses described in (ii) and (iii) were also conducted on all the days of App use, i.e. for all the days of App use, we compared the distribution of global VAS, as well as the proportion of monotherapy versus comedication, according to the treatment reported on that day. Finally, for each treatment, we compared the average number of days of treatment reported per user, estimated by dividing the total number of days for which the use of a medication was reported by the total number of users reporting that medication at least once. To investigate the consistency of our results during and outside the pollen season, we compared characteristics at entry between during and outside the pollen season. The ARIA score on Day 1 (ranging from 0 to 4) was considered either as a continuous or a categorical variable. Global VAS was considered either as a continuous, or a categorical variable - using three cutoffs: VAS < 20/100 (controlled days), VAS 20-49 (days with moderate control), VAS ≥ 50 (days with poor control) [4, 11]. Chi square tests were used to compare the distribution of categorical variables (i.e. symptoms and impact of symptoms on Day 1, ARIA score on Day 1, global VAS categories). Kruskal–Wallis tests were used to compare the distribution of continuous variables (i.e. ARIA score, global VAS). Results Demographic characteristics The study included 9037 users (i.e. 6939 who started to use the app during the pollen season and 2098 who started outside the season). Roughly 5% of users did not report their age or reported an age of below 10. Users ranged from zero to 91 years-old (mean, SD: 33.5 ± 15.5 years). There were 53.5% of women and 46.5% of men. A total of 211,003 days were recorded between 2016 and 2018. Duplicates or multiplicates for the same day were found in 4397 days. 49,566 days were recorded by the 6939 users during the pollen season. There were 23,377 (54.4%) days without treatment and 19,568 (45.6%) days with the targetted INCS or OAH. 20,720 days were recorded by the 2098 users outside the pollen season. There were 13,130 (69.5%) days without treatment and 5756 (30.5%) days with treatment (Fig. 1).Fig. 1 Flow chart of the study population Characteristics on Day 1 Characteristics on Day 1 are given in Tables 3 and 4 for the pollen season and in Tables 3 and 5 for outside the pollen season.Table 3 Comparison of characteristics and VAS levels at entry recorded during and outside the pollen season During pollen season (n = 6939) Outside pollen season (n = 2098) P value Symptoms Day 1 Itchy nose (%) 73 66 <0.001 Sneezing (%) 61 55 <0.001 Congestion (%) 69 65 0.001 Red eyes (%) 46 37 <0.001 Itchy eyes (%) 68 53 <0.001 Watery eyes (%) 47 38 <0.001 Impact of symptoms Day 1 Sleep (%) 38 35 0.06 Daily activities (%) 45 39 <0.001 Work/school (%) 30 26 <0.001 Bothersome (%) 76 68 <0.001 ARIA score (%) 0 14 20 1 30 32 2 25 21 <0.001 3 18 16 4 14 12 Median [p25-p75] 2 [1–3] 1 [1–3] <0.001 FF Fluticasone Furoate, FP Fluticasone Propionate, MF Mometasone Furoate, MPAzeFlu Azelastine-Fluticasone Propionate *Chi square tests were used for categorical variables (i.e. baseline symptoms and impact of symptoms, ARIA score); Kruskal–Wallis tests were used for continuous variables (i.e. ARIA score) p25: 25th percentile; p75: 75th percentile Table 4 Results for all participants recruited during the pollen season Treatment days No treatment days P value* FF MPAzeFlu MF OAH mono N users Day 1 331 (5.5%) 159 (2.7%) 351 (5.9%) 1414 (23.6%) 3736 (62.4%) Symptoms Day 1  Runny nose (%) 69 74 75 78 69 0.77  Itchy nose (%) 68 55 65 67 57 0.006  Sneezing (%) 79 73 76 87 77 0.20  Nasal congestion (%) 75 74 79 71 64 0.37  Red eyes (%) 50 44 42 52 42 0.56  Itchy eyes (%) 70 64 68 74 64 0.22  Watery eyes (%) 48 42 45 54 43 0.29 Impact of symptoms Day 1  Sleep (%) 44 44 47 41 32 0.70  Daily activities (%) 41 50 50 49 41 0.36  Work/school (%) 31 42 33 33 27 0.02  Bothersome (%) 76 77 77 78 74 0.94 ARIA score (%)  0 11 11 12 11 16  1 29 26 23 28 32  2 30 24 27 26 24 0.08  3 19 16 23 21 16  4 12 23 16 15 12  Median [p25-75] 2 [1–3] 2 [1–3] 2 [1–3] 2 [1–3] 2 [1–3] 0.36 VAS global Day 1 (%)  N 331 159 351 1414 3736  <20 17 18 16 16 30 0.53  20-49 32 28 33 26 28  ≥50 51 55 51 58 42  Median [p25-75] 50 [28–71] 52 [25–73] 50 [28–68] 55 [30–75] 40 [15–66] 0.72 VAS global – all days (%)  N days 3186 2594 4093 9780 23,377  N users 507 256 548 2196 4569  Average number of days per user± 6.3 10.1 7.5 4.5 5.1  <20 42 55 52 48 58 0.0001  20-49 32 27 30 28 24  ≥50 26 18 18 24 18  Median [p25-75] 26 [8–50] 16 [6–38] 19 [7–39] 21 [7–48] 14 [3–38] 0.0001 FF Fluticasone Furoate, MF Mometasone Furoate, MPAzeFlu Azelastine-Fluticasone Propionate * Comparing MPAzeFlu versus FF or MF. Chi square tests were used for categorical variables (i.e. symptoms and impact of symptoms, ARIA score, global VAS categories); Kruskal–Wallis tests were used for continuous variables (i.e. ARIA score, global VAS) ±Estimated by dividing the total number of days for which the use of a medication was reported by the total number of users reporting that medication p25: 25th percentile; p75: 75th percentile Table 5 Results for all participants recruited outside the pollen season N users Day 1 Treatment days No treatment days P value* FF MPAzeFlu MF OAH mono 99 80 95 275 1299 Symptoms day 1  Runny nose (%) 72 55 65 71 65 0.03  Itchy nose (%) 72 53 61 61 53 0.03  Sneezing (%) 76 49 71 74 67 <0.001  Nasal congestion (%) 84 63 78 65 62 0.001  Red eyes (%) 39 21 38 41 36 0.006  Itchy eyes (%) 55 38 47 62 52 0.04  Watery eyes (%) 41 29 27 45 34 0.35 Impact of symptoms day 1  Sleep (%) 47 36 43 35 32 0.17  Daily activities (%) 46 36 34 37 38 0.54  Work/school (%) 30 31 24 25 24 0.51  Bothersome (%) 84 55 68 67 67 <0.001 ARIA score (%)  0 8 22 19 20 23  1 30 38 29 34 31  2 23 16 22 21 21 0.06  3 22 10 22 12 15  4 16 14 7 13 11  Median [p25-75] 2 [1–3] 1 [1–2] 2 [1–3] 1 [1–3] 1 [0–2] 0.04 VAS global day 1 (%)  N 99 80 95 275 1299  <20 25 29 27 27 41 0.68  20-49 28 34 33 31 29  ≥50 46 38 40 42 30  Median [p25-75] 44 [19–67] 34.5 [15–62.5] 46 [17–64] 38 [18–66] 29 [6–54] 0.25 VAS global – all days (%)  N days 1116 1258 1437 1956 13,120  N users 167 128 154 437 1553  Average number of days per user± 6.7 9.8 9.3 4.5 8.5  <20 50 54 59 50 74 0.0001  20-49 29 33 27 27 16  ≥50 21 13 15 23 10  Median [p25-75] 19 [5.5-44] 18 [7–36] 14 [5–34] 19 [5-47] 5 [0-20] 0.18 FF Fluticasone Furoate, MF Mometasone Furoate, MPAzeFlu Azelastine-Fluticasone Propionate * Comparing MPAzeFlu versus FF or MF. Chi square tests were used for categorical variables (i.e. symptoms and impact of symptoms, ARIA score, global VAS categories); Kruskal–Wallis tests were used for continuous variables (i.e. ARIA score, global VAS) ± Estimated by dividing the total number of days for which the use of a medication was reported by the total number of users reporting that medication p25: 25th percentile; p75: 75th percentile During the pollen season (Table 4), 69 to 78% of users reported rhinorrhoea on Day 1. Other nasal symptoms were reported in 55 to 87% of users, and ocular symptoms in 42 to 74%. Most users reported bothersome symptoms (74–78%). Impact on sleep, daily activities and work/school attendance was reported in 27–50% of users. The ARIA score was similar in all five groups of users. Outside the pollen season (Table 5), 55 to 72% of users reported rhinorrhoea on Day 1. Other nasal symptoms were reported in 49 to 84% of users and ocular symptoms in 21 to 62%. Most users reported bothersome symptoms (55–84%). Impact on sleep, daily activities and work/school attendance was reported in 24 to 47% of users. The use of MPAzeFlu on Day 1 was significantly associated with fewer symptoms, compared to the use of FF or MF. App users who reported the use of MPAzeFlu on Day 1 were less likely to report a severe impact of symptoms, compared to users of FF or MF on Day 1. However, the difference was only borderline significant. Significantly more symptoms on Day 1 were reported during the pollen season than outside the pollen season, and the ARIA severity score was significantly higher outside the pollen season. Similar trends were found when restricting the population to users not reporting treatment on Day 1 (results not shown). Treatment efficacy During the pollen season, on Day 1, VAS levels were reported by 3736 users without treatment, 1414 users with OAH in monotherapy and 841 users with INCS treatment (Table 4). No statistically significant difference in VAS levels was observed between INCS treatments on Day 1. When all VAS days were studied, we observed significantly lower VAS levels in MPAzeFlu days compared to other INCS (FF or MF) days (p = 0.0001, Table 4). Outside the pollen season, on Day 1, VAS levels were reported by 1299 users without treatment, 275 users with OAH in monotherapy and 274 users with INCS treatment (Table 5). No statistically significant difference in VAS levels was observed between INCS treatments on Day 1. When all VAS days were studied, we observed non-significant differences between MPAzeFlu use compared to other INCS use or OAH. Monotherapy versus co-medication according to INCS use During the pollen season, monotherapy was significantly more reported in users who reported the use of MPAzeFlu on Day 1 (44%) compared to app users who reported the use of FF or MF on Day 1 (i.e. between 30 and 35%) (p < 0.01). Similar results were found when all VAS days were studied (p < 0.001) (Fig. 2).Fig. 2 Proportion of INCS treatment groups on all days during and outside the pollen season Outside the pollen season, monotherapy was significantly more reported in users who reported the use of MPAzeFlu on Day 1 (71%) compared to those who reported the use of FF or MF on Day 1 (40 to 50%) (p < 0.001). Similar results were found when all VAS days were studied (p < 0.001) (Fig. 2). Number of days with treatment In untreated users, the estimated average number of days of reporting per user increased from 5.1 (during pollen season) to 8.5 (outside). Both during and outside the pollen season, there was a similar trend of days reported from OAH, FF, MF to MPAzeFlu (Tables 4 and 5). The average number of days of reporting per user was low for OAH (4.5 days) and increased to around 10 days for MPAzeFlu (during and outside pollen season). Discussion Two MASK studies [4, 11] have shown that, in real life, the assessment of days can provide (i) information on patients’ treatment (ii) novel insight into the behaviour of AR patients towards treatment and (iii) novel concepts for change management of AR [29]. In the present study (Table 3), we show that the ARIA severity score is (i) lower outside than during the pollen season (ii) similar for all INCS treatment groups on Day 1 during the pollen season and (iii) lower in the MPAzeFlu group than in the MF and FF groups outside the pollen season. We also show that MPAzeFlu might be more effective than FF or MF in the pollen season (lower VAS levels are reported in days with MPAzeFlu treatment, and MPAzeFlu is more frequently used as monotherapy) as well as outside the pollen season (more frequent use of monotherapy). Finally, the number of days of reported treatment per user increased from OAH to MPAzeFlu (Table 6).Table 6 New information provided by this paper 1. There was no differential assessment of MASK during and between the pollen seasons 2. There was  no assessment of baseline characteristics 3. Patients included in MASK have moderate/severe AR during and outside the pollen season although they were less severe outside the pollen season Strengths and limitations Strengths and limitations of MASK have previously been reported [11]. As for all studies using participatory data, potential biases include (i) the likelihood of sampling bias being present (ii) the lack of generalizability of the study that was found, as bothersome symptoms are present in around 80% of users, indicating that most users have a moderate to severe disease, and (iii) outcome misclassification that cannot be assessed. Data obtained with an app are not representative of the general population. In the previous MASK studies, there was very little information on patient characteristics. In the present study, we examined characteristics at entry in more detail. As in other studies [4, 11], we used days in a cross-sectional analysis because there is no clear pattern of treatment and a longitudinal study was not feasible since users mostly use the App intermittently. In the current study, we cannot ascertain that the users are allergic to a given allergen since this information is not available for all patients. Moreover, we did not assess the real pollen exposure of the patients, as only 60% of them agreed to be geolocated. The diagnosis of AR was not supported by a physician but was a response to the question: “Do you have allergic rhinitis? Yes/No”. Some of the users with non-allergic rhinitis may therefore have responded “Yes” to the question. However, > 95% of responders declared symptoms of AR by questionnaire. Precise patient characterization is impossible using an App, but every observational study using MASK was able to identify days with poor control or criteria of severity [26, 27, 30–32]. Moreover, some data are highly similar across studies. These include the percentage of untreated days (i.e. approximately 50% of the total days recorded). There is a clear deviation in the results obtained in highly populated countries and a very high prevalence of allergic rhinitis with little collection data. These results could possibly influence the data. The current study has many strengths including larger numbers, multiple countries, range of treatments studied and patient/person-generated data. Interpretation of the results and generalizability This real-world assessment of the Allergy Diary using VAS allows the  assessment of treatment efficacy by days [4, 11]. This observational study complements the two previous studies in many aspects (Table 7).Table 7 Key messages 1. What is already known about this topic? The MASK mHealth App has generated real-world evidence that has led to novel pharmacotherapy insights – for example, that patterns of treatment for allergic rhinitis do not always accord with guidelines. 2. What does this article add to our knowledge? Results can be extended to both the estimated pollen season and the period outside. The study shows that rhinitis medications are equally effective during and outside the pollen season. The baseline characteristics of the patients show that most users have moderate to severe rhinitis and that mHealth data may not be generalisable to all patients with allergic rhinitis 3. How does this study impact current management guidelines? This paper confirms the importance of the MASK mHealth App in next-generation GRADE guidelines that embed real-world-evidence into the GRADE-based evidence. The same treatment can be administered during and outside the pollen season First, it shows that over 75% of patients using the app during the pollen season have bothersome symptoms. Outside of the pollen season, the rate of bothersome symptoms is around 65%. It is therefore likely that most App users have moderate/severe AR and do not therefore represent the general population [33]. It is interesting to note that these levels of impairment are close to those of patients consulting in primary [34] or specialist care [35]. Although the impact of AR is less important outside the pollen season than during, differences are not very important in the ARIA score. Second, it was expected that MPAzeFlu would have been given to more severe patients. The ARIA score was not different between groups in the pollen season. In contradistinction, the ARIA score was significantly lower outside the pollen season in untreated users and even lower in the MPAzeFlu users. Third, both during and outside the pollen season, MPAzeFlu is associated with less symptoms, something that seems consistent with being the most potent medication in a randomized controlled trial [36]. However, there are differences between seasons. During the pollen season, the use of MPAzeFlu is associated with the lowest VAS levels in treated groups, and MPAzeFlu is used more commonly as monotherapy. Outside of the pollen season, all medications appear to be associated with similar VAS levels. However, MPAzeFlu is used as a monotherapy in 70% of days whereas the other INCS are used in less than 50% of days. Nevertheless, given the cross-sectional setting of our study, effectiveness cannot be inferred easily. Fourth, the estimated average number of days reported per user in the MPAzeFlu group was almost twice as high as that among the OAH group. Although there is no simple interpretation, it is suggested that the most effective treatments are reported for a longer period of time. However, we cannot assess duration in this cross-sectional setting, but this finding is consistently found across MASK studies [11]. Again, there is no major difference between seasons. Fifth, as already found in all users [4, 11], median VAS levels are the lowest in untreated days, both during and outside the pollen season. This can be interpreted as subjects using treatment when they do not feel well, in opposition to the paradigm in which those who take medication are the ones with controlled symptoms (and therefore lower VAS). Also, the patterns of co-medication of MPAzeFlu by comparison to FF or MF are similar in the two periods. Sixth, the behaviour of users appears to be quite similar between seasons. In particular, they report the same number of days with the same medications. This study shows that, in real-life, the same treatments have similar patterns during and outside the pollen season for most criteria tested. This is an important finding that may impact guidelines considering AR severity rather than seasonal patterns [37, 38]. Conclusions Although the MASK mHealth App has generated real-world evidence that has led to novel pharmacotherapy insights, the current study extends our knowledge by (i) assessing the characteristics of the patients, (ii) showing that results can be extended to both the estimated pollen season and the period outside the season, and (iii) showing that rhinitis medications are equally effective during and outside the pollen season (Table 5). Real-world data (RWD) and real-world evidence (RWE) both play an increasing role in health care decisions supporting clinical trial designs and observational studies to generate innovative and new treatment approaches. This study shows that the overall efficacy of treatments is similar during and outside the pollen season and indicates that medications are similarly effective during the year. It is an important study for the digital transformation of health and care in rhinitis and asthma multimorbidity [3, 39–41]. Abbreviations ARAllergic rhinitis ARIAAllergic Rhinitis and its Impact on Asthma MPAzeFluIntranasal azelastine-fluticasone propionate CETCetirizine DLDesloratadine FEXOFexofenadine FFFluticasone Furoate FPFluticasone Propionate GRADEGrading of Recommendations, Assessment, Development and Evaluation ICTInformation Communication Technology INCSIntranasal corticosteroid INNInternational Nonproprietary Names LEVOCETLevocetirizine LoraLoratadine MASK-rhinitisMobile Airways Sentinel NetworK for allergic rhinitis MFMometasone Furoate OAHOral H1-anti-histamine RCTRandomized controlled trial VASvisual analogue scale Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Authors’ contributions JB proposed the study and is leading the analyses of MASK, he participated in  the writing of the paper; AB performed the analyses of the data and wrote the paper; XB, JMA JG, PD, IA proposed the analyses and reviewed the data and analyses; SA and GLO led the data management; AB is the MASK project manager and reviewed the English; WC and RM participated in the concept of the study and the review of the data; RA, JAF, JCS, MM, AT, EC included Portuguese patients; LC, GF, MI, EM, RM, CSt, MT Ventura included Italian patients; IB, JF Fontaine, N Pham-Thi included French patients; PS, FS included Swiss patients; NHC, WJF, S Reitsma included Dutch patients; RD, RE, VK, AV included Lithuanian patients; PK, BS included Polish patients; LK, RM, OP, SS included German patients; RER, PVT included Austrian patients; DR, AS included UK patients; TH, ST, EV included Finnish patients; VC, JM, AV included Spanish patients; MM, NGP, EPP, FP included Greek patients; CB, PWH, BP included Belgian patients; CB, E included Danish patients; IK, EM, MW included Swedish patients; MT and MS gave advice for pollen counts; GV, ME are the app developpers; IA, IJA, SB, AAC, TC, JCI, DL, DW, SW, AY are members of the MASK study group, they reviewed the protocol and the results; D Laune is a member of Kyomed Innov where the app data are monitored. All authors read and approved the final manuscript. Funding MASK, SPAL (EU structural and development funds), unrestricted educational grant from Mylan. Availability of data and materials  On request to Kyomed Innov. Members of the MASK study group have free access to the data. Ethics approval and consent to participate The Allergy Diary is CE1 registered. By using k-anonymity, the data were all anonymized including the data related to geolocalization. MASK-air® is in line with the General Data Protection Regulation (GDPR) EU Directive 95/46/EC. Independent Review Board approval was not required since the study is observational and users agree to having their data analysed (terms of use). Consent for publication Not applicable. Competing interests Dr. Almeida reports grants from ERDF (European Regional Development Fund) through the operation POCI-01-0145-FEDER-029130 (“mINSPIRERS—mHealth para medição e melhoria da adesão à medicação nas doenças respiratórias obstrutivas crónicas—generalização e avaliação de tecnologias de gamificação, suporte por pares e processamento avançado de imagem”) funded by the Programa Operacional Competitividade e Internacionalização—COMPETE2020 and by National Funds through FCT (Fundação para a Ciência e a Tecnologia, during the conduct of the study.Dr. Ansotegui reports personal fees from Hikma, Roxall, Astra Zeneca, Menarini, UCB, Faes Farma, Sanofi, Mundipharma, outside the submitted work.Bachert: Meda, Stallergenes and ALK (speaker). J Bousquet reports personal fees and other from Chiesi, Cipla, Hikma, Menarini, Mundipharma, Mylan, Novartis, Sanofi-Aventis, Takeda, Teva, Uriach, outside the submitted work. other from Kyomed. Dr. Bosnic-Anticevich reports personal fees from Teva, Boehringer Ingelheim, Sanofi, GSK, AstraZeneca, outside the submitted work. Dr. Cardona reports personal fees from ALK, Allergopharma, Allergy Therapeutics, Diater, LETI, Thermofisher, Stallergenes, outside the submitted work. Dr. Cecchi reports personal fees from Menarini, Malesci, ALK Abellò, Menarini, non-financial support from Mundipharma, outside the submitted work.Dr. Correia-de-Sousa reports other from Boheringer Ingelheim, GSK, AstraZeneca, outside the submitted work. Dr. Cruz reports grants and personal fees from Astrazeneca, grants from GSK, personal fees from Boehringer Ingelheim, CHIESI, NOVARTIS, Eurofarma, MEDA Pharma, Boston Scientific, outside the submitted work. Dr. Devillier reports personal fees and non-financial support from Astra Zeneca, Mylan, Stallergenes Greer, personal fees from ALK Abello, Menarini, GlaxoSmithKline, Sanofi, outside the submitted work. Dr. Haahtela reports personal fees from Mundipharma, Novartis, and Orion Pharma, outside the submitted work. Dr. Eller reports other from Thermofisher Scientific, outside the submitted work. Dr. Fonseca reports personal fees from AstraZeneca, GSK, Novartis, Teva, grants from Mundipharma, outside the submitted work. Dr. Ivancevich reports personal fees from Faes Farma Euro-Farma Argentina, other from Lboratorios Casasco, Sanofi, outside the submitted work. Dr. Fokkens reports grants from Mylan, ALK, Allergy Therapeutics, GSK, Sanofi, Novartis, outside the submitted work. Dr. Klimek reports personal fees from MEDA, Sweden, Boehringer Ingelheim, Germany, grants and personal fees from ALK Abelló, Denmark, Novartis, Switzerland, Allergopharma, Germany, Bionorica, Germany, GSK, Great Britain, Lofarma, Italy, grants from Biomay, Austria, HAL, Netherlands, LETI, Spain, Roxall, Germany Bencard, Great Britain, outside the submitted work. Dr. Kuna reports personal fees from Adamed, Boehringer Ingelheim, AstraZeneca, Chiesi, FAES, Berlin Chemie, Novartis, Polpharma, Allergopharma,outside the submitted work. Dr Kvedariene has received payment for consultancy from GSK and for lectures from StallergensGreer, Berlin-CHemie outside the submitted work. Dr. Larenas Linnemann reports personal fees from Amstrong, Astrazeneca, Boehringer Ingelheim, Chiesi, DBV Technologies, Grunenthal, GSK, MEDA, Menarini, MSD, Novartis, Pfizer, Sanofi, Siegfried, UCB, grants from Sanofi, Astrazeneca, Novartis, UCB, GSK, TEVA, Boehringer Ingelheim, Chiesi, outside the submitted work. Dr. Melén reports personal fees from Advisory board reimbursement from Novartis, outside the submitted work. Dr. Ralph Mösges reports personal fees from ALK, allergopharma, Allergy Therapeutics, Hexal, personal fees from Servier, personal fees from Klosterfrau, Stada, UCB, Friulchem, grants from ASIT biotech, Nuvo, Bayer, FAES, GSK, MSD, Johnson&Johnson, Meda, Optima, Ursapharm, BitopAG, Hulka, grants and personal fees from Bencard, grants from Leti, Stallergenes, grants, personal fees and non-financial support from Lofarma, non-financial support from Roxall, from Atmos, from Bionorica, Otonomy, Ferrero, personal fees and non-financial support from Novartis, outside the submitted work. Dr. Papadopoulos reports grants from Gerolymatos, personal fees from Hal Allergy B.V., Novartis Pharma AG, Menarini, Hal Allergy B.V., Mylan, outside the submitted work. Dr. Pfaar reports grants and personal fees from ALK-Abelló, Allergopharma, Stallergenes Greer, HAL Allergy Holding B.V./HAL Allergie GmbH, Bencard Allergie GmbH/Allergy Therapeutics, Lofarma, ASIT Biotech Tools S.A., Laboratorios LETI/LETI Pharma, Anergis S.A., grants from Glaxo Smith Kline, Biomay, Nuvo, Circassia, personal fees from MEDA Pharma/MYLAN, Mobile Chamber Experts (a GA2LEN Partner Indoor Biotechnologies, Astellas Pharma Global, outside the submitted work. Dr. Ryan reports personal fees from Mylan, AZ, AZ, GSK, from Chiesi, BI, grants from Mylan, outside the submitted work.Dr Schmid-Grendelmeier reports honarium and consultancy fees from ALK-Abello, Allergopharma, Bencard, MEDA and Stallergenes Dr. Stelmach reports grants from São Paulo Research Foundation, MSD, grants and personal fees from Novartis, grants, personal fees and non-financial support from AstraZeneca, Chiesi, personal fees and non-financial support from Boheringer Ingelheim, outside the submitted work. Dr. Todo-Bom reports grants and personal fees from Novartis, Mundipharma, GSK Teva Pharma, personal fees from AstraZeneca, grants from Boehringer Ingelheim, Sanofi, Leti, outside the submitted work. Dr. Toppila-Salmi reports other from Biomedical Systems Ltd., Roche Ltd., grants from Erkko Foundation, outside the submitted work. Dr. Waserman reports other from CSL Behring Shire, AstraZeneca, Teva, Meda, other from Merck, GSK, Novartis, Pediapharm, Aralez Sanofi, Stallergenes, outside the submitted work. ==== Refs References 1. Bousquet J Arnavielhe S Bedbrook A Bewick M Laune D Mathieu-Dupas E MASK 2017: ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity using real-world-evidence Clin Transl Allergy. 2018 8 45 10.1186/s13601-018-0227-6 30386555 2. 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