Identification by cluster analysis of patients with asthma and nasal symptoms using the MASK-air® mHealth app

peer reviewedBackground: The self-reporting of asthma frequently leads to patient misidentification in epidemiological studies. Strategies combining the triangulation of data sources may help to improve the identification of people with asthma. We aimed to combine information from the self-reporting of asthma, medication use and symptoms to identify asthma patterns in the users of an mHealth app. Methods: We studied MASK-air® users who reported their daily asthma symptoms (assessed by a 0-100 visual analogue scale – “VAS Asthma”) at least three times (either in three different months or in any period). K-means cluster analysis methods were applied to identify asthma patterns based on: (i) whether the user self-reported asthma; (ii) whether the user reported asthma medication use and (iii) VAS asthma. Clusters were compared by the number of medications used, VAS asthma levels and Control of Asthma and Allergic Rhinitis Test (CARAT) levels. Findings: We assessed a total of 8,075 MASK-air® users. The main clustering approach resulted in the identification of seven groups. These groups were interpreted as probable: (i) severe/uncontrolled asthma despite treatment (11.9-16.1% of MASK-air® users); (ii) treated and partly-controlled asthma (6.3-9.7%); (iii) treated and controlled asthma (4.6-5.5%); (iv) untreated uncontrolled asthma (18.2-20.5%); (v) untreated partly-controlled asthma (10.1-10.7%); (vi) untreated controlled asthma (6.7-8.5%) and (vii) no evidence of asthma (33.0-40.2%). This classification was validated in a study of 192 patients enrolled by physicians. Interpretation: We identified seven profiles based on the probability of having asthma and on its level of control. mHealth tools are hypothesis-generating and complement classical epidemiological approaches in identifying patients with asthma. © 2022 Sociedade Portuguesa de Pneumologi

Os diversos papéis dos subconjuntos de células T na asma

Asthma is a heterogeneous disease. Several distinct clinical phenotypes have been described and it is now debated whether asthma is a “single disease” or, instead, a group of inflammatory lung diseases with similar manifestations but diverse pathophysiology. More recently, these underlying inflammation mechanisms have been used to classify asthma into “endotypes” (1). Although several markers have been proposed to distinguish specific asthma endotypes (e.g., IgE sensitization in allergic asthma, peripheral eosinophil counts in eosinophilic asthma, periostin in Th2-high asthma, etc.), the most consensual distinction is based on the CD4+ T-helper (Th) cytokine profiles involved (i.e., Th2-high vs Th2-low), therefore illustrating the central role of these cells in asthma. T cells are central coordinators of the immune response. T-cell receptor (TCR) recognition is crucial for the initiation and specificity of the adaptive immune response, while T cell dervied cytokines tailor the type of immune response. Asthma is an inflammatory lung disease and T cells have been shown to play a central role in the pathophysiology of the disease. A good understanding of T cells in asthma is also important for therapeutic reasons, in particular for the choice of biological treatments in severe asthma. T cells are generally divided into two major types: CD4+ T cells and CD8+ T cells. CD4+ T cell are activated by antigen presented by major histocompatibility complex (MHC) class II on the surface of professional antigen-presenting cells (APC), whereas CD8+T cells recognize antigens presented by MHC class I on the surface of all nucleated cells. As discussed below, each of these types can be subdivided into several functionally distinct subtypes. Classically, asthma has been considered a Th2-mediated inflam matory disease. However, more recent studies have identified contributing roles for other types of T cells in the pathophysiology and the heterogeneity of the disease. In this chapter, we review how the different types and subtypes of T cells are involved in asthma and its phenotypes/endotypes.info:eu-repo/semantics/publishedVersio

The Role of Mobile Health Technologies in Stratifying Patients for AIT and Its Cessation: The ARIA-EAACI Perspective

Allergen immunotherapy (AIT) is a proven therapeutic option for the treatment of allergic rhinitis and/or asthma. Many international or national practice guidelines have been produced, but the evidence-based method varies and they do not usually propose care pathways. The present article considers the possible role of mobile health in AIT for allergic rhinitis/asthma. There are no currently available validated biologic biomarkers that can predict AIT success, and mobile health biomarkers have some relevance. In the current article, the following aspects will be discussed: patient stratification for AIT, symptom-medication scores for the follow-up of patients, clinical trials, as well as the approach of the European Academy of Allergy and Clinical Immunology. © 2021 American Academy of Allergy, Asthma & Immunolog

Potential Interplay between Nrf2, TRPA1, and TRPV1 in Nutrients for the Control of COVID-19

In this article, we propose that differences in COVID-19 morbidity may be associated with transient receptor potential ankyrin 1 (TRPA1) and/or transient receptor potential vanilloid 1 (TRPV1) activation as well as desensitization. TRPA1 and TRPV1 induce inflammation and play a key role in the physiology of almost all organs. They may augment sensory or vagal nerve discharges to evoke pain and several symptoms of COVID-19, including cough, nasal obstruction, vomiting, diarrhea, and, at least partly, sudden and severe loss of smell and taste. TRPA1 can be activated by reactive oxygen species and may therefore be up-regulated in COVID-19. TRPA1 and TRPV1 channels can be activated by pungent compounds including many nuclear factor (erythroid-derived 2) (Nrf2)-interacting foods leading to channel desensitization. Interactions between Nrf2-associated nutrients and TRPA1/TRPV1 may be partly responsible for the severity of some of the COVID-19 symptoms. The regulation by Nrf2 of TRPA1/TRPV1 is still unclear, but suggested from very limited clinical evidence. In COVID-19, it is proposed that rapid desensitization of TRAP1/TRPV1 by some ingredients in foods could reduce symptom severity and provide new therapeutic strategies. © 2021 S. Karger AG, Basel

Behavioural patterns in allergic rhinitis medication in Europe: A study using MASK-air® real-world data

Background: Co-medication is common among patients with allergic rhinitis (AR), but its dimension and patterns are unknown. This is particularly relevant since AR is understood differently across European countries, as reflected by rhinitis-related search patterns in Google Trends. This study aims to assess AR co-medication and its regional patterns in Europe, using real-world data. Methods: We analysed 2015–2020 MASK-air® European data. We compared days under no medication, monotherapy and co-medication using the visual analogue scale (VAS) levels for overall allergic symptoms (‘VAS Global Symptoms’) and impact of AR on work. We assessed the monthly use of different medication schemes, performing separate analyses by region (defined geographically or by Google Trends patterns). We estimated the average number of different drugs reported per patient within 1 year. Results: We analysed 222,024 days (13,122 users), including 63,887 days (28.8%) under monotherapy and 38,315 (17.3%) under co-medication. The median ‘VAS Global Symptoms’ was 7 for no medication days, 14 for monotherapy and 21 for co-medication (p <.001). Medication use peaked during the spring, with similar patterns across different European regions (defined geographically or by Google Trends). Oral H1-antihistamines were the most common medication in single and co-medication. Each patient reported using an annual average of 2.7 drugs, with 80% reporting two or more. Conclusions: Allergic rhinitis medication patterns are similar across European regions. One third of treatment days involved co-medication. These findings suggest that patients treat themselves according to their symptoms (irrespective of how they understand AR) and that co-medication use is driven by symptom severity. © 2022 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd

Allergen immunotherapy in MASK-air users in real-life: Results of a Bayesian mixed-effects model

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. © 2022 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology

Development and validation of combined symptom-medication scores for allergic rhinitis*

Background: Validated combined symptom-medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real-life data from the MASK-air® app to generate and validate hypothesis- and data-driven CSMSs. Methods: We used MASK-air® data to assess the concurrent validity, test-retest reliability and responsiveness of one hypothesis-driven CSMS (modified CSMS: mCSMS), one mixed hypothesis- and data-driven score (mixed score), and several data-driven CSMSs. The latter were generated with MASK-air® data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK-air®, and Work Productivity and Activity Impairment: Allergy Specific [WPAI-AS]), (ii) quality-of-life (EQ-5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). Results: We assessed 317,176 days of MASK-air® use from 17,780 users aged 16-90 years, in 25 countries. The mCSMS and the factor analyses-based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate-to-strong correlations with the tested comparators, high test-retest reliability and moderate-to-large responsiveness. Among data-driven CSMSs, a better performance was observed for cluster analyses-based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC-ROC = 0.904) and for the mixed CSMS (AUC-ROC = 0.820). Conclusion: The mixed CSMS and the cluster-based CSMSs presented medium-high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials. © 2022 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd

COVID-19 pandemic: Practical considerations on the organization of an allergy clinic—An EAACI/ARIA Position Paper

Background: The coronavirus disease 2019 (COVID-19) has evolved into a pandemic infectious disease transmitted by the severe acute respiratory syndrome coronavirus (SARS-CoV-2). Allergists and other healthcare providers (HCPs) in the field of allergies and associated airway diseases are on the front line, taking care of patients potentially infected with SARS-CoV-2. Hence, strategies and practices to minimize risks of infection for both HCPs and treated patients have to be developed and followed by allergy clinics. Method: The scientific information on COVID-19 was analysed by a literature search in MEDLINE, PubMed, the National and International Guidelines from the European Academy of Allergy and Clinical Immunology (EAACI), the Cochrane Library, and the internet. Results: Based on the diagnostic and treatment standards developed by EAACI, on international information regarding COVID-19, on guidelines of the World Health Organization (WHO) and other international organizations, and on previous experience, a panel of experts including clinicians, psychologists, IT experts, and basic scientists along with EAACI and the “Allergic Rhinitis and its Impact on Asthma (ARIA)” initiative have developed recommendations for the optimal management of allergy clinics during the current COVID-19 pandemic. These recommendations are grouped into nine sections on different relevant aspects for the care of patients with allergies. Conclusions: This international Position Paper provides recommendations on operational plans and procedures to maintain high standards in the daily clinical care of allergic patients while ensuring the necessary safety measures in the current COVID-19 pandemic. © 2020 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd

Management of anaphylaxis due to COVID-19 vaccines in the elderly

none149siOlder adults, especially men and/or those with diabetes, hypertension, and/or obesity, are prone to severe COVID-19. In some countries, older adults, particularly those residing in nursing homes, have been prioritized to receive COVID-19 vaccines due to high risk of death. In very rare instances, the COVID-19 vaccines can induce anaphylaxis, and the management of anaphylaxis in older people should be considered carefully. An ARIA-EAACI-EuGMS (Allergic Rhinitis and its Impact on Asthma, European Academy of Allergy and Clinical Immunology, and European Geriatric Medicine Society) Working Group has proposed some recommendations for older adults receiving the COVID-19 vaccines. Anaphylaxis to COVID-19 vaccines is extremely rare (from 1 per 100,000 to 5 per million injections). Symptoms are similar in younger and older adults but they tend to be more severe in the older patients. Adrenaline is the mainstay treatment and should be readily available. A flowchart is proposed to manage anaphylaxis in the older patients.noneBousquet J.; Agache I.; Blain H.; Jutel M.; Ventura M.T.; Worm M.; Del Giacco S.; Benetos A.; Bilo B.M.; Czarlewski W.; Abdul Latiff A.H.; Al-Ahmad M.; Angier E.; Annesi-Maesano I.; Atanaskovic-Markovic M.; Bachert C.; Barbaud A.; Bedbrook A.; Bennoor K.S.; Berghea E.C.; Bindslev-Jensen C.; Bonini S.; Bosnic-Anticevich S.; Brockow K.; Brussino L.; Camargos P.; Canonica G.W.; Cardona V.; Carreiro-Martins P.; Carriazo A.; Casale T.; Caubet J.-C.; Cecchi L.; Cherubini A.; Christoff G.; Chu D.K.; Cruz A.A.; Dokic D.; El-Gamal Y.; Ebisawa M.; Eberlein B.; Farrell J.; Fernandez-Rivas M.; Fokkens W.J.; Fonseca J.A.; Gao Y.; Gavazzi G.; Gawlik R.; Gelincik A.; Gemicioglu B.; Gotua M.; Guerin O.; Haahtela T.; Hoffmann-Sommergruber K.; Hoffmann H.J.; Hofmann M.; Hrubisko M.; Illario M.; Irani C.; Ispayeva Z.; Ivancevich J.C.; Julge K.; Kaidashev I.; Khaitov M.; Knol E.; Kraxner H.; Kuna P.; Kvedariene V.; Lauerma A.; Le L.T.T.; Le Moing V.; Levin M.; Louis R.; Lourenco O.; Mahler V.; Martin F.C.; Matucci A.; Milenkovic B.; Miot S.; Montella E.; Morais-Almeida M.; Mortz C.G.; Mullol J.; Namazova-Baranova L.; Neffen H.; Nekam K.; Niedoszytko M.; Odemyr M.; O'Hehir R.E.; Okamoto Y.; Ollert M.; Palomares O.; Papadopoulos N.G.; Panzner P.; Passalacqua G.; Patella V.; Petrovic M.; Pfaar O.; Pham-Thi N.; Plavec D.; Popov T.A.; Recto M.T.; Regateiro F.S.; Reynes J.; Roller-Winsberger R.E.; Rolland Y.; Romano A.; Rondon C.; Rottem M.; Rouadi P.W.; Salles N.; Samolinski B.; Santos A.F.; S Sarquis F.; Sastre J.; M. G. A. Schols J.; Scichilone N.; Sediva A.; Shamji M.H.; Sheikh A.; Skypala I.; Smolinska S.; Sokolowska M.; Sousa-Pinto B.; Sova M.; Stelmach R.; Sturm G.; Suppli Ulrik C.; Todo-Bom A.M.; Toppila-Salmi S.; Tsiligianni I.; Torres M.; Untersmayr E.; Urrutia Pereira M.; Valiulis A.; Vitte J.; Vultaggio A.; Wallace D.; Walusiak-Skorupa J.; Wang D.-Y.; Waserman S.; Yorgancioglu A.; Yusuf O.M.; Zernotti M.; Zidarn M.; Chivato T.; Akdis C.A.; Zuberbier T.; Klimek L.Bousquet, J.; Agache, I.; Blain, H.; Jutel, M.; Ventura, M. T.; Worm, M.; Del Giacco, S.; Benetos, A.; Bilo, B. M.; Czarlewski, W.; Abdul Latiff, A. H.; Al-Ahmad, M.; Angier, E.; Annesi-Maesano, I.; Atanaskovic-Markovic, M.; Bachert, C.; Barbaud, A.; Bedbrook, A.; Bennoor, K. S.; Berghea, E. C.; Bindslev-Jensen, C.; Bonini, S.; Bosnic-Anticevich, S.; Brockow, K.; Brussino, L.; Camargos, P.; Canonica, G. W.; Cardona, V.; Carreiro-Martins, P.; Carriazo, A.; Casale, T.; Caubet, J. -C.; Cecchi, L.; Cherubini, A.; Christoff, G.; Chu, D. K.; Cruz, A. A.; Dokic, D.; El-Gamal, Y.; Ebisawa, M.; Eberlein, B.; Farrell, J.; Fernandez-Rivas, M.; Fokkens, W. J.; Fonseca, J. A.; Gao, Y.; Gavazzi, G.; Gawlik, R.; Gelincik, A.; Gemicioglu, B.; Gotua, M.; Guerin, O.; Haahtela, T.; Hoffmann-Sommergruber, K.; Hoffmann, H. J.; Hofmann, M.; Hrubisko, M.; Illario, M.; Irani, C.; Ispayeva, Z.; Ivancevich, J. C.; Julge, K.; Kaidashev, I.; Khaitov, M.; Knol, E.; Kraxner, H.; Kuna, P.; Kvedariene, V.; Lauerma, A.; L. T. T., Le; Le Moing, V.; Levin, M.; Louis, R.; Lourenco, O.; Mahler, V.; Martin, F. C.; Matucci, A.; Milenkovic, B.; Miot, S.; Montella, E.; Morais-Almeida, M.; Mortz, C. G.; Mullol, J.; Namazova-Baranova, L.; Neffen, H.; Nekam, K.; Niedoszytko, M.; Odemyr, M.; O'Hehir, R. E.; Okamoto, Y.; Ollert, M.; Palomares, O.; Papadopoulos, N. G.; Panzner, P.; Passalacqua, G.; Patella, V.; Petrovic, M.; Pfaar, O.; Pham-Thi, N.; Plavec, D.; Popov, T. A.; Recto, M. T.; Regateiro, F. S.; Reynes, J.; Roller-Winsberger, R. E.; Rolland, Y.; Romano, A.; Rondon, C.; Rottem, M.; Rouadi, P. W.; Salles, N.; Samolinski, B.; Santos, A. F.; S Sarquis, F.; Sastre, J.; M. G. A. Schols J., ; Scichilone, N.; Sediva, A.; Shamji, M. H.; Sheikh, A.; Skypala, I.; Smolinska, S.; Sokolowska, M.; Sousa-Pinto, B.; Sova, M.; Stelmach, R.; Sturm, G.; Suppli Ulrik, C.; Todo-Bom, A. M.; Toppila-Salmi, S.; Tsiligianni, I.; Torres, M.; Untersmayr, E.; Urrutia Pereira, M.; Valiulis, A.; Vitte, J.; Vultaggio, A.; Wallace, D.; Walusiak-Skorupa, J.; Wang, D. -Y.; Waserman, S.; Yorgancioglu, A.; Yusuf, O. M.; Zernotti, M.; Zidarn, M.; Chivato, T.; Akdis, C. A.; Zuberbier, T.; Klimek, L

Management of anaphylaxis due to COVID-19 vaccines in the elderly

Older adults, especially men and/or those with diabetes, hypertension, and/or obesity, are prone to severe COVID-19. In some countries, older adults, particularly those residing in nursing homes, have been prioritized to receive COVID-19 vaccines due to high risk of death. In very rare instances, the COVID-19 vaccines can induce anaphylaxis, and the management of anaphylaxis in older people should be considered carefully. An ARIA-EAACI-EuGMS (Allergic Rhinitis and its Impact on Asthma, European Academy of Allergy and Clinical Immunology, and European Geriatric Medicine Society) Working Group has proposed some recommendations for older adults receiving the COVID-19 vaccines. Anaphylaxis to COVID-19 vaccines is extremely rare (from 1 per 100,000 to 5 per million injections). Symptoms are similar in younger and older adults but they tend to be more severe in the older patients. Adrenaline is the mainstay treatment and should be readily available. A flowchart is proposed to manage anaphylaxis in the older patients. © 2021 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd