BACKGROUND: Adherence to rhinitis treatment has been insufficiently assessed. We aimed to use data from the MASK-air mHealth app to assess adherence to oral antihistamines (OAH), intra-nasal corticosteroids (INCS) or azelastine-fluticasone in patients with allergic rhinitis. METHODS: We included regular European MASK-air users with self-reported allergic rhinitis and reporting at least 1 day of OAH, INCS or azelastine-fluticasone. We assessed weeks during which patients answered the MASK-air questionnaire on all days. We restricted our analyses to data provided between January and June, to encompass the pollen seasons across the different assessed countries. We analysed symptoms using visual analogue scales (VASs) and the combined symptom-medication score (CSMS), performing stratified analyses by weekly adherence levels. Medication adherence was computed as the proportion of days in which patients reported rhinitis medication use. Sensitivity analyses were performed considering all weeks with at most 1 day of missing data and all months with at most 4 days of missing data. RESULTS: We assessed 8212 complete weeks (1361 users). Adherence (use of medication > 80% days) to specific drug classes ranged from 31.7% weeks for azelastine-fluticasone to 38.5% weeks for OAH. Similar adherence to rhinitis medication was found in users with or without self-reported asthma, except for INCS (better adherence in asthma patients). VAS and CSMS levels increased from no adherence to full adherence, except for INCS. A higher proportion of days with uncontrolled symptoms was observed in weeks with higher adherence. In full adherence weeks, 41.2% days reported rhinitis co-medication. The sensitivity analyses displayed similar results. CONCLUSIONS: A high adherence was found in patients reporting regular use of MASK-air. Different adherence patterns were found for INCS compared to OAH or azelastine-fluticasone that are likely to impact guidelines.
- Klíčová slova
- allergic rhinitis, mobile health, treatment adherence,
- Publikační typ
- časopisecké články MeSH
The traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients' resources and abilities to be experts in their own lives based on their lived experiences. Improving healthcare safety, quality, and coordination, as well as quality of life, is an important aim in the care of patients with chronic conditions. Person-centered care needs to ensure that people's values and preferences guide clinical decisions. This paper reviews current knowledge to develop (1) digital care pathways for rhinitis and asthma multimorbidity and (2) digitally enabled, person-centered care.1 It combines all relevant research evidence, including the so-called real-world evidence, with the ultimate goal to develop digitally enabled, patient-centered care. The paper includes (1) Allergic Rhinitis and its Impact on Asthma (ARIA), a 2-decade journey, (2) Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, (3) mHealth impact on airway diseases, (4) From guidelines to digital care pathways, (5) Embedding Planetary Health, (6) Novel classification of rhinitis and asthma, (7) Embedding real-life data with population-based studies, (8) The ARIA-EAACI (European Academy of Allergy and Clinical Immunology) strategy for the management of airway diseases using digital biomarkers, (9) Artificial intelligence, (10) The development of digitally enabled, ARIA person-centered care, and (11) The political agenda. The ultimate goal is to propose ARIA 2024 guidelines centered around the patient to make them more applicable and sustainable.
- Klíčová slova
- ARIA, Artificial intelligence, Asthma, Evidence-based medicine, Person-centered care, Rhinitis, mHealth,
- MeSH
- alergická rýma * terapie MeSH
- bronchiální astma * terapie MeSH
- kritické cesty MeSH
- lidé MeSH
- péče orientovaná na pacienta * MeSH
- směrnice pro lékařskou praxi jako téma MeSH
- telemedicína * MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
Biomarkers for the diagnosis, treatment and follow-up of patients with rhinitis and/or asthma are urgently needed. Although some biologic biomarkers exist in specialist care for asthma, they cannot be largely used in primary care. There are no validated biomarkers in rhinitis or allergen immunotherapy (AIT) that can be used in clinical practice. The digital transformation of health and health care (including mHealth) places the patient at the center of the health system and is likely to optimize the practice of allergy. Allergic Rhinitis and its Impact on Asthma (ARIA) and EAACI (European Academy of Allergy and Clinical Immunology) developed a Task Force aimed at proposing patient-reported outcome measures (PROMs) as digital biomarkers that can be easily used for different purposes in rhinitis and asthma. It first defined control digital biomarkers that should make a bridge between clinical practice, randomized controlled trials, observational real-life studies and allergen challenges. Using the MASK-air app as a model, a daily electronic combined symptom-medication score for allergic diseases (CSMS) or for asthma (e-DASTHMA), combined with a monthly control questionnaire, was embedded in a strategy similar to the diabetes approach for disease control. To mimic real-life, it secondly proposed quality-of-life digital biomarkers including daily EQ-5D visual analogue scales and the bi-weekly RhinAsthma Patient Perspective (RAAP). The potential implications for the management of allergic respiratory diseases were proposed.
- Klíčová slova
- ARIA, EAACI, apps, digital health, rhinitis,
- MeSH
- alergická rýma * diagnóza terapie MeSH
- biologické markery MeSH
- bronchiální astma * diagnóza terapie MeSH
- lidé MeSH
- péče orientovaná na pacienta MeSH
- poruchy dýchání * MeSH
- rinitida * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
- Názvy látek
- biologické markery MeSH
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.
- Klíčová slova
- mobile health, patient-reported outcomes, real-world data, rhinitis,
- MeSH
- lidé MeSH
- longitudinální studie MeSH
- průzkumy a dotazníky MeSH
- rinitida * epidemiologie MeSH
- telemedicína * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: In clinical and epidemiological studies, cutoffs of patient-reported outcome measures can be used to classify patients into groups of statistical and clinical relevance. However, visual analog scale (VAS) cutoffs in MASK-air have not been tested. OBJECTIVE: To calculate cutoffs for VAS global, nasal, ocular, and asthma symptoms. METHODS: In a cross-sectional study design of all MASK-air participants, we compared (1) approaches based on the percentiles (tertiles or quartiles) of VAS distributions and (2) data-driven approaches based on clusters of data from 2 comparators (VAS work and VAS sleep). We then performed sensitivity analyses for individual countries and for VAS levels corresponding to full allergy control. Finally, we tested the different approaches using MASK-air real-world cross-sectional and longitudinal data to assess the most relevant cutoffs. RESULTS: We assessed 395,223 days from 23,201 MASK-air users with self-reported allergic rhinitis. The percentile-oriented approach resulted in lower cutoff values than the data-driven approach. We obtained consistent results in the data-driven approach. Following the latter, the proposed cutoff differentiating "controlled" and "partly-controlled" patients was similar to the cutoff value that had been arbitrarily used (20/100). However, a lower cutoff was obtained to differentiate between "partly-controlled" and "uncontrolled" patients (35 vs the arbitrarily-used value of 50/100). CONCLUSIONS: Using a data-driven approach, we were able to define cutoff values for MASK-air VASs on allergy and asthma symptoms. This may allow for a better classification of patients with rhinitis and asthma according to different levels of control, supporting improved disease management.
- Klíčová slova
- Asthma, Conjunctivitis, Cutoffs, MASK-air, Rhinitis,
- MeSH
- alergická rýma * diagnóza MeSH
- bronchiální astma * epidemiologie terapie MeSH
- hodnocení výsledků péče pacientem MeSH
- lidé MeSH
- průřezové studie MeSH
- rinitida * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
MASK-air® , a validated mHealth app (Medical Device regulation Class IIa) has enabled large observational implementation studies in over 58,000 people with allergic rhinitis and/or asthma. It can help to address unmet patient needs in rhinitis and asthma care. MASK-air® is a Good Practice of DG Santé on digitally-enabled, patient-centred care. It is also a candidate Good Practice of OECD (Organisation for Economic Co-operation and Development). MASK-air® data has enabled novel phenotype discovery and characterisation, as well as novel insights into the management of allergic rhinitis. MASK-air® data show that most rhinitis patients (i) are not adherent and do not follow guidelines, (ii) use as-needed treatment, (iii) do not take medication when they are well, (iv) increase their treatment based on symptoms and (v) do not use the recommended treatment. The data also show that control (symptoms, work productivity, educational performance) is not always improved by medications. A combined symptom-medication score (ARIA-EAACI-CSMS) has been validated for clinical practice and trials. The implications of the novel MASK-air® results should lead to change management in rhinitis and asthma.
BACKGROUND: Different treatments exist for allergic rhinitis (AR), including pharmacotherapy and allergen immunotherapy (AIT), but they have not been compared using direct patient data (i.e., "real-world data"). We aimed to compare AR pharmacological treatments on (i) daily symptoms, (ii) frequency of use in co-medication, (iii) visual analogue scales (VASs) on allergy symptom control considering the minimal important difference (MID) and (iv) the effect of AIT. METHODS: We assessed the MASK-air® app data (May 2015-December 2020) by users self-reporting AR (16-90 years). We compared eight AR medication schemes on reported VAS of allergy symptoms, clustering data by the patient and controlling for confounding factors. We compared (i) allergy symptoms between patients with and without AIT and (ii) different drug classes used in co-medication. RESULTS: We analysed 269,837 days from 10,860 users. Most days (52.7%) involved medication use. Median VAS levels were significantly higher in co-medication than in monotherapy (including the fixed combination azelastine-fluticasone) schemes. In adjusted models, azelastine-fluticasone was associated with lower average VAS global allergy symptoms than all other medication schemes, while the contrary was observed for oral corticosteroids. AIT was associated with a decrease in allergy symptoms in some medication schemes. A difference larger than the MID compared to no treatment was observed for oral steroids. Azelastine-fluticasone was the drug class with the lowest chance of being used in co-medication (adjusted OR = 0.75; 95% CI = 0.71-0.80). CONCLUSION: Median VAS levels were higher in co-medication than in monotherapy. Patients with more severe symptoms report a higher treatment, which is currently not reflected in guidelines.
- Klíčová slova
- allergen immunotherapy, allergic rhinitis, co-medication, multivariable mixed-effects model, real-world data,
- MeSH
- alergická rýma * terapie MeSH
- desenzibilizace imunologická MeSH
- flutikason terapeutické užití MeSH
- hormony kůry nadledvin terapeutické užití MeSH
- lidé MeSH
- rinitida * farmakoterapie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- flutikason MeSH
- hormony kůry nadledvin MeSH
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.
- Klíčová slova
- Co-medication, MASK-air, allergic rhinitis, visual analogue scale,
- MeSH
- alergická rýma * farmakoterapie epidemiologie MeSH
- antihistaminika terapeutické užití MeSH
- lidé MeSH
- rinitida * farmakoterapie MeSH
- zvyky MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Evropa epidemiologie MeSH
- Názvy látek
- antihistaminika MeSH
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.
- Klíčová slova
- allergic rhinitis, immunotherapy, mobile health, patient-reported outcomes, real-life data analysis,
- Publikační typ
- časopisecké články MeSH
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.
- Klíčová slova
- COVID-19 vaccines, adrenaline, anaphylaxis, older (adults/people),
- MeSH
- adrenalin MeSH
- anafylaxe * etiologie prevence a kontrola MeSH
- COVID-19 * MeSH
- lidé MeSH
- SARS-CoV-2 MeSH
- senioři MeSH
- vakcíny proti COVID-19 MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- adrenalin MeSH
- vakcíny proti COVID-19 MeSH
