Concepts for the development of person-centred, digitally-enabled, Artificial Intelligence-assisted ARIA care pathways (ARIA 2024).

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 life based on their lived experiences. Improving healthcare safety, quality and coordination, as well as quality of life, are important aims in the care of patients with chronic conditions. Person-centred care needs to ensure that people's values and preferences guide clinical decisions. This paper reviews current knowledge to develop (i) digital care pathways for rhinitis and asthma multimorbidity and (ii) digitally-enabled person-centred care (1). It combines all relevant research evidence, including the so-called real-world evidence, with the ultimate goal to develop digitally-enabled, patient-centred care. The paper includes (i) Allergic Rhinitis and its Impact on Asthma (ARIA), a two-decade journey, (ii) Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, (iii) mHealth impact on airway diseases, (iv) from guidelines to digital care pathways, (v) embedding Planetary Health, (vi) novel classification of rhinitis and asthma, (vi) embedding real-life data with population-based studies, (vii) the ARIA-EAACI strategy for the management of airway diseases using digital biomarkers, (viii) Artificial Intelligence, (ix) the development of digitally-enabled ARIA Person-Centred Care and (x) the political agenda. The ultimate goal is to propose ARIA 2024 guidelines centred around the patient in order to make them more applicable and sustainable.

Pediatric asthma comorbidities: Global impact and unmet needs.

Real-world data on the range and impact of comorbid health conditions that affect pediatric asthma are scant, especially from developing countries. Lack of data hinders effective diagnosis, treatment, and overall management of these complex cases. We, hereby, describe the common pediatric asthma comorbid conditions in terms of evidence for association, potential mechanisms of impact on asthma control, and treatment benefit. Obesity, upper airway allergies, dysfunctional breathing, multiple sensitizations, depressive disorders, food allergy, and gastro-esophageal reflux are common associations with difficult-to-treat asthma. On the other hand, asthma symptoms and/or management may negatively impact the well-being of children through drug adverse effects, worsening of anaphylaxis symptoms, and disturbing mental health. Awareness of these ailments may be crucial for designing the optimum care for each asthmatic child individually and may ultimately improve the quality of life of patients and their families. A multidisciplinary team of physicians is required to identify and manage such comorbidities aiming to mitigate the over-use of asthma pharmacotherapy. Asthma research should target relevant real-world difficulties encountered at clinical practice and focus on interventions that would mitigate the impact of such comorbidities. Finally, policymakers and global healthcare organizations are urged to recognize pediatric asthma control as a healthcare priority and allocate resources for research and clinical interventions. In other words, global asthma control needs support by compassionate scientific partnership.

Relevance of individual bronchial symptoms for asthma diagnosis and control in patients with rhinitis: A MASK-air study.

RATIONALE: It is unclear how each individual asthma symptom is associated with asthma diagnosis or control. OBJECTIVES: To assess the performance of individual asthma symptoms in the identification of patients with asthma and their association with asthma control. METHODS: In this cross-sectional study, we assessed real-world data using the MASK-air® app. We compared the frequency of occurrence of five asthma symptoms (dyspnea, wheezing, chest tightness, fatigue and night symptoms, as assessed by the Control of Allergic Rhinitis and Asthma Test [CARAT] questionnaire) in patients with probable, possible or no current asthma. We calculated the sensitivity, specificity and predictive values of each symptom, and assessed the association between each symptom and asthma control (measured using the e-DASTHMA score). Results were validated in a sample of patients with a physician-established diagnosis of asthma. MEASUREMENT AND MAIN RESULTS: We included 951 patients (2153 CARAT assessments), with 468 having probable asthma, 166 possible asthma and 317 no evidence of asthma. Wheezing displayed the highest specificity (90.5%) and positive predictive value (90.8%). In patients with probable asthma, dyspnea and chest tightness were more strongly associated with asthma control than other symptoms. Dyspnea was the symptom with the highest sensitivity (76.1%) and the one consistently associated with the control of asthma as assessed by e-DASTHMA. Consistent results were observed when assessing patients with a physician-made diagnosis of asthma. CONCLUSIONS: Wheezing and chest tightness were the asthma symptoms with the highest specificity for asthma diagnosis, while dyspnea displayed the highest sensitivity and strongest association with asthma control.

Poor Rhinitis and Asthma Control Is Associated With Decreased Health-Related Quality of Life and Utilities: A MASK-air Study.

BACKGROUND: Allergic rhinitis (AR) and asthma may affect health-related quality of life. However, national estimates on the quality of life of patients with AR or asthma are lacking. OBJECTIVE: To provide estimates for utility scores and EuroQoL five-dimension (EQ-5D) visual analog scale (VAS) for patients with AR or asthma. METHODS: We conducted a cross-sectional study using direct patient data from the MASK-air app on European MASK-air users with self-reported AR or asthma. We used a multi-attribute instrument (EQ-5D) to measure quality of life (as utility scores and EQ-5D VAS values). Mean scores were calculated per country and disease control level using multilevel regression models with poststratification, accounting for age and sex biases. RESULTS: We assessed data from 7905 MASK-air users reporting a total of up to 82,737 days. For AR, utilities ranged from 0.86 to 0.99 for good control versus 0.72 to 0.85 for poor control; EQ-5D VAS levels ranged from 78.9 to 87.9 for good control versus 55.3 to 64.2 for poor control. For asthma, utilities ranged from 0.84 to 0.97 for good control versus 0.73 to 0.87 for poor control; EQ-5D VAS levels ranged from 68.4 to 81.5 for good control versus 51.4 to 64.2 for poor control. Poor disease control was associated with a mean loss of 0.14 utilities for both AR and asthma. For the same control levels, AR and asthma were associated with similar utilities and EQ-5D VAS levels. However, lower values were observed for asthma plus AR compared with AR alone. CONCLUSIONS: Poor AR or asthma control are associated with reduced quality of life. The estimates obtained from mobile health data may provide valuable insights for health technology assessment studies.

Recommendations for asthma monitoring in children: A PeARL document endorsed by APAPARI, EAACI, INTERASMA, REG, and WAO.

Monitoring is a major component of asthma management in children. Regular monitoring allows for diagnosis confirmation, treatment optimization, and natural history review. Numerous factors that may affect disease activity and patient well-being need to be monitored: response and adherence to treatment, disease control, disease progression, comorbidities, quality of life, medication side-effects, allergen and irritant exposures, diet and more. However, the prioritization of such factors and the selection of relevant assessment tools is an unmet need. Furthermore, rapidly developing technologies promise new opportunities for closer, or even "real-time," monitoring between visits. Following an approach that included needs assessment, evidence appraisal, and Delphi consensus, the PeARL Think Tank, in collaboration with major international professional and patient organizations, has developed a set of 24 recommendations on pediatric asthma monitoring, to support healthcare professionals in decision-making and care pathway design.

Updated grading system for systemic allergic reactions: Joint Statement of the World Allergy Organization Anaphylaxis Committee and Allergen Immunotherapy Committee.

There is a lack of consensus over the description and severity assignment of allergic adverse reactions to immunotherapy, although there seems to be a consensus at least in terms of using the World Allergy Organization (WAO) grading systems to describe local adverse events for Sublingual Immunotherapy (SLIT) and Systemic Allergic Reactions (SARs) to Subcutaneous Immunotherapy (SCIT) amongst the major national/regional allergy societies. In this manuscript, we propose a modification of the previous WAO Grading system for SARs, which aligns with the newly-proposed Consortium for Food Allergy Research (CoFAR) Grading Scale for Systemic Allergic Reactions in Food Allergy (version 3.0). We hope this can facilitate a unified grading system appropriate to SARs due to allergen immunotherapy, independent of allergen and route of administration, and across clinical and research practice.

Asthma and rhinitis control in adolescents and young adults: A real-world MASK-air study.

BACKGROUND: In allergic rhinitis and asthma, adolescents and young adult patients are likely to differ from older patients. We compared adolescents, young adults and adults on symptoms, control levels, and medication adherence. METHODS: In a cross-sectional study (2015-2022), we assessed European users of the MASK-air mHealth app of three age groups: adolescents (13-18 years), young adults (18-26 years), and adults (>26 years). We compared them on their reported rhinitis and asthma symptoms, use and adherence to rhinitis and asthma treatment and app adherence. Allergy symptoms and control were assessed by means of visual analogue scales (VASs) on rhinitis or asthma, the combined symptom-medication score (CSMS), and the electronic daily control score for asthma (e-DASTHMA). We built multivariable regression models to compare symptoms or medication accounting for potential differences in demographic characteristics and baseline severity. RESULTS: We assessed 965 adolescent users (15,252 days), 4595 young adults (58,161 days), and 15,154 adult users (258,796 days). Users of all three age groups displayed similar app adherence. In multivariable models, age groups were not found to significantly differ in their adherence to rhinitis or asthma medication. These models also found that adolescents reported lower VAS on global allergy, ocular, and asthma symptoms (as well as lower CSMS) than young adults and adults. CONCLUSIONS: Adolescents reported a better rhinitis and asthma control than young adults and adults, even though similar medication adherence levels were observed across age groups. These results pave the way for future studies on understanding how adolescents control their allergic diseases.

Unanswered questions on the use of biologics in pediatric asthma.

The emergence of biologic therapies for the management of asthma has been a revolutionary change in our capacity to manage this disease. Since the launch of omalizumab, several other biologics have been marketed or are close to being marketed, suggesting that a plethora of monoclonal antibodies can be expected in the coming years. This will facilitate the transition to the paradigm of personalized medicine, but on the other hand will decisively further complicate the choice of the most appropriate treatment, in the absence of reliable enough biological markers. For these reasons, along with the relatively short time of use with these treatments, there are recurrently arising questions for which there are not even moderately documented answers, and for which the only solution must be based, with all reservations, on the combination of indirect evidence and expertise. In this paper, we attempt to address such questions, providing relevant commentaries and considering the whole width of the evidence base.

Utility of biomarkers in the diagnosis and monitoring of asthmatic children.

Asthma imposes a heavy morbidity burden during childhood; it affects over 10% of children in Europe and North America and it is estimated to exceed 400 million people worldwide by the year 2025. In clinical practice, diagnosis of asthma in children is mostly based on clinical criteria; nevertheless, assessment of both physiological and pathological processes through biomarkers, support asthma diagnosis, aid monitoring, and further lead to better treatment outcomes and reduced morbidity. Recently, identification and validation of biomarkers in pediatric asthma has emerged as a top priority across leading experts, researchers, and clinicians. Moreover, the implementation of non-invasive biomarkers for the assessment and monitoring of paediatric patients with asthma, has been prioritized; however, only a proportion of them are currently included in the clinical practise. Although, the use of non-invasive biomarkers is highly supported in recent asthma guidelines for documenting diagnosis and supporting monitoring of asthmatic patients, data on the Pediatric population are limited. In the present report, the Pediatric Asthma Committee of the World Allergy Organization (WAO), aims to summarize and discuss available data for the implementation of non-invasive biomarkers in the diagnosis and monitoring in children with asthma. Information on the most studied biomarkers, including spirometry, oscillometry, markers of allergic sensitization, fractional exhaled nitric oxide, and the most recent exhaled breath markers and "omic" approaches, will be reviewed. Practical limitations and considerations based on both experts' opinion and critical review of the literature, on the utility of all "well-known" and newly introduced non-invasive biomarkers will be presented. A critical commentary on biomarkers' use in diagnosing and monitoring asthma during the COVID-19 pandemic, cost and availability of biomarkers in different settings and in developing countries, the differences on the biomarkers use between Primary Practitioners, Pediatricians, and Specialists and their role on the longitudinal aspect of asthma is provided.

Digitally-enabled, patient-centred care in rhinitis and asthma multimorbidity: The ARIA-MASK-air® approach.

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.

Cutoff Values of MASK-air Patient-Reported Outcome Measures.

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.

Consistent trajectories of rhinitis control and treatment in 16,177 weeks: The MASK-air® longitudinal study.

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.

Real-world data using mHealth apps in rhinitis, rhinosinusitis and their multimorbidities.

Digital health is an umbrella term which encompasses eHealth and benefits from areas such as advanced computer sciences. eHealth includes mHealth apps, which offer the potential to redesign aspects of healthcare delivery. The capacity of apps to collect large amounts of longitudinal, real-time, real-world data enables the progression of biomedical knowledge. Apps for rhinitis and rhinosinusitis were searched for in the Google Play and Apple App stores, via an automatic market research tool recently developed using JavaScript. Over 1500 apps for allergic rhinitis and rhinosinusitis were identified, some dealing with multimorbidity. However, only six apps for rhinitis (AirRater, AllergyMonitor, AllerSearch, Husteblume, MASK-air and Pollen App) and one for rhinosinusitis (Galenus Health) have so far published results in the scientific literature. These apps were reviewed for their validation, discovery of novel allergy phenotypes, optimisation of identifying the pollen season, novel approaches in diagnosis and management (pharmacotherapy and allergen immunotherapy) as well as adherence to treatment. Published evidence demonstrates the potential of mobile health apps to advance in the characterisation, diagnosis and management of rhinitis and rhinosinusitis patients.

The Allergic Rhinitis and Its Impact on Asthma (ARIA) Approach of Value-Added Medicines: As-Needed Treatment in Allergic Rhinitis.

Drug repurposing is a major field of value-added medicine. It involves investigating and evaluating existing drugs for new therapeutic purposes that address unmet healthcare needs. Several unmet needs in allergic rhinitis could be improved by drug repurposing. This could be game-changing for disease management. Current medications for allergic rhinitis are centered on continuous long-term treatment, and medication registration is based on randomized controlled trials carried out for a minimum of 14 days with adherence of 70% or greater. A new way of treating allergic rhinitis is to propose as-needed treatment depending on symptoms, rather than classical continuous treatment. This rostrum will discuss existing clinical trials on as-needed treatment for allergic rhinitis and real-world data obtained by the mobile health app MASK-air, which focuses on digitally-enabled, patient-centered care pathways.

Academic Productivity of Young People With Allergic Rhinitis: A MASK-air Study.

BACKGROUND: Several studies have suggested an impact of allergic rhinitis on academic productivity. However, large studies with real-world data (RWD) are not available. OBJECTIVE: To use RWD to assess the impact of allergic rhinitis on academic performance (measured through a visual analog scale [VAS] education and the Work Productivity and Activity Impairment Questionnaire plus Classroom Impairment Questions: Allergy Specific [WPAI+CIQ:AS] questionnaire), and to identify factors associated with the impact of allergic rhinitis on academic performance. METHODS: We assessed data from the MASK-air mHealth app of users aged 13 to 29 years with allergic rhinitis. We assessed the correlation between variables measuring the impact of allergies on academic performance (VAS education, WPAI+CIQ:AS impact of allergy symptoms on academic performance, and WPAI+CIQ:AS percentage of education hours lost due to allergies) and other variables. In addition, we identified factors associated with the impact of allergic symptoms on academic productivity through multivariable mixed models. RESULTS: A total of 13,454 days (from 1970 patients) were studied. VAS education was strongly correlated with the WPAI+CIQ:AS impact of allergy symptoms on academic productivity (Spearman correlation coefficient = 0.71 [95% confidence interval (CI) = 0.58; 0.80]), VAS global allergy symptoms (0.70 [95% CI = 0.68; 0.71]), and VAS nose (0.66 [95% CI = 0.65; 0.68]). In multivariable regression models, immunotherapy showed a strong negative association with VAS education (regression coefficient = -2.32 [95% CI = -4.04; -0.59]). Poor rhinitis control, measured by the combined symptom-medication score, was associated with worse VAS education (regression coefficient = 0.88 [95% CI = 0.88; 0.92]), higher impact on academic productivity (regression coefficient = 0.69 [95% CI = 0.49; 0.90]), and higher percentage of missed education hours due to allergy (regression coefficient = 0.44 [95% CI = 0.25; 0.63]). CONCLUSION: Allergy symptoms and worse rhinitis control are associated with worse academic productivity, whereas immunotherapy is associated with higher productivity.

Economic burden of drug-induced anaphylaxis: what can we do better?

PURPOSE OF REVIEW: This systematic review evaluates published data related to the economic burden of drug-induced anaphylaxis (DIA) to understand preventive cost saving measures that could reduce the burden of these conditions. RECENT FINDINGS: Although DIA has a relevant societal impact, there are limited and heterogenous available data related to its cost. Direct costs related to the management of acute phase of DIA was estimated by $529.6 to $3125, depending on the number of emergency room visits/hospitalizations, emergency kits and transports in ambulance. Direct costs of investigations of DIA varied from $288 to $2292.95 and the desensitization was estimated by $6796. Main variables for this were: personnel, allergy screening procedures, medical consumables and space cost. The mean indirect cost was based on a mean absenteeism of 3 days per DIA corresponding to $381.2. SUMMARY: More than reviewing the published data, we were able to identify variables that, if correctly managed, can reduce the economic burden of DIA, such as adjusting the timing of referral and etiological diagnosis, identification of potential risk and/or co-factors, correct written recommendations to patients. The evidence presented highlights the need of optimization of healthcare patients to patients suffering from DIA.

Comparison of rhinitis treatments using MASK-air® data and considering the minimal important difference.

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.