Concurrent validity, cut-offs and ability to change of patient-reported outcome measures for rhinitis and asthma in MASK-air®.

Patient-reported outcome measures (PROMs) are used to assess a patient's health status at a particular point in time. They are essential in the development of person-centred care. This paper reviews studies performed on PROMs for assessing AR and asthma control, in particular VAS scales that are included in the app MASK-air® (Mobile Airways Sentinel networK) for asthma and rhinitis. VASs were initially developed on paper and pencil and tested for their criterion validity, cut-offs and responsiveness. Then, a multicentric, multinational, double-blind, placebo-controlled, randomised control trial (DB-PC-RCT) using an electronic VAS form was carried out. Finally, with the development of MASK-air® in 2015, previously validated VAS questions were adapted to the digital format and further methodologic evaluations were performed. VAS for asthma, rhinitis, conjunctivitis, work and EQ-5D are included in the app. Additionally, two control-medication scores for allergic symptoms of asthma (e-DASTHMA) were validated for their criterion validity, cut-offs and responsiveness.

Concepts for the Development of Person-Centered, 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 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.

Digitally-enabled, person-centred care (PCC) in allergen immunotherapy: An ARIA-EAACI Position Paper.

In rhinitis and asthma, several mHealth apps have been developed but only a few have been validated. However, these apps have a high potential for improving person-centred care (PCC), especially in allergen immunotherapy (AIT). They can provide support in AIT initiation by selecting the appropriate patient and allergen shared decision-making. They can also help in (i) the evaluation of (early) efficacy, (ii) early and late stopping rules and (iii) the evaluation of (carried-over) efficacy after cessation of the treatment course. Future perspectives have been formulated in the first report of a joint task force (TF)-Allergic Rhinitis and Its Impact on Asthma (ARIA) and the European Academy of Allergy and Clinical Immunology (EAACI)-on digital biomarkers. The TF on AIT now aims to (i) outline the potential of the clinical applications of mHealth solutions, (ii) express their current limitations, (iii) make proposals regarding further developments for both clinical practice and scientific purpose and (iv) suggest which of the tools might best comply with the purpose of digitally-enabled PCC in AIT.

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.

Impairment of EQ-5D-5L Domains According to Allergic Rhinitis and Asthma Control: A MASK-air Real-World Study.

BACKGROUND: EQ-5D-5L (EuroQOL, 5 Domains, 5 Levels) is a widely used health-related quality-of-life instrument, comprising 5 domains. However, it is not known how each domain is impacted by rhinitis or asthma control. OBJECTIVE: To assess the association between rhinitis or asthma control and the different EQ-5D-5L domains using data from the MASK-air mHealth app. METHODS: In this cross-sectional study, we assessed data from all MASK-air users (2015-2021; 24 countries). For the levels of each EQ-5D-5L domain, we assessed rhinitis and asthma visual analog scales (VASs) and the combined symptom-medication score (CSMS). We built ordinal multivariable models assessing the adjusted association between VAS/CSMS values and the levels of each EQ-5D-5L domain. Finally, we compared EQ-5D-5L data from users with rhinitis and self-reported asthma with data from users with rhinitis alone. RESULTS: We assessed 5354 days from 3092 users. We observed an association between worse control of rhinitis or asthma (higher VASs and CSMS) and worse EQ-5D-5L levels. In multivariable models, all VASs and the CSMS were associated with higher levels of pain/discomfort and daily activities. For anxiety/depression, the association was mostly observed for rhinitis-related tools (VAS nose, VAS global, and CSMS), although the presence of self-reported asthma was also associated with worse anxiety/depression. Worse mobility ("walking around") was particularly associated with VAS asthma and with the presence of asthma. CONCLUSIONS: A worse rhinitis control and a worse asthma control are associated with higher EQ-5D-5L levels, particularly regarding pain/discomfort and activity impairment. Worse rhinitis control is associated with worse anxiety/depression, and poor asthma control with worse mobility.

UCRAID (Ukrainian Citizen and refugee electronic support in Respiratory diseases, Allergy, Immunology and Dermatology) action plan.

Eight million Ukrainians have taken refuge in the European Union. Many have asthma and/or allergic rhinitis and/or urticaria, and around 100,000 may have a severe disease. Cultural and language barriers are a major obstacle to appropriate management. Two widely available mHealth apps, MASK-air® (Mobile Airways Sentinel NetworK) for the management of rhinitis and asthma and CRUSE® (Chronic Urticaria Self Evaluation) for patients with chronic spontaneous urticaria, were updated to include Ukrainian versions that make the documented information available to treating physicians in their own language. The Ukrainian patients fill in the questionnaires and daily symptom-medication scores for asthma, rhinitis (MASK-air) or urticaria (CRUSE) in Ukrainian. Then, following the GDPR, patients grant their physician access to the app by scanning a QR code displayed on the physician's computer enabling the physician to read the app contents in his/her own language. This service is available freely. It takes less than a minute to show patient data to the physician in the physician's web browser. UCRAID-developed by ARIA (Allergic Rhinitis and its Impact on Asthma) and UCARE (Urticaria Centers of Reference and Excellence)-is under the auspices of the Ukraine Ministry of Health as well as European (European Academy of Allergy and Clinical immunology, EAACI, European Respiratory Society, ERS, European Society of Dermatologic Research, ESDR) and national societies.

ARIA Care Pathways 2019: Next-Generation Allergic Rhinitis Care and Allergen Immunotherapy in Malaysia.

An increase in the prevalence of allergic rhinitis (AR) worldwide presents a significant burden to the health care system. An initiative was started in Europe designated as Allergic Rhinitis and Its Impact on Asthma (ARIA) to develop internationally applicable guidelines by utilising an evidence-based approach to address this crucial issue. The efforts are directed at empowerment of patients for self-management, the use of digital mobile technology to complement and personalise treatment, and establishment of real-life integrated care pathways (ICPs). This guideline includes aspects of patients' and health care providers' management and covers the main areas of treatment for AR. The model provides better real-life health care than the previous traditional models. This review summarises the ARIA next-generation guideline in the context of the Malaysian health care system.

Patient-centered digital biomarkers for allergic respiratory diseases and asthma: The ARIA-EAACI approach - ARIA-EAACI Task Force Report.

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.

Development and validation of an electronic daily control score for asthma (e-DASTHMA): a real-world direct patient data study.

BACKGROUND: Validated questionnaires are used to assess asthma control over the past 1-4 weeks from reporting. However, they do not adequately capture asthma control in patients with fluctuating symptoms. Using the Mobile Airways Sentinel Network for airway diseases (MASK-air) app, we developed and validated an electronic daily asthma control score (e-DASTHMA). METHODS: We used MASK-air data (freely available to users in 27 countries) to develop and assess different daily control scores for asthma. Data-driven control scores were developed based on asthma symptoms reported by a visual analogue scale (VAS) and self-reported asthma medication use. We included the daily monitoring data from all MASK-air users aged 16-90 years (or older than 13 years to 90 years in countries with a lower age of digital consent) who had used the app in at least 3 different calendar months and had reported at least 1 day of asthma medication use. For each score, we assessed construct validity, test-retest reliability, responsiveness, and accuracy. We used VASs on dyspnoea and work disturbance, EQ-5D-VAS, Control of Allergic Rhinitis and Asthma Test (CARAT), CARAT asthma, and Work Productivity and Activity Impairment: Allergy Specific (WPAI:AS) questionnaires as comparators. We performed an internal validation using MASK-air data from Jan 1 to Oct 12, 2022, and an external validation using a cohort of patients with physician-diagnosed asthma (the INSPIRERS cohort) who had had their diagnosis and control (Global Initiative for Asthma [GINA] classification) of asthma ascertained by a physician. FINDINGS: We studied 135 635 days of MASK-air data from 1662 users from May 21, 2015, to Dec 31, 2021. The scores were strongly correlated with VAS dyspnoea (Spearman correlation coefficient range 0·68-0·82) and moderately correlated with work comparators and quality-of-life-related comparators (for WPAI:AS work, we observed Spearman correlation coefficients of 0·59-0·68). They also displayed high test-retest reliability (intraclass correlation coefficients range 0·79-0·95) and moderate-to-high responsiveness (correlation coefficient range 0·69-0·79; effect size measures range 0·57-0·99 in the comparison with VAS dyspnoea). The best-performing score displayed a strong correlation with the effect of asthma on work and school activities in the INSPIRERS cohort (Spearman correlation coefficients 0·70; 95% CI 0·61-0·78) and good accuracy for the identification of patients with uncontrolled or partly controlled asthma according to GINA (area under the receiver operating curve 0·73; 95% CI 0·68-0·78). INTERPRETATION: e-DASTHMA is a good tool for the daily assessment of asthma control. This tool can be used as an endpoint in clinical trials as well as in clinical practice to assess fluctuations in asthma control and guide treatment optimisation. FUNDING: None.

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.

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.

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.

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.

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.

Available and affordable complementary treatments for COVID-19: From hypothesis to pilot studies and the need for implementation.

Vaccination is a highly effective preventive measure against COVID-19. However, complementary treatments are needed to better control the disease. Fermented vegetables and spices, agonists of the antioxidant transcription factor nuclear factor (erythroid-derived 2)-like 2 (Nrf2) and TRPA1/V1 channels (Transient Receptor Potential Ankyrin 1 and Vanillin 1), may help in the control of COVID-19. Some preliminary clinical trials suggest that curcumin (spice) can prevent some of the COVID-19 symptoms. Before any conclusion can be drawn and these treatments recommended for COVID-19, the data warrant confirmation. In particular, the benefits of the foods need to be assessed in more patients, through research studies and large trials employing a double-blind, placebo-controlled design.

Automatic market research of mobile health apps for the self-management of allergic rhinitis.

BACKGROUND: Only a small number of apps addressing allergic rhinitis (AR) patients have been evaluated. This makes their selection difficult. We aimed to introduce a new approach to market research for AR apps, based on the automatic screening of Apple App and Google Play stores. METHODS: A JavaScript programme was devised for automatic app screening, and applied in a market assessment of AR self-management apps. We searched the Google Play and Apple App stores of three countries (USA, UK and Australia) with the following search terms: "hay fever", "hayfever", "asthma", "rhinitis", "allergic rhinitis". Apps were eligible if symptoms were evaluated. Results obtained with the automatic programme were compared to those of a blinded manual search. As an example, we used the search to assess apps that can be used to design a combined medication score for AR. RESULTS: The automatic search programme identified 39 potentially eligible apps out of a total of 1593 retrieved apps. Each of the 39 apps was individually checked, with 20 being classified as relevant. The manual search identified 19 relevant apps (out of 6750 screened apps). Combining both methods, a total of 21 relevant apps were identified, pointing to a sensitivity of 95% and a specificity of 99% for the automatic method. Among these 21 apps, only two could be used for the combined symptom-medication score for AR. CONCLUSIONS: The programmed algorithm presented herein is able to continuously retrieve all relevant AR apps in the Apple App and Google Play stores, with high sensitivity and specificity. This approach has the potential to unveil the gaps and unmet needs of the apps developed so far.