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

Abstract

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.

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

“…Bayesian mixed‐effects models—with clustering by patient, country and pollen season—were analysed (Figure 13 ). 94 …”

Molecular sensitization pattern to house dust mites is formed from the first years of life and includes group 1, 2, Der p 23, Der p 5, Der p 7 and Der p 21 allergens

“…To determine the probability of developing sensitization to certain molecular components in individual patient profiles, machine learning was used as it has been previously shown to have applications in the diagnostics of allergic diseases, in particular for children [ 20 ]. Thus, according to data on sensitization to HDM allergens in the study population, a Bayesian network was built, as a tool to determine the probability of developing processes related to the health of the population [ 21 ] useful for analyzing the data obtained from the eHealth system [ 22 ].…”

“…That is, if one of the three BN types (1)-( 3) is found in the table of data with three characteristics X, Y, Z, certain conclusions can be drawn about the probability of having one characteristic in a given object, depending on the probability of having other characteristics. This approach is usually used for finding causative-consecutive patterns [21][22][23][24][25]. Nevertheless, we suggest using it in a broader way.…”

Standardization of clinical outcomes used in allergen immunotherapy in allergic asthma: An EAACI position paper

“…120,121 This CSMS was shown to be more relevant in AIT than the classical VAS global allergy symptoms. 121,122 A similar score has been developed for asthma (Sousa-Pinto, in preparation). These scores have the potential to compare the daily control of the disease with pollen counts and pollution.…”