Allergy 2021

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

Sousa-Pinto B, Filipe Azevedo L, Jutel M, Agache I, Canonica GW, Czarlewsk W, Papadopoulos NG, Bergmann KC, Devillier P, Laune D, Klimek L, Anto A, Antó JM, Eklund P, Almeida R, Bedbrook A, Bosnic-Anticevich S, Brough HA, Brussino L, Cardona V, Casale T, Cecchi L, Charpin D, Chivato T, Costa EM, Cruz AA, Dramburg S, Durham SR, De Feo G, Gerth van Wijk R, Fokkens WJ, Gemicioglu B, Haahtela T, Illario M, Ivancevich JC, Kvedariene V, Kuna P, Larenas-Linnemann DE, Makris M, Mathieu-Dupas E, Melen E, Morais-Almeida M, Mosges R, Mullol J, Nadeau KC, Pham-Thi N, O'Hehir R, Regateiro FS, Reitsma S, Samolinski B, Sheikh A, Stellato C, Todo-Bom A, Tomazic PV, Toppila-Salmi S, Valero A, Valiulis A, Ventura MT, Wallace D, Waserman S, Yorgancioglu A, De Vries G, van Eerd M, Zieglmayer P, Zuberbier T, Pfaar O, Almeida Fonseca J, Bousquet J
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.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]).We assessed 317,176 days of MASK-air® use from 17,780 users aged between 16 and 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).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.This article is protected by copyright. All rights reserved.