Heterogeneous validity of daily data on symptoms of seasonal allergic rhinitis recorded by patients using the e‐diary AllergyMonitor®

Abstract

Abstract Background Patient‐generated symptom and medication scores are essential for diagnostic and therapeutic decisions in seasonal allergic rhinitis (SAR). Previous studies have shown solid consistencies between different scores at population level in real‐life data and trials. For clinicians, the evaluation of individual data quality over time is essential to decide whether to rely on these data in clinical decision‐making. Objective To analyze the consistency of different symptom (SS) and symptom medication scores (SMSs) at individual level in two study cohorts with different characteristics and explore individual patient trajectories over time. Methods Within the pilot phase of the @IT.2020 project on diagnostic synergy of mobile health and molecular IgE assessment in patients with SAR, we analyzed data of 101 children and 93 adults with SAR and instructed them to record their symptoms and medication intake daily via the mobile app AllergyMonitor®. We then assessed the correlation between different SMS and a visual analogue scale (VAS) on the impact of allergy symptoms on daily life at population and individual level. Results At population level, the Rhinoconjunctivitis total symptom score (RTSS) correlated better with VAS than the combined symptom and medication score (CSMS). At individual level, consistency among RTSS and VAS was highly heterogeneous and unrelated to disease severity or adherence to recording. Similar heterogeneity was observed for CSMS and VAS. Conclusions The correlation of clinical information provided by different disease severity scores based on data collected via electronic diaries (e‐diaries), is sufficient at population level, but broadly heterogeneous for individual patients. Consistency of the recorded data must be examined for each patient before remotely collected information is used for clinical decision making.

Keywords

• allergic rhinitis
• mHealth
• patient‐generated data
• patient‐reported outcomes
• symptom scores