The minimal clinically important difference of app-based electronic patient-reported outcomes for hay fever

BackgroundHay fever is a common allergic disease, with an estimated worldwide prevalence of 14.4% and a variety of symptoms. This study assessed the minimal clinically important difference (MCID) of nasal symptom score (NSS), non-nasal symptom score (NNSS), and total symptoms score (TSS) for app-based hay-fever monitoring. MethodsMCIDs were calculated based on the data from a previous large-scale, crowdsourced, cross-sectional study using AllerSearch, an in-house smartphone application. MCIDs were determined with anchor-based and distribution-based methods. The face scale score of the Japanese Allergic Conjunctival Disease Standard Quality of Life Questionnaire Domain III and the daily stress level due to hay fever were used as anchors for determining MCIDs. The MCID estimates were summarized as MCID ranges. ResultsA total of 7590 participants were included in the analysis (mean age: 35.3 years, 57.1% women). The anchor-based method produced a range of MCID values (median, interquartile range) for NSS (2.0, 1.5-2.1), NNSS (1.0, 0.9-1.2), and TSS (2.9, 2.4-3.3). The distribution-based method produced two MCIDs (based on half a standard deviation, based on a standard error of measurement) for NSS (2.0, 1.8), NNSS (1.3, 1.2), and TSS (3.0, 2.3). The final suggested MCID ranges for NSS, NNSS, and TSS were 1.8-2.1, 1.2-1.3, and 2.4-3.3, respectively. ConclusionsMCID ranges for app-based hay-fever symptom assessment were obtained from the data collected through a smartphone application, AllerSearch. These estimates may be useful for monitoring the subjective symptoms of Japanese patients with hay fever through mobile platforms.

Automated summary

This study assessed the minimal clinically important difference (MCID) of nasal symptom score (NSS), non-nasal symptom score (NNSS), and total symptoms score (TSS) for app-based hay-fever monitoring, and obtained the MCID ranges from the data collected through a smartphone application. These estimates may be useful for monitoring the subjective symptoms of Japanese patients with hay fever through mobile platforms.