PLOS digital health
A longitudinal analysis of real world symptom tracking and patient-reported outcomes in Brisa, a German Digital Health App for multiple sclerosis
By Stratil AS, Papukchieva S, Steinmetz-Späh J and 4 others.
Abstract
Brisa, a companion app designed for multiple sclerosis (MS) patients, can support the patient journey by collecting longitudinal real-world data. This study aimed to characterize the demographic and clinical profile of Brisa users and longitudinal trends in app engagement, self-reported symptoms and patient-reported outcomes (PROs). This retrospective analysis included Brisa users aged ≥18 years, reported use of category 1 (low), 2 (medium), or 3 (high efficacy) disease-modifying therapy (DMT) according to German DGN guidelines, and had no medication switching. Users diagnosed within 0-1 years were classified as newly diagnosed cases. App engagement was defined as any screen activity; disengagement was defined as >180 consecutive days without engagement and analysed using Cox proportional hazards regression. Symptoms were rated on a 1-5 emoticon-based scale (1 = poor, 5 = excellent). PROs included the MFIS, PDDS, PDQ-5, IVIS, and PES. Among 4,194 users, the majority were female (80.8%), aged 26-35 years (30.5%) and diagnosed with relapsing-remitting MS (77.4%), with 27.9% newly diagnosed. Consistent with a shift towards high-efficacy treatment, use of category 3 (high-efficacy) DMTs among newly diagnosed users significantly increased from 2023 to 2024/2025 (χ2, p < 0.0001). In engagement analyses, users receiving category 3 DMTs, those aged ≥36 years, and newly diagnosed users showed a significantly lower risk of disengagement compared with users on category 1 DMTs, aged 18-25 years or diagnosed ≥2 years prior. Overall, about 76.0% of users tracked at least one symptom or PRO. Longitudinally, among users with ≥1 year of tracking, symptom and PRO scores remained largely stable. A shift toward higher efficacy treatment in newly diagnosed users was observed, while symptom and PRO scores remained largely stable over time. These findings highlight the potential of digital health tools for tracking treatment patterns, patient engagement and self-reported symptom changes in MS.




