ArticleJournal of personalized medicine2022
Demographic Patterns of MS Patients Using BRISA: An MS-Specific App in Germany.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Exploring attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective.PLOS digital health · 2026Article
- Data on Ocrelizumab Treatment Collected by MS Patients in Germany Using Brisa App.Journal of personalized medicine · 2024Article
- Validated, Quantitative, Machine Learning-Generated Neurologic Assessment of Multiple Sclerosis Using a Mobile Application.International journal of MS careArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMultiple sclerosis (MS) is a chronic, progressive neurological autoimmune disease impacting quality of life. BRISA is an app designed to help MS patients in Germany track their disease course by symptom-monitoring. This study aimed to understand demographic and health-related characteristics of BRISA users.
methodsDemographic data provided by 2095 users were analyzed to describe characteristics such as sex, age, type of MS, and medication. The distribution of tracked symptoms based on age and time since diagnosis were studied. Furthermore, the covariance of specific symptom pairs was analyzed.
resultsBRISA users are predominantly female and between 26 and 55 years old. Relapsing-remitting MS was the most prevalent form of MS. First-line category 1 drugs were most frequently used, followed by high-efficacy category 3 drugs (e.g., monoclonal antibodies). The relative frequencies of use of category 1 and category 2 drugs (e.g., spingosine-1-phosphate-receptor modulators) significantly altered with time since diagnosis. Fatigue, concentration disorders, tingling, forgetfulness, and pain were the top five symptoms affecting users.
conclusionThe results highlight the diversity among MS patients and the need for extensive cohort characterization in the real-world scenario. In-depth analysis could help in identifying novel insights that could aid in disease management.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.