ArticleTherapeutic advances in neurological disorders2021
An algorithm using clinical data to predict the optimal individual glucocorticoid dosage to treat multiple sclerosis relapses.
Article in Therapeutic advances in neurological disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Multiple sclerosis: Immunopathological heterogeneity and its implications.European journal of immunology · 2022Review
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlucocorticoid (GC) pulse therapy is used for multiple sclerosis (MS) relapse treatment; however, GC resistance is a common problem. Considering that GC dosing is individual with several response-influencing factors, establishing a predictive model, which supports clinicians to estimate the maximum GC dose above which no additional therapeutic value can be expected presents a huge clinical need.
methodWe established two, independent retrospective cohorts of MS patients. The first was an explorative cohort for model generation, while the second was established for its validation. Using the explorative cohort, a multivariate regression analysis with the GC dose used as the dependent variable and serum vitamin D (25D) concentration, sex, age, EDSS, contrast enhancement on cranial magnetic resonance imaging (MRI), immune therapy, and the involvement of the optic nerve as independent variables was established.
resultsIn the explorative cohort, 113 MS patients were included. 25-hydroxyvitamin D (25D) serum concentration and the presence of optic neuritis were independent predictors of the GC dose needed to treat MS relapses [(25D): -25.95 (95% confidence interval (CI)): -47.40 to -4.49;
conclusionOur model could predict the GC dose given in clinical, routine MS relapse care, above which clinicians estimate no further benefit. Further studies should validate and improve our algorithm to help the implementation of predictive models in GC dosing.
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