Evidence mapPaperPMID 42397473Full record

ArticleNeurology and therapy2026

Polypharmacy, Potential Drug-Drug Interactions and Medication Non-Adherence in Patients with Multiple Sclerosis: A Longitudinal Study.

Avinash M Suntah, Michael Hecker, Bassel Barhoum, Jonas E Langenberger, Julia Baldt, Barbara Streckenbach, Jörg Richter, Niklas Frahm, Felicita Heidler, Uwe K Zettl

Abstract read
PubMed Publisher
In one paragraph

Article in Neurology and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Avinash M SuntahNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany. avinash.suntah@uni-rostock.de.ORCID http://orcid.org/0009-0008-3800-5348
Michael HeckerNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.ORCID http://orcid.org/0000-0001-7015-3094
Bassel BarhoumNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.ORCID http://orcid.org/0009-0001-0864-181X
Jonas E LangenbergerNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.
Julia BaldtNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.
Barbara StreckenbachNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.
Jörg RichterFaculty of Health Sciences, University of Hull, Hull, UK.
Niklas FrahmNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.ORCID http://orcid.org/0000-0002-4655-774X
Felicita HeidlerDepartment of Neurology, Ecumenic Hainich Hospital gGmbH, Mühlhausen, Germany.ORCID http://orcid.org/0000-0001-7948-958X
Uwe K ZettlNeuroimmunology Section, Department of Neurology, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMultiple sclerosis (MS) is a chronic neuroinflammatory disease affecting approximately 2.9 million people worldwide. Disease-modifying therapies for MS effectively lower the risk of relapses and delay disability progression, but the increasing medication burden and ongoing adherence challenges complicate disease management. An improved understanding of predictors of medication-related risks is essential to optimize long-term safety, treatment effectiveness, and quality of life in patients with MS.

methodsIn this longitudinal observational study, 206 adults with MS or clinically isolated syndrome were enrolled, of whom 175 completed the 5-year follow-up assessment. Sociodemographic, clinical, and comprehensive medication data were collected at baseline and follow-up through structured interviews and review of medical records. Polypharmacy was defined as the concurrent use of ≥ 5 medications. Potential drug-drug interactions (pDDIs) were systematically identified using the DrugBank database, and medication non-adherence was defined based on patient self-reported missed medication.

resultsOver the 5-year follow-up period, the prevalence of polypharmacy increased from 53.1% to 62.3% (p = 0.024), and pDDI exposure rose from 67.4% to 81.1% (p < 0.001), mainly driven by the greater use of drugs for comorbid conditions and dietary supplements. In contrast, monthly medication non-adherence remained stable (25.7% to 27.3%, p = 0.855). Major interactions accounted for 7.1% of all identified pDDIs. Older age, disability pension status, higher disability levels, coexisting medical conditions, and lower educational attainment were associated with polypharmacy and the presence of pDDIs, whereas non-adherence was linked to prior non-adherent behavior and inpatient care at baseline.

conclusionOver time, the prevalence of polypharmacy and pDDIs increased in patients with MS, whereas medication non-adherence emerged as a largely independent risk domain. Polypharmacy and the presence of pDDIs were mainly associated with aging- and disability-related factors, whereas medication non-adherence was more difficult to predict. Our findings emphasize the need for regular medication monitoring that considers both prescribed and non-prescribed drugs, alongside individualized adherence support to mitigate distinct medication-related risks in long-term MS care.

Indexed as

Drug–drug interactionsMedication non-adherenceMultiple sclerosisPolypharmacy

Identifiers

PMID42397473

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.