A Review of the Impact of Platform Therapies (DMTs) on Associated Clinical Symptoms of Multiple Sclerosis
Bibliographic record
Abstract
Santosh B Shirol,1 Kannan Subramaniam,2 Tjalf Ziemssen3 1Global Medical Affairs, Viatris, Bangalore, India; 2Global Medical Affairs, Viatris, Auckland, New Zealand; 3Center of Clinical Neuroscience, Neurological Clinic, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, GermanyCorrespondence: Santosh B Shirol, Global Medical Affairs, Viatris, 7-11th Floor, Kadubeesenahalli, Varthur ORR, Marathahalli, Bangalore, 560103, India, Tel +91 97311 66776, Email santoshbasavraj.shirol@viatris.comAbstract: Persons with multiple sclerosis (pwMS) experience varied symptoms, often influencing clinical decisions. Symptoms including cognitive deficits, pain, fatigue, and depression profoundly impact quality of life (QoL). Disease-modifying therapies (DMTs) primarily focus on reducing relapses and delaying progression; however, their ability to alleviate symptoms is less known. This narrative review consolidates the current evidence of the role of platform DMTs (Glatiramer Acetate (GA), Interferon (IFN), Dimethyl Fumarate (DMF), Teriflunomide (TER)) on the associated symptoms of MS and their efficacy in prevention of relapse, and disease progression. A literature search was conducted using the PubMed database for studies assessing the impact of GA and other platform DMTs on associated symptoms and effectiveness in pwMS. Studies using specific validated scales to assess each of the symptoms in pwMS treated with platform therapies were considered. A total of 132 publications were identified, and of which 13 were found appropriate for inclusion in the review. Effectiveness outcomes included annual relapse/exacerbation rates and lesion size. The impact of platform DMTs was evaluated in 13 studies in patients with MS having associated symptoms such as cognitive deficits (n=4), pain and spasticity (n=3), and fatigue, depression and overall QoL (n=6). Additionally, eight studies assessed the overall effectiveness of GA in the treatment and management of pwMS. Although a limited number of studies compared the impact of platform therapies on MS-related symptoms, treatment with GA demonstrated statistically significant improvements in cognition, pain, spasticity and fatigue, which was also clinically meaningful on minimum detectable change parameters. This review offers insights and proposes a hypothesis for conducting a large-scale study to explore the impact of platform therapies on MS symptoms that affect quality of life. It may also aid clinicians in making evidence-based therapeutic decisions for the effective management of PwMS.Keywords: disease-modifying therapies, glatiramer acetate, interferons, persons with multiple sclerosis, quality of life
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".