ReviewFrontiers in pharmacology2024
Advancements and prospects of novel biologicals for myasthenia gravis: toward personalized treatment based on autoantibody specificities.
Review in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Minimal Symptom Expression in Generalized Myasthenia Gravis: A Valuable Patient-Centric Treatment Goal.European journal of neurology · 2026Review
- The immune microenvironment and population heterogeneity in myasthenia gravis: implications for precision therapeutics.Frontiers in immunology · 2026Review
- Telitacicept as an alternative to non-steroidal immunosuppressive therapies in the treatment of myasthenia gravis: a study on clinical efficacy and steroid-sparing effect.Frontiers in immunology · 2025Article
- Ofatumumab-mediated CD20Frontiers in pharmacology · 2025Article
- Differential expression profiles of lncRNAs and a preliminary study on the mechanism of lncRNA FAM225A in triple seronegative myasthenia gravis.Frontiers in immunology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Myasthenia gravis (MG) is an antibody-mediated autoimmune disease with a prevalence of 150-250 cases per million individuals. Autoantibodies include long-lived antibodies against the acetylcholine receptor (AChR), mainly of the IgG1 subclass, and IgG4, produced almost exclusively by short-lived plasmablasts, which are prevalent in muscle-specific tyrosine kinase (MuSK) myasthenia gravis. Numerous investigations have demonstrated that MG patients receiving conventional medication today still do not possess satisfactory symptom control, indicating a substantial disease burden. Subsequently, based on the type of the autoantibody and the pathogenesis, we synthesized the published material to date and reached a conclusion regarding the literature related to personalized targeted therapy for MG. Novel agents for AChR MG have shown their efficacy in clinical research, such as complement inhibitors, FcRn receptor antagonists, and B-cell activating factor (BAFF) inhibitors. Rituximab, a representative drug of anti-CD20 therapy, has demonstrated benefits in treatment of MuSK MG patients. Due to the existence of low-affinity antibodies or unidentified antibodies that are inaccessible by existing methods, the treatment for seronegative MG remains complicated; thus, special testing and therapy considerations are necessary. It may be advantageous to initiate the application of novel biologicals at an early stage of the disease. Currently, therapies can also be combined and individualized according to different types of antibodies. With such a wide range of drugs, how to tailor treatment strategies to patients with various conditions and find the most suitable solution for each MG profile are our necessary and urgent aims.
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.