Insights into the classification of myasthenia gravis

Tetsuya Akaishi, Takuhiro Yamaguchi, Yasushi Suzuki, Yuriko Nagane, Shigeaki Suzuki, Hiroyuki Murai, Tomihiro Imai, Masakatsu Motomura, Kazuo Fujihara, Masashi Aoki, Kimiaki Utsugisawa

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Background and Purpose: Myasthenia gravis (MG) is often categorized into thymoma-associated MG, early-onset MG with onset age <50 years, and late-onset MG with onset age ≥50 years. However, the boundary age of 50 years old between early- and late-onset MG remains controversial, and each category contains further subtypes. We attempted to classify MG from a statistical perspective. Methods: We analyzed 640 consecutive MG patients using two-step cluster analysis with clinical variables and discrimination analysis, using onset age as a variable. Results: Two-step cluster analyses categorized MG patients into the following five subtypes: ocular MG; MG with thymic hyperplasia (THMG); generalized anti-acetylcholine receptor antibody (AChR-Ab)-negative MG; thymoma-associated MG; and generalized AChR-Ab-positive (SP) MG without thymic abnormalities. Among these 5 subtypes, THMG showed a distribution of onset age skewed toward a younger age (p<0.01), whereas ocular MG and SPMG without thymic abnormalities showed onset age skewed toward an older age (p<0.001 and p<0.0001, respectively). The other 2 subtypes showed normal distributions. THMG appeared as the main component of early-onset MG, and ocular MG and SPMG without thymic abnormalities as the main components of late-onset MG. Discrimination analyses between THMG and ocular MG and/or SPMG without thymic abnormalities demonstrated a boundary age of 45 years old. Conclusions: From a statistical perspective, the boundary age between early- and late-onset MG is about 45 years old.

Original languageEnglish
Article numbere106757
JournalPloS one
Volume9
Issue number9
DOIs
Publication statusPublished - Sep 5 2014

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Myasthenia Gravis
Cholinergic Receptors
Antibodies
Cluster analysis
Normal distribution
eyes
thymoma
Age of Onset
cholinergic receptors
Thymoma
antibodies
hyperplasia
Cluster Analysis
cluster analysis
Thymus Hyperplasia
Normal Distribution
Age Distribution

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Akaishi, T., Yamaguchi, T., Suzuki, Y., Nagane, Y., Suzuki, S., Murai, H., ... Utsugisawa, K. (2014). Insights into the classification of myasthenia gravis. PloS one, 9(9), [e106757]. https://doi.org/10.1371/journal.pone.0106757

Insights into the classification of myasthenia gravis. / Akaishi, Tetsuya; Yamaguchi, Takuhiro; Suzuki, Yasushi; Nagane, Yuriko; Suzuki, Shigeaki; Murai, Hiroyuki; Imai, Tomihiro; Motomura, Masakatsu; Fujihara, Kazuo; Aoki, Masashi; Utsugisawa, Kimiaki.

In: PloS one, Vol. 9, No. 9, e106757, 05.09.2014.

Research output: Contribution to journalArticle

Akaishi, T, Yamaguchi, T, Suzuki, Y, Nagane, Y, Suzuki, S, Murai, H, Imai, T, Motomura, M, Fujihara, K, Aoki, M & Utsugisawa, K 2014, 'Insights into the classification of myasthenia gravis', PloS one, vol. 9, no. 9, e106757. https://doi.org/10.1371/journal.pone.0106757
Akaishi T, Yamaguchi T, Suzuki Y, Nagane Y, Suzuki S, Murai H et al. Insights into the classification of myasthenia gravis. PloS one. 2014 Sep 5;9(9). e106757. https://doi.org/10.1371/journal.pone.0106757
Akaishi, Tetsuya ; Yamaguchi, Takuhiro ; Suzuki, Yasushi ; Nagane, Yuriko ; Suzuki, Shigeaki ; Murai, Hiroyuki ; Imai, Tomihiro ; Motomura, Masakatsu ; Fujihara, Kazuo ; Aoki, Masashi ; Utsugisawa, Kimiaki. / Insights into the classification of myasthenia gravis. In: PloS one. 2014 ; Vol. 9, No. 9.
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AU - Murai, Hiroyuki

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