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Insights into the classification of myasthenia gravis.


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.

SUBMITTER: Akaishi T 

PROVIDER: S-EPMC4156422 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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<h4>Background and purpose</h4>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.<h4>Methods</h4>We analyzed 640 consecutive MG patients using two-step cluster analysis with clinical variable  ...[more]

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