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Response to treatment of myasthenia gravis according to clinical subtype

Overview of attention for article published in BMC Neurology, November 2016
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Title
Response to treatment of myasthenia gravis according to clinical subtype
Published in
BMC Neurology, November 2016
DOI 10.1186/s12883-016-0756-3
Pubmed ID
Authors

Tetsuya Akaishi, Yasushi Suzuki, Tomihiro Imai, Emiko Tsuda, Naoya Minami, Yuriko Nagane, Akiyuki Uzawa, Naoki Kawaguchi, Masayuki Masuda, Shingo Konno, Hidekazu Suzuki, Hiroyuki Murai, Masashi Aoki, Kimiaki Utsugisawa

Abstract

We have previously reported using two-step cluster analysis to classify myasthenia gravis (MG) patients into the following five subtypes: ocular MG; thymoma-associated MG; MG with thymic hyperplasia; anti-acetylcholine receptor antibody (AChR-Ab)-negative MG; and AChR-Ab-positive MG without thymic abnormalities. The objectives of the present study were to examine the reproducibility of this five-subtype classification using a new data set of MG patients and to identify additional characteristics of these subtypes, particularly in regard to response to treatment. A total of 923 consecutive MG patients underwent two-step cluster analysis for the classification of subtypes. The variables used for classification were sex, age of onset, disease duration, presence of thymoma or thymic hyperplasia, positivity for AChR-Ab or anti-muscle-specific tyrosine kinase antibody, positivity for other concurrent autoantibodies, and disease condition at worst and current. The period from the start of treatment until the achievement of minimal manifestation status (early-stage response) was determined and then compared between subtypes using Kaplan-Meier analysis and the log-rank test. In addition, between subtypes, the rate of the number of patients who maintained minimal manifestations during the study period/that of patients who only achieved the status once (stability of improved status) was compared. As a result of two-step cluster analysis, 923 MG patients were classified into five subtypes as follows: ocular MG (AChR-Ab-positivity, 77%; histogram of onset age, skewed to older age); thymoma-associated MG (100%; normal distribution); MG with thymic hyperplasia (89%; skewed to younger age); AChR-Ab-negative MG (0%; normal distribution); and AChR-Ab-positive MG without thymic abnormalities (100%, skewed to older age). Furthermore, patients classified as ocular MG showed the best early-stage response to treatment and stability of improved status, followed by those classified as thymoma-associated MG and AChR-Ab-positive MG without thymic abnormalities; by contrast, those classified as AChR-Ab-negative MG showed the worst early-stage response to treatment and stability of improved status. Differences were seen between the five subtypes in demographic characteristics, clinical severity, and therapeutic response. Our five-subtype classification approach would be beneficial not only to elucidate disease subtypes, but also to plan treatment strategies for individual MG patients.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 18%
Other 7 14%
Student > Ph. D. Student 6 12%
Student > Bachelor 5 10%
Student > Doctoral Student 4 8%
Other 6 12%
Unknown 13 26%
Readers by discipline Count As %
Medicine and Dentistry 18 36%
Neuroscience 8 16%
Nursing and Health Professions 3 6%
Engineering 2 4%
Agricultural and Biological Sciences 2 4%
Other 2 4%
Unknown 15 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2018.
All research outputs
#18,589,103
of 23,025,074 outputs
Outputs from BMC Neurology
#1,907
of 2,459 outputs
Outputs of similar age
#305,076
of 418,506 outputs
Outputs of similar age from BMC Neurology
#30
of 39 outputs
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