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Multicenter Study
. 2012 Feb;41(4):589-98.
doi: 10.1016/j.semarthrit.2011.07.010. Epub 2011 Sep 29.

"To be or not to be," ten years after: evidence for mixed connective tissue disease as a distinct entity

Affiliations
Multicenter Study

"To be or not to be," ten years after: evidence for mixed connective tissue disease as a distinct entity

Susanna Cappelli et al. Semin Arthritis Rheum. 2012 Feb.

Abstract

Objectives: To determine if mixed connective tissue disease (MCTD) can be considered an independent clinical entity, to compare 3 different classification criteria for MCTD (Kasukawa, Alarcón-Segovia, and Sharp), and to define predictors (clinical features and autoantibodies) of potential evolution toward other connective tissue diseases (CTDs).

Methods: One hundred sixty-one MCTD patients were evaluated retrospectively at the diagnosis and in 2008. They were classified, at the diagnosis, according to the 3 classification criteria of MCTD (Sharp, Alarcón-Segovia, and Kasukawa) and reclassified in 2008 according to their evolution. Statistical analyses were performed to find out predictors (clinical features and autoantibodies) of evolution into other CTDs.

Results: After a mean of 7.9 years of disease, 57.9% of patients still satisfied MCTD classification criteria of Kasukawa; 17.3% evolved into systemic sclerosis, 9.1% into systemic lupus erythematosus, 2.5% into rheumatoid arthritis, 11.5% was reclassified as affected by undifferentiated connective tissue disease, and 1.7% as suffering from overlap syndrome. Kasukawa's criteria were more sensitive (75%) in comparison to those of Alarcón-Segovia (73%) and Sharp (42%). The presence of anti-DNA antibodies (P = 0.012) was associated with evolution into systemic lupus erythematosus; hypomotility or dilation of esophagus (P < 0.001); and sclerodactyly (P = 0.034) with evolution into systemic sclerosis.

Conclusions: MCTD is a distinct clinical entity but it is evident that a subgroup of patients may evolve into another CTD during disease progression. Initial clinical features and autoantibodies can be useful to predict disease evolution.

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