Clinical characteristics and long-term prognosis of anti-MDA5-positive dermatomyositis: a comparative study across

Fang Dong1, Panpan Zhang1, Wenlu Hu1

  • 1Clinical Immunology and Rheumatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan Province, China.

Abstract

Insights

Age significantly impacts clinical presentation and prognosis in anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis (anti-MDA5+ DM). Older patients (≥60 years) face higher mortality risks, particularly with Pneumocystis jirovecii pneumonia (PJP) infection.

Area of Science:

  • Rheumatology
  • Immunology
  • Dermatology

Background:

  • Limited research exists on age-related clinical differences and prognosis in anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis (anti-MDA5+ DM).
  • Understanding these variations is crucial for tailoring treatment and improving patient outcomes.

Purpose of the Study:

  • To investigate the clinical manifestations and long-term mortality of anti-MDA5+ DM patients across different age groups.
  • To identify age-specific risk factors and develop a prognostic model for mortality.

Main Methods:

  • A cohort of 318 newly diagnosed anti-MDA5+ DM patients was analyzed.
  • Cochran-Armitage test for trend (CATT) assessed age-related clinical characteristic changes.
  • Cox regression and a nomogram model were used for mortality risk stratification.

Main Results:

  • Clinical features like cough, Pneumocystis jirovecii pneumonia (PJP), dyspnea, and rapidly progressive interstitial lung disease (RP-ILD) increased with age.
  • Rash and arthralgia prevalence decreased in older age groups.
  • A novel nomogram incorporating age and PJP infection demonstrated independent and combined effects on mortality.

Conclusions:

  • Clinical and laboratory findings in anti-MDA5+ DM vary significantly by age.
  • Advanced age (≥60 years) and PJP infection are key indicators of poor prognosis.
  • The developed nomogram aids in early risk stratification for improved clinical decision-making.

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