Global trends in systemic sclerosis-related mortality, 2001–2023: an epidemiological analysis using World Health Organization mortality data

Open

Keith Pardillada Belangoy, Yoshito Nishimura, Ko Harada, Hideharu Hagiya, Quynh Thi Vu, Hanane Ouddoud, Judah Israel Ong Lescano, Michio Yamamoto, Tatsuaki Takeda, Hirofumi Hamano, Toshihiro Koyama, Yoshito Zamami

2026 Clinical Rheumatology Vol. 45 Issue 5 Article Cited by 1 Quartile

Abstract

Objectives: This study aimed to evaluate the global trends in systemic sclerosis (SSc)-related mortality by age, sex, and geographic region. SSc is a multisystem autoimmune disease characterized by tissue fibrosis, vascular dysfunction, and multi-organ involvement, which is associated with a high mortality risk. Methods: Using the World Health Organization Mortality Database, we examined trends in SSc-related crude mortality rates (SSc-CRs) and age-standardized mortality rates (SSc-ASMR) per 1,000,000 population from 2001 to 2023. Locally weighted regression was applied to visualize long-term patterns, and Joinpoint regression was used to assess the national trends from 2010 to 2023. Results: Across 74 countries, 85,291 SSc-related deaths were reported, with 79.41% occurring in females. The SSc-CR steadily increased from 1.97 (95% confidence interval [CI]: 1.71–2.23) in 2001 to 2.34 (95% CI: 2.01–2.68) in 2023, while the SSc-ASMR decreased from 1.58 (95% CI: 1.42–1.74) to 1.29 (95% CI: 1.08–1.50), respectively. Regionally, mortality was the highest in the Western Pacific region and declined in the Americas and Europe, with temporal fluctuations. The SSc-ASMR was highest in countries with a middle sociodemographic index (SDI). Conclusions: While overall age-standardized mortality from SSc has declined in many regions, disparities persist. These results underscore the importance of sustaining research and enhancing disease awareness, as well as developing strategies to reduce mortality in high-risk populations and regions. (Table presented.) © The Author(s) 2026.

Affiliations

Department of Health Data Science, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama University, Okayama, 7008558, Japan; Division of Haematology and Oncology, Mayo Clinic, Rochester, 55901, MN, United States; Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, 100295674, NY, United States; Department of Infectious Diseases, Okayama University Hospital, Okayama, 7008558, Japan; Graduate School of Human Sciences, The University of Osaka, Osaka, 5650871, Japan; RIKEN Center for Advanced Intelligence Project, Tokyo, 1030027, Japan; Data Science and AI Innovation Research Promotion Center, Shiga University, Shiga, 5228522, Japan; Department of Education and Research Center for Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Okayama University, Okayama, 7008558, Japan; Department of Pharmacy, Okayama University Hospital, Okayama, 7008558, Japan; Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Haiphong University of Medicine and Pharmacy, Haiphong, 180000, Viet Nam; Department of Pharmacy, University of San Carlos, Cebu City, 6000, Philippines