Vitamin D levels in idiopathic inflammatory myopathy patients: a meta-analysis

ABSTRACT

Purpose

This meta-analysis aimed to explore correlations between vitamin D and idiopathic inflammatory myopathy (IIM).

Methods

A comprehensive database search was conducted on 13 October 2020. Mean differences (MDs) and aggregated risk ratios (RR) with 95% confidence intervals (CIs) were used to determine the correlation between vitamin D deficiency (VDD) and IIM. Statistical analysis was performed with RevMan 5.4 and Stata15, statistical significance was set at p < 0.05.

Results

Search revealed five studies with 286 IIM patients and 480 healthy controls. Results with random-effects modeling indicated that serum vitamin D levels were significantly lower in IIM patients than in healthy controls (MD = -13.10 ng/mL; 95% CI: −16.51 to −9.68; p < 0.00001). No differences were found between patients with IIM and other autoimmune diseases on vitamin D levels (MD =-2.65 ng/mL; 95% CI: −11.31–6.01; p = 0.55). In two studies with 185 IIM patients, those with low vitamin D levels exhibited higher creatine kinase levels (MD = 85.20 IU/L; 95% CI: 72.67–97.73; p < 0.00001) than those with normal vitamin D levels. VDD was correlated with an increased risk of IIM (RR = 3.24, 95% CI: 1.81–5.79; p < 0.0001).

Conclusion

This meta-analysis showed correlations between vitamin D level and IIM. The results indicated, VDD may be a risk factor for IIM, a determinant of immune dysregulation in IIM, or a consequence of IIM. Also, it implied further research to determine whether vitamin D supplementation is beneficial for patients with IIM.

KEYWORDS:

• Vitamin D
• IIM
• Vitamin D Deficiency
• autoimmune
• meta-analysis

Declaration of financial/other relationships

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgments

The authors sincerely thank the founder of the RevMan software for the guidance and team’s collaboration, and providing many constructive suggestions in the process of writing and publishing the article.

Author contributions

Anji Xiong, Shifeng Zhou, Can Liu and Ziyi Hu, analysis of data and drafting of manuscript; Xiaoli Zheng and Chuanmei Xie analysis of data and approval of manuscript; Xiongyan Luo study concept and design. Anji Xiong, Shifeng Zhou, Can Liu and Ziyi Hu had primary responsibility for final content. All authors read and approved the final manuscript.

Data availability statement

Data described in the manuscript will be made available upon request pending [e.g. application and approval, payment, other]. The data for this manuscript are licensed by the participants.

Additional information

Funding

This work was supported by the Government and School Cooperation Program of Nanchong, Sichuan, China [grant numbers 22JCYJPT0027], Luzhou Government and Southwest Medical University Strategic Cooperation Project [Grant no. 2019LZXNYDZ01] and Sichuan Science and Technology Program [2022YFS0622].