Supplementary file 1_Global prevalence, site-specific patterns, and key risk factors for o

A systematic review and meta-analysis of 59 studies quantifying bone loss in systemic lupus erythematosus (SLE) patients. The analysis reports an overall osteoporosis prevalence of 16.70% and osteopenia prevalence of 39.50%, identifying key risk factors like age and glucocorticoid use. The supplementary document was authored by Chunhui Yu and uploaded to figshare in April 2026.

Use Cases

• Estimating global and regional disease burden for osteoporosis in SLE patients based on the pooled prevalence rates.
• Identifying high-risk patient subgroups for targeted screening based on reported factors like postmenopausal status and Asian ethnicity.
• Modeling the impact of glucocorticoid dosage on fracture risk based on the quantified odds ratios.
• Analyzing site-specific patterns of bone loss (e.g., lumbar spine vs. femoral neck) for clinical monitoring strategies.

Strengths

• Provides specific, pooled prevalence figures: 16.70% for osteoporosis and 39.50% for osteopenia in SLE patients.
• Quantifies key risk factors with odds ratios, such as age >50 years (OR=21.92) and long-term glucocorticoid use (OR=1.63).
• Based on a systematic methodology reviewing 59 studies from multiple databases up to September 2025.

Limitations

• The primary data file is a 575.1 KB DOCX document; the underlying tabular data from the meta-analysis is not directly accessible.
• Column-level documentation is absent; field semantics must be inferred from the text after download.
• Row count is unknown, which may limit suitability assessment for direct computational analysis.

Provenance

Source

Chunhui Yu via figshare.

Collection Method

Systematic review and meta-analysis of observational studies from PubMed, Embase, Cochrane, Web of Science, CNKI, and WANFANG.

Time Range

Studies included up to 26 September 2025.

Freshness

Last updated 2026-04-15 05:44:14; freshness should be verified.

Geography

Global, with subgroup analysis suggesting regional patterns (e.g., Asian patients).