ArticleDiagnostics (Basel, Switzerland)2019
Multivariate Comparison of Cytokine Profiles for Normal- and Low-Bone-Density Subjects.
Article in Diagnostics (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Machine Learning-Driven Prediction of Low BMD in Postmenopausal Women Using Cytokine, RANKL/OPG, and Oxidative Stress Biomarker Signatures: An Exploratory Study.Biomedicines · 2026Article
- Associations Between Inflammatory Mediators and Bone Outcomes in Postmenopausal Women: A Cross-Sectional Analysis of Baseline Data from the Prune Study.Journal of inflammation research · 2023Article
- Negligible Effect of Estrogen Deficiency on Development of Skeletal Changes Induced by Type 1 Diabetes in Experimental Rat Models.Mediators of inflammation · 2020Article
- Cytokines in Inflammatory Disease.International journal of molecular sciences · 2019Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Osteoporosis is a serious worldwide public health concern. The role of the immune system in the onset of osteoporosis in postmenopausal women is an area of current research. Here we study data from a panel of 10 cytokines obtained from postmenopausal women, with both normal and low bone mineral density (BMD). Normal- and low-BMD groups are compared and contrasted, and further low-BMD participants are sub-classified into osteopenic and osteoporotic based on BMD levels, and compared to each other. Via the use of multivariate statistical tools, we examine contrasting groups in relation to: (a) the presence of subgroups/clusters; (b) whether groups have statistically different multivariate distributions; (c) how strongly groups differ (if at all), which relates to the practical/clinical significant of any differences; and (d) which cytokines contribute most to any differences between groups. We find that the normal- vs. low-BMD groups are markedly different (
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