Unveiling the efficacy predictors and potential mechanisms of Semen Cuscutae against osteoporosis via machine learning and meta-analysis: a preclinical study
Abstract
Purpose: To systematically evaluate the anti-osteoporotic efficacy and underlying mechanisms of Semen Cuscutae and to explore potential experimental factors associated with treatment efficacy using an integration of meta-analysis and machine learning (ML).
Methods: A comprehensive search of eight databases (from inception to December 1, 2025) was conducted to identify randomized controlled trials of Semen Cuscutae in osteoporotic animal models. Meta-analysis was performed to assess Bone Mineral Density (BMD), bone histomorphometry, and inflammatory/metabolic markers. Additionally, an exploratory XGBoost model interpreted via SHapley Additive exPlanations (SHAP) was constructed to quantitatively rank ten experimental variables potentially associated with therapeutic efficacy.
Results: Fifteen studies were included in the final analysis. Meta-analysis demonstrated that Semen Cuscutae intervention significantly increased femoral and lumbar spine BMD, improved trabecular micro-architecture (increased BV/TV and Tb.Th; decreased Tb.Sp), and enhanced biomechanical strength. Mechanistically, Semen Cuscutae remodeled the osteoimmune microenvironment by suppressing pro-inflammatory cytokines (IL-6) and bone resorption markers (TRACP, CTX, RANKL), while ALP showed an increasing trend and osteogenic or reparative factors, including OPG, IGF, and TGF-β, were significantly upregulated. Exploratory ML analysis ranked "Species," "Dose," and "Treatment Duration" as the variables most…
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Evidence Hub reads this as a meta-analysis, done in animal and computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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