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Choosing the tool for osteoporosis risk prediction
Catherine Cormier1, Eugenie Koumakis, Jean-Claude Souberbielle
1aDepartment of Rheumatology A, Cochin Hospital bPhysiology Department, Necker-Enfants-Malades Hospital, Paris Descartes University, Paris, France.
Predicting osteoporotic fracture risk is crucial for high-risk populations. Recent advancements in clinical, biochemical, and imaging tools, alongside Dual-energy X-ray absorptiometry (DXA), enhance fracture risk assessment and clinical decision-making.
Area of Science:
- Orthopedics
- Gerontology
- Radiology
Background:
- Osteoporotic fractures pose a significant health challenge, particularly with an aging global population.
- Accurate fracture risk prediction is essential for timely intervention and prevention strategies.
- Novel assessment tools are continuously being developed to improve predictive accuracy.
Purpose of the Study:
- To review recent advancements in clinical, biochemical, and imaging modalities for fracture risk prediction.
- To summarize the utility of Dual-energy X-ray absorptiometry (DXA)-derived tools and other emerging techniques.
- To provide an overview of current and potential future methods for assessing fracture risk.
Main Methods:
- Review of recent literature on fracture risk prediction tools.
- Synthesis of information on clinical strategies, DXA-based methods, imaging techniques, and biochemical markers.
- Evaluation of the current and potential applications of various assessment tools.
Main Results:
- Dual-energy X-ray absorptiometry (DXA) and clinical fracture risk prediction tools are currently preferred methods.
- Clinical fracture risk assessment can be utilized independently when DXA is inaccessible.
- Emerging tools like trabecular bone score, quantitative ultrasound, and bone turnover markers show promise.
Conclusions:
- DXA and established clinical risk tools are primary for fracture risk assessment.
- Clinical risk prediction alone is a viable alternative if DXA is unavailable.
- Further research on emerging tools will likely enhance individualized fracture risk management and clinical decision-making.
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