Department of General Practice, Maastricht University/Caphri, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Maturitas. 2010 Feb;65(2):143-8. doi: 10.1016/j.maturitas.2009.12.007. Epub 2010 Jan 6.
Low bone mineral density (BMD) and clinical factors (CRF) have been identified as factors associated with an increased relative risk of fractures. From this observation and for clinical decision making, the concept of prediction of the individual absolute risk of fractures has emerged. It refers to the individual's risk for fractures over a certain time period, e.g. the next 5 and 10 years. Two individualized fracture risk calculation tools that are increasingly used and are available on the web are the FRAX algorithm and the Garvan fracture risk calculator. These tools integrate BMD and CRFs for fracture risk calculation in the individual patient in daily practice. Although both tools include straightforward risk factors, such as age, sex, previous fractures, body weight and BMD, they differ in several aspects, such as the inclusion of other CRFs, fall risks and number of previous fractures. Both models still need to be validated in different populations before they can be generalized to other populations, since the background risk for fractures is population specific. Further studies will be needed to validate their contribution in selecting patients who will achieve fracture risk reduction with anti-osteoporosis therapy.
低骨密度（BMD）和临床因素（CRF）已被确定为与骨折风险增加相关的因素。基于这一观察结果，并为临床决策考虑，出现了预测个体骨折绝对风险的概念。它指的是个体在特定时间段内（例如未来 5 年和 10 年）发生骨折的风险。目前在网络上广泛应用的两种个体化骨折风险计算工具是 FRAX 算法和 Garvan 骨折风险计算器。这些工具整合了 BMD 和 CRF，以便在日常实践中计算个体患者的骨折风险。虽然这两种工具都包含了年龄、性别、既往骨折史、体重和 BMD 等简单的风险因素，但它们在其他方面存在差异，例如包含其他 CRF、跌倒风险和既往骨折次数。在将这些模型推广到其他人群之前，还需要在不同人群中进行验证，因为骨折的背景风险是特定于人群的。还需要进一步的研究来验证它们在选择接受抗骨质疏松治疗后可降低骨折风险的患者方面的贡献。
