Crans Gerald G, Genant Harry K, Krege John H
Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, USA.
Bone. 2005 Aug;37(2):175-9. doi: 10.1016/j.bone.2005.04.003.
The semiquantitative spinal deformity index (SDI) is a summary measure of the vertebral fracture status of the spine incorporating both the number and severity of vertebral fractures. For each vertebra, a visual semiquantitative grade of 0, 1, 2, or 3 is assigned for no fracture or mild, moderate, or severe fracture, respectively, and the SDI is calculated by summing the fracture grades of all vertebrae (T4 to L4). We investigated the effect of prevalent vertebral fracture number and severity, as integrated by the SDI, on 3-year vertebral fracture risk by performing logistic regression modeling with data from the MORE trial. There was a striking linear relationship between baseline SDI and the model-based vertebral fracture risk estimates, with a near-perfect correlation (r = 0.98, P < 0.001). However, the SDI may be overly simplistic, as a given SDI value can be attained through differing vertebral fracture scenarios (i.e., an SDI of 3 can be realized three ways), each corresponding to potentially different vertebral fracture risk. To address this issue, a second, more complex model was constructed that included individual predictor variables for number of mild, number of moderate, and number of severe prevalent vertebral fractures. The model-based risk estimates for vertebral fracture using the SDI and the more complex model were highly correlated (r = 0.91, P < 0.001), giving almost identical values up to an SDI of 5. Thus, for most clinical scenarios, it is not necessary to consider the particular fracture configuration that led to a given SDI score for predicting a patient's future vertebral fracture risk. These results validate the SDI as an accurate tool for assessing future vertebral fracture risk; patients with greater baseline SDI had greater future risk for vertebral fractures.
半定量脊柱畸形指数(SDI)是一种对脊柱椎体骨折状况的综合测量方法,它综合考虑了椎体骨折的数量和严重程度。对于每个椎体,分别赋予0、1、2或3的视觉半定量等级,分别表示无骨折、轻度骨折、中度骨折或重度骨折,SDI通过将所有椎体(T4至L4)的骨折等级相加来计算。我们利用MORE试验的数据进行逻辑回归建模,研究了由SDI整合的椎体骨折数量和严重程度对3年椎体骨折风险的影响。基线SDI与基于模型的椎体骨折风险估计值之间存在显著的线性关系,相关性近乎完美(r = 0.98,P < 0.001)。然而,SDI可能过于简单,因为给定的SDI值可以通过不同的椎体骨折情况获得(例如,SDI为3可以通过三种方式实现),每种情况对应潜在不同的椎体骨折风险。为了解决这个问题,构建了第二个更复杂的模型,该模型包括轻度、中度和重度椎体骨折数量的个体预测变量。使用SDI和更复杂模型的基于模型的椎体骨折风险估计值高度相关(r = 0.91,P < 0.001),在SDI达到5之前给出几乎相同的值。因此,对于大多数临床情况,在预测患者未来椎体骨折风险时,无需考虑导致给定SDI评分的具体骨折组合。这些结果验证了SDI作为评估未来椎体骨折风险的准确工具;基线SDI较高的患者未来发生椎体骨折的风险更大。