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更新的小梁骨评分(TBS)算法的临床性能,考虑到软组织厚度:OsteoLaus 研究。

Clinical Performance of the Updated Trabecular Bone Score (TBS) Algorithm, Which Accounts for the Soft Tissue Thickness: The OsteoLaus Study.

机构信息

Centre of Bone Diseases, Bone and Joint Department, Lausanne University Hospital, Lausanne, Switzerland.

出版信息

J Bone Miner Res. 2019 Dec;34(12):2229-2237. doi: 10.1002/jbmr.3851. Epub 2019 Oct 25.

Abstract

Regional soft tissue may have a noise effect on trabecular bone score (TBS) and eventually alter its estimate. The current TBS software (TBS iNsight®) is based on an algorithm accounting for body mass index (BMI) (TBS ). We aimed to explore the updated TBS algorithm that accounts for soft tissue thickness (TBS ). This study was embedded in the OsteoLaus cohort of women in Lausanne, Switzerland. Hip and lumbar spine (LS) dual-energy X-ray absorptiometry (DXA) scans were performed using Discovery A System (Hologic). The incident major osteoporotic fractures (MOFs) were assessed from vertebral fracture assessments using Genant's method (vertebral MOF) or questionnaires (nonvertebral MOF). We assessed the correlations of bone mineral density (BMD) or TBS with body composition parameters; MOF prediction ability of both versions of TBS; and the differences between Fracture Risk Assessment Tool (FRAX) adjusted for TBS or TBS . In total, 1362 women with mean ± SD age 64.4 ± 7.5 years and mean ± SD BMI 25.9 ± 4.5 kg/m were followed for 4.4 years and 132 experienced an MOF. All the anthropometric measurements of our interest were positively correlated with LS, femoral neck, or hip BMD and TBS ; whereas with TBS their correlations were negative. In the models adjusted for age, soft tissue thickness, osteoporotic treatment, and LS-BMD, for each SD decline in TBS , there was a 43% (OR 1.43; 95% CI, 1.12 to 1.83) increase in the odds of having MOF; whereas for each SD decline in TBS , there was a 54% (OR 1.54; 95% CI, 1.18 to 2.00) increase in the odds of having an MOF. Both FRAXs were very strongly correlated and the mild differences were present in the already high-risk women for MOF. This study shows that TBS overcomes the debatable residual negative correlation of the current TBS with body size and composition parameters, postulating itself as free from the previously acknowledged technical limitation of TBS. © 2019 American Society for Bone and Mineral Research.

摘要

区域软组织可能会对骨小梁评分(TBS)产生噪声影响,从而改变其估计值。当前的 TBS 软件(TBS iNsight®)基于一种考虑体重指数(BMI)的算法(TBS )。我们旨在探索一种新的 TBS 算法,该算法考虑了软组织厚度(TBS )。本研究纳入了瑞士洛桑 OsteoLaus 队列中的女性。使用 Discovery A 系统(Hologic)进行髋部和腰椎(LS)双能 X 射线吸收法(DXA)扫描。通过 Genant 方法(椎体 MOF)或问卷(非椎体 MOF)评估主要骨质疏松性骨折(MOF)的发生情况。我们评估了骨密度(BMD)或 TBS 与身体成分参数的相关性;两种 TBS 版本的 MOF 预测能力;以及 TBS 或 TBS 调整后的骨折风险评估工具(FRAX)之间的差异。共有 1362 名女性,平均年龄为 64.4 ± 7.5 岁,平均 BMI 为 25.9 ± 4.5 kg/m²,随访时间为 4.4 年,132 名女性发生 MOF。我们感兴趣的所有人体测量学指标均与 LS、股骨颈或髋部 BMD 和 TBS 呈正相关;而与 TBS 呈负相关。在调整年龄、软组织厚度、骨质疏松治疗和 LS-BMD 的模型中,TBS 每下降一个标准差,MOF 的发生几率增加 43%(OR 1.43;95%CI,1.12 至 1.83);而 TBS 每下降一个标准差,MOF 的发生几率增加 54%(OR 1.54;95%CI,1.18 至 2.00)。两种 FRAX 高度相关,在已经处于 MOF 高风险的女性中,差异较小。本研究表明,TBS 克服了当前 TBS 与身体大小和成分参数之间存在的有争议的负相关关系,假设其不受先前承认的 TBS 技术限制。

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