It is recognized that the trabecular bone score (TBS) provides skeletal information, and frailty measurement is significantly associated with increased risks of adverse health outcomes. Given the suboptimal predictive power in fracture risk assessment tools, we aimed to evaluate the combination of frailty and TBS regarding predictive accuracy for risk of major osteoporotic fracture (MOF). Data from the prospective longitudinal study of CaMos (Canadian Multicentre Osteoporosis Study) were used for this study. TBS values were estimated using lumbar spine (L₁ to L₄) dual‐energy X‐ray absorptiometry (DXA) images; frailty was evaluated by a frailty index (FI) of deficit accumulation. Outcome was time to first incident MOF during the follow‐up. We used the Harrell's C‐index to compare the model predictive accuracy. The Akaike information criterion, likelihood ratio test, and net reclassification improvement (NRI) were used to compare model performances between the model combining frailty and TBS (subsequently called “FI + TBS”), FI‐alone, and TBS‐alone models. We included 2730 participants (mean age 69 years; 70% women) for analyses (mean follow‐up 7.5 years). There were 243 (8.90%) MOFs observed during follow‐up. Participants with MOF had significantly higher FI (0.24 versus 0.20) and lower TBS (1.231 versus 1.285) than those without MOF. FI and TBS were significantly related with MOF risk in the model adjusted for FRAX with bone mineral density (BMD) and other covariates: hazard ratio (HR) = 1.26 (95% confidence interval [CI] 1.11–1.43) for per‐SD increase in FI; HR = 1.38 (95% CI 1.21–1.59) for per‐SD decrease in TBS; and these associations showed negligible attenuation (HR = 1.24 for per‐SD increase in FI, and 1.35 for per‐SD decrease in TBS) when combined in the same model. Although the model FI + TBS was a better fit to the data than FI‐alone and TBS‐alone, only minimal and nonsignificant enhancement of discrimination and NRI were observed in FI + TBS. To conclude, frailty and TBS are significantly and independently related to MOF risk. Larger studies are warranted to determine whether combining frailty and TBS can yield improved predictive accuracy for MOF risk. © 2020 American Society for Bone and Mineral Research.

中文翻译：

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结合脆弱性和小梁骨评分并不能提高对主要骨质疏松性骨折风险的预测准确性。

众所周知，骨小梁评分 (TBS) 可提供骨骼信息，而脆弱性测量与不良健康结果风险的增加显着相关。鉴于骨折风险评估工具的预测能力欠佳，我们旨在评估脆弱性和 TBS 的组合对主要骨质疏松性骨折 (MOF) 风险的预测准确性。本研究使用了来自 CaMos（加拿大多中心骨质疏松症研究）前瞻性纵向研究的数据。TBS 值使用腰椎（L ₁至 L ₄) 双能 X 射线骨密度仪 (DXA) 图像；虚弱是通过赤字积累的虚弱指数（FI）来评估的。结果是随访期间首次发生 MOF 的时间。我们使用 Harrell 的 C 指数来比较模型的预测准确性。Akaike 信息标准、似然比检验和净重分类改进 (NRI) 用于比较结合脆弱性和 TBS（随后称为“FI + TBS”）的模型、单独的 FI 和单独的 TBS 模型之间的模型性能。我们纳入了 2730 名参与者（平均年龄 69 岁；70% 为女性）进行分析（平均随访 7.5 年）。随访期间观察到 243 例 (8.90%) MOF。与没有 MOF 的参与者相比，具有 MOF 的参与者具有显着更高的 FI（0.24 对 0.20）和更低的 TBS（1.231 对 1.285）。FI 和 TBS 与模型中的 MOF 风险显着相关，该模型通过骨矿物质密度 (BMD) 和其他协变量调整了 FRAX：每个 SD 增加的风险比 (HR) = 1.26 (95% 置信区间 [CI] 1.11–1.43)在 FI 中；HR = 1.38 (95% CI 1.21–1.59) 对于每个 SD 的 TBS 下降；当在同一模型中组合时，这些关联显示出可忽略不计的衰减（FI 中每 SD 增加的 HR = 1.24，TBS 中每 SD 减少的 HR = 1.35）。尽管模型 FI + TBS 比单独的 FI 和单独的 TBS 模型更适合数据，但在 FI + TBS 中仅观察到最小且不显着的辨别力和 NRI 增强。总而言之，衰弱和 TBS 与 MOF 风险显着且独立相关。需要进行更大规模的研究来确定结合衰弱和 TBS 是否可以提高 MOF 风险的预测准确性。