Li Guowei, Leslie William D, Kovacs Christopher S, Prior Jerilynn, Josse Robert G, Towheed Tanveer, Davison K Shawn, Thabane Lehana, Papaioannou Alexandra, Levine Mitchell Ah, Goltzman David, Zeng Jie, Qi Yong, Tian Junzhan, Adachi Jonathan D
Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou, China.
Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, Canada.
J Bone Miner Res. 2020 Jun;35(6):1058-1064. doi: 10.1002/jbmr.3971. Epub 2020 Feb 14.
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 (L to L ) 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.
人们认识到，小梁骨评分（TBS）可提供骨骼信息，而衰弱测量与不良健康结局风险增加显著相关。鉴于骨折风险评估工具的预测能力欠佳，我们旨在评估衰弱与TBS相结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值通过腰椎（L1至L4）双能X线吸收法（DXA）图像进行估算；衰弱通过缺陷积累衰弱指数（FI）进行评估。结局为随访期间首次发生MOF的时间。我们使用Harrell's C指数比较模型的预测准确性。使用赤池信息准则、似然比检验和净重新分类改善（NRI）来比较衰弱与TBS相结合的模型（以下简称“FI + TBS”）、单独的FI模型和单独的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。发生MOF的参与者的FI显著更高（0.24对0.20），TBS显著更低（1.231对1.285）。在根据FRAX、骨密度（BMD）和其他协变量进行调整的模型中，FI和TBS与MOF风险显著相关：FI每增加1个标准差，风险比（HR）= 1.26（95%置信区间[CI] 1.11 - 1.43）；TBS每降低1个标准差，HR = 1.38（95% CI 1.21 - 1.59）；当两者合并在同一模型中时，这些关联的衰减可忽略不计（FI每增加1个标准差，HR = 1.24；TBS每降低1个标准差，HR = 1.35）。尽管FI + TBS模型比单独的FI模型和单独的TBS模型对数据的拟合度更好，但在FI + TBS中仅观察到辨别力和NRI的最小且不显著的增强。总之，衰弱和TBS与MOF风险显著且独立相关。需要开展更大规模的研究来确定衰弱与TBS相结合是否能提高MOF风险的预测准确性。© 2020美国骨与矿物质研究学会。
