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A Statistical Approach Regarding the Diagnosis of Osteoporosis and Osteopenia From

机译:关于骨质疏松症和骨质增生的诊断的统计方法

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摘要

Osteoporosis and osteopenia are diagnosed most commonly by evaluating the lowest T‐score of BMD measurements, typically taken at three sites: the L1‐L4 lumbar spine, femoral neck, and total hip. This study aimed to evaluate the effect of using all three BMD measurements and multivariate statistical theory to evaluate how the diagnoses of osteoporosis and osteopenia change in simulation studies and in real data. First, it was found that the T‐scores from these three BMD measurements rarely give concordant diagnoses using the same World Health Organization (WHO) and International Society for Clinical Densitometry (ISCD) guidelines, so that the diagnosis strongly depends on the BMD sites measured. Next, strong correlations were found between the BMD measurements at different sites within the same person, which resulted in increased congruence/concordance between the diagnoses obtained from the BMD T‐scores. Multivariate statistical theory was used to show that the joint distribution of the BMD T‐scores at different sites follows a multivariate t distribution and found that the marginal distribution of any BMD T‐score follows a univariate t distribution. Confidence ellipsoids were derived that are equivalent to the univariate WHO/ISCD thresholds for osteoporosis (T‐score ≤−2.5) and osteopenia (−2.5 < T‐score <−1). The study found that more patients are diagnosed with osteoporosis using the multivariate version of the WHO/ISCD guidelines rather than the current WHO/ISCD guidelines in both real data and simulation studies. Diagnoses of osteoporosis using the statistics derived method were also associated with higher FRAX (fracture risk assessment tool) probabilities of major osteoporotic (p = 0.001) and hip fractures (p = 2.2 × 10−6). In conclusion, this study shows that considering all three BMD T‐scores is potentially more informative than using the single lowest BMD T‐score. © 2020 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.
机译:通过评估BMD测量的最低T分数,通常在三个地点进行核对,骨质疏松症和骨赘最常诊断:L1-L4腰椎,股骨颈和总臀部。本研究旨在评估使用所有三种BMD测量和多变量统计理论的效果,评价骨质疏松症的诊断和骨内血症如何变化模拟研究和实际数据。首先,发现来自这三种BMD测量的T分数很少使用同一个世界卫生组织(WHO)和国际临床密度测定(ISCD)指南的协调诊断,因此诊断强烈取决于测量的BMD位点。接下来,在同一人内不同部位的BMD测量之间发现强相关性,这导致从BMD T分数获得的诊断之间增加的同致/一致性。多元统计理论旨在表明,不同部位的BMD T分析的关节分布遵循多元化的T分布,发现任何BMD T分的边缘分布遵循单变量的T分布。衍生信心椭圆体,其等于骨质疏松症的单变量(T-Score≤-2.5)和骨缩减(-2.5分数<-1)的单变量阈值。该研究发现,使用WHO / ISCD指南的多元版本而不是实际数据和模拟研究的当前患者诊断患者患有骨质疏松症的骨质疏松症。使用统计学衍生方法诊断骨质疏松症也与高骨质疏松症(P = 0.001)和髋部骨折的较高毛(断裂风险评估工具)概率有关(P = 2.2×10-6)。总之,本研究表明,考虑到所有三个BMD T分数可能比使用单个最低BMD T分数更有信息。 ©2020作者。 JBMR Plus由Wiley期刊LLC发布。代表美国人骨骼和矿物学研究。

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