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爱尔兰的 DXA-FRAX 可能与 Web-FRAX 有很大的显著差异。

Ireland DXA-FRAX may differ significantly and substantially to Web-FRAX.

机构信息

Insight SFI Research Centre for Data Analytics, Data Science Institute, University of Galway, IDA Business Park, Lower Dangan, Galway, H91 AEX4, Ireland.

School of Engineering, College of Science and Engineering, University of Galway, Galway, Ireland.

出版信息

Arch Osteoporos. 2023 Mar 20;18(1):43. doi: 10.1007/s11657-023-01232-y.

DOI:10.1007/s11657-023-01232-y
PMID:36939937
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10027809/
Abstract

UNLABELLED

Appropriate use of FRAX reduces the number of people requiring DXA scans, while contemporaneously determining those most at risk. We compared the results of FRAX with and without inclusion of BMD. It suggests clinicians to carefully consider the importance of BMD inclusion in fracture risk estimation or interpretation in individual patients.

PURPOSE

FRAX is a widely accepted tool to estimate the 10-year risk of hip and major osteoporotic fracture in adults. Prior calibration studies suggest this works similarly with or without the inclusion of bone mineral density (BMD). The purpose of the study is to compare within-subject differences between FRAX estimations derived using DXA and Web software with and without the inclusion of BMD.

METHOD

A convenience cohort was used for this cross-sectional study, consisting of 1254 men and women aged between 40 and 90 years who had a DXA scan and complete validated data available for analysis. FRAX 10-year estimations for hip and major osteoporotic fracture were calculated using DXA software (DXA-FRAX) and the Web tool (Web-FRAX), with and without BMD. Agreements between estimates within each individual subject were examined using Bland-Altman plots. We performed exploratory analyses of the characteristics of those with very discordant results.

RESULTS

Overall median DXA-FRAX and Web-FRAX 10-year hip and major osteoporotic fracture risk estimations which include BMD are very similar: 2.9% vs. 2.8% and 11.0% vs. 11% respectively. However, both are significantly lower than those obtained without BMD: 4.9% and 14% respectively, P < 0.001. Within-subject differences between hip fracture estimates with and without BMD were < 3% in 57% of cases, between 3 and 6% in 19% of cases, and > 6% in 24% of cases, while for major osteoporotic fractures such differences are < 10% in 82% of cases, between 10 and 20% in 15% of cases, and > 20% in 3% of cases.

CONCLUSIONS

Although there is excellent agreement between the Web-FRAX and DXA-FRAX tools when BMD is incorporated, sometimes there are very large differences for individuals between results obtained with and without BMD. Clinicians should carefully consider the importance of BMD inclusion in FRAX estimations when assessing individual patients.

摘要

未标注

FRAX 的合理使用减少了需要 DXA 扫描的人数,同时确定了风险最高的人群。我们比较了 FRAX 有和没有包含 BMD 的结果。它建议临床医生在评估或解释个体患者的骨折风险时,仔细考虑包含 BMD 的重要性。

目的

FRAX 是一种广泛接受的工具,用于估计成年人髋部和主要骨质疏松性骨折的 10 年风险。先前的校准研究表明,无论是否包含骨密度 (BMD),该工具的效果均相似。本研究的目的是比较使用 DXA 和网络软件得出的 FRAX 估计值在有和没有包含 BMD 时的个体内差异。

方法

本横断面研究使用方便队列,纳入 1254 名年龄在 40 至 90 岁之间的男性和女性,他们进行了 DXA 扫描,并且有完整的经过验证的数据可供分析。使用 DXA 软件 (DXA-FRAX) 和网络工具 (Web-FRAX) 计算了髋部和主要骨质疏松性骨折的 FRAX 10 年估计值,有和没有 BMD。使用 Bland-Altman 图检查每个个体内估计值之间的一致性。我们对差异非常大的结果的特征进行了探索性分析。

结果

总体而言,包含 BMD 的 DXA-FRAX 和 Web-FRAX 10 年髋部和主要骨质疏松性骨折风险估计值非常相似:分别为 2.9%和 2.8%,11.0%和 11%。然而,两者均明显低于不包含 BMD 的结果:分别为 4.9%和 14%,P<0.001。在有和没有 BMD 的情况下,髋部骨折估计值的个体内差异<3%的情况占 57%,在 3%至 6%的情况占 19%,>6%的情况占 24%,而对于主要骨质疏松性骨折,这样的差异<10%的情况占 82%,在 10%至 20%的情况占 15%,>20%的情况占 3%。

结论

虽然当包含 BMD 时,Web-FRAX 和 DXA-FRAX 工具之间具有很好的一致性,但有时对于个体而言,在有和没有 BMD 的情况下,结果之间存在非常大的差异。在评估个体患者时,临床医生应仔细考虑在 FRAX 估计中包含 BMD 的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/7a39c5d01caa/11657_2023_1232_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/0ce3a15bcfee/11657_2023_1232_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/6a2c44cb6402/11657_2023_1232_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/72e4c19ed9d0/11657_2023_1232_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/dbe32ae2e76f/11657_2023_1232_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/4c0959e7c8ef/11657_2023_1232_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/7a39c5d01caa/11657_2023_1232_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/0ce3a15bcfee/11657_2023_1232_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/6a2c44cb6402/11657_2023_1232_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/72e4c19ed9d0/11657_2023_1232_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/dbe32ae2e76f/11657_2023_1232_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/4c0959e7c8ef/11657_2023_1232_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/10027809/7a39c5d01caa/11657_2023_1232_Fig6_HTML.jpg

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