OPEN - Open Patient data Explorative Network, Department of Clinical Research, University of Southern Denmark, Odense University Hospital, Heden 16, DK-5000 Odense C, Denmark; Department of Medicine, Holbæk Hospital, Smedelundsgade 60, DK-4300 Holbæk, Denmark.
OPEN - Open Patient data Explorative Network, Department of Clinical Research, University of Southern Denmark, Odense University Hospital, Heden 16, DK-5000 Odense C, Denmark.
Bone. 2021 Jun;147:115934. doi: 10.1016/j.bone.2021.115934. Epub 2021 Mar 20.
Prevention of osteoporotic fractures remains largely insufficient, and effective means to identify patients at high, short-term fracture risk are needed. The FREM tool is available for automated case finding of men and women aged 45 years or older at high imminent (1-year) risk of osteoporotic fractures, based on administrative health data with a 15-year look-back. The aim of this study was to validate the performance of FREM, and the effect of applying a shorter look-back period. We also evaluated FREM for 5-year fracture risk prediction.
Using Danish national health registers we generated consecutive general population cohorts for the years 2014 through 2018. Within each year and across the full time period we estimated the individual fracture risk scores and determined the actual occurrence of major osteoporotic fractures (MOF) and hip fractures. Risk scores were calculated with 15- and 5-year look-back periods. The discriminative ability was evaluated by area under the receiver operating curve (AUC), and negative predictive value (NPV) and positive predictive value (PPV) were estimated applying a calculated risk cut-off of 2% for MOF and 0.3% for hip fractures.
Applying a 15-year look-back, AUC was around 0.75-0.76 for MOF and 0.84-0.87 for hip fractures in 2014, with minor decreases in the subsequent fracture cohorts (2015 to 2018). Applying a 5-year look-back generated similar results, with only marginally lower AUC. In the 5-year risk prediction setting, AUC-values were 0.70-0.72 for MOF and 0.81-0.84 for hip fractures. Generally, PPVs were low, while NPVs were very high.
FREM predicts the 1- and 5-year risk of MOF and hip fractures with acceptable vs excellent discriminative power, respectively, when applying both a 15- and a 5-year look-back. Hence, the FREM tool may be applied to improve identification of individuals at high imminent risk of fractures using administrative health data.
骨质疏松性骨折的预防仍然远远不够，需要有效的方法来识别短期（1 年）内骨折风险较高的患者。FREM 工具可基于具有 15 年回溯期的行政健康数据，自动发现 45 岁或以上的男性和女性的高即时（1 年）骨质疏松性骨折风险病例。本研究的目的是验证 FREM 的性能，以及应用较短回溯期的效果。我们还评估了 FREM 对 5 年骨折风险的预测。
使用丹麦国家健康登记册，我们为 2014 年至 2018 年生成了连续的一般人群队列。在每一年和整个时间段内，我们估计了个体骨折风险评分，并确定了主要骨质疏松性骨折（MOF）和髋部骨折的实际发生情况。风险评分分别采用 15 年和 5 年回溯期计算。通过接受者操作特征曲线（AUC）下面积评估区分能力，并通过计算的 MOF 风险截止值为 2%和髋部骨折风险截止值为 0.3%来估计阴性预测值（NPV）和阳性预测值（PPV）。
在 2014 年应用 15 年回溯期时，MOF 和髋部骨折的 AUC 约为 0.75-0.76，随后的骨折队列（2015 年至 2018 年）略有下降。应用 5 年回溯期时得到了相似的结果，仅 AUC 略有下降。在 5 年风险预测中，MOF 和髋部骨折的 AUC 值分别为 0.70-0.72 和 0.81-0.84。一般来说，PPV 较低，而 NPV 非常高。
当应用 15 年和 5 年回溯期时，FREM 分别以可接受的 vs 优异的区分能力预测 MOF 和髋部骨折的 1 年和 5 年风险。因此，FREM 工具可以应用于使用行政健康数据来提高对高即时骨折风险个体的识别。
