Validation of the Fracture Risk Evaluation Model (FREM) in predicting major osteoporotic fractures and hip fractures using administrative health data

Michael K Skjødt; Sören Möller; Nana Hyldig; Anne Clausen; Mette Bliddal; Jens Søndergaard; Bo Abrahamsen; Katrine Hass Rubin

doi:10.1016/j.bone.2021.115934

Validation of the Fracture Risk Evaluation Model (FREM) in predicting major osteoporotic fractures and hip fractures using administrative health data

Bone. 2021 Jun:147:115934. doi: 10.1016/j.bone.2021.115934. Epub 2021 Mar 20.

Authors

Michael K Skjødt¹, Sören Möller², Nana Hyldig², Anne Clausen², Mette Bliddal², Jens Søndergaard³, Bo Abrahamsen¹, Katrine Hass Rubin⁴

Affiliations

¹ 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.
² OPEN - Open Patient data Explorative Network, Department of Clinical Research, University of Southern Denmark, Odense University Hospital, Heden 16, DK-5000 Odense C, Denmark.
³ The Research Unit of General Practice, Department of Public Health, University of Southern Denmark, J.B. Winsløws Vej 9, DK-5000 Odense, Denmark.
⁴ OPEN - Open Patient data Explorative Network, Department of Clinical Research, University of Southern Denmark, Odense University Hospital, Heden 16, DK-5000 Odense C, Denmark. Electronic address: krubin@health.sdu.dk.

PMID: 33757901
DOI: 10.1016/j.bone.2021.115934

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords: Automated risk calculation; Effectiveness; FREM fracture risk; Validation.

MeSH terms

Bone Density
Female
Hip Fractures* / epidemiology
Humans
Male
Osteoporotic Fractures* / epidemiology
Risk Assessment
Risk Factors