ArticleArchives of osteoporosis2022
External validation of FRISBEE 5-year fracture prediction models: a registry-based cohort study.
Article in Archives of osteoporosis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Predictive value of machine learning on fracture risk in osteoporosis: a systematic review and meta-analysis.BMJ open · 2023Pooled it
- Model-based algorithms to ascertain smoking in administrative health data: a registry-based validation study.BMC medical research methodology · 2026Article
- Association between sarcopenia, its components, and osteoporosis in the FRISBEE cohort.BMC musculoskeletal disorders · 2025Article
- External validation of FRISBEE 2-year and 5-year fracture prediction models in a fracture liaison service cohort.Archives of osteoporosis · 2025Article
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12 authors at 4 institutions in 2 countries.
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Abstract
Five-year fracture risk prediction from the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) models was externally tested in 9716 Canadian women and demonstrated good discrimination but consistently overestimated risk.
introductionFive-year risk prediction models for all fractures, major osteoporotic fractures (MOFs) and central fractures (proximal to forearm and ankle) from the FRISBEE cohort demonstrated good performance in the original derivation cohort. Our aim was to externally validate the FRISBEE-based 5-year prediction models in routine practice.
methodsUsing the population-based Manitoba Bone Mineral Density (BMD) registry, we identified women aged 60-85 years undergoing baseline BMD assessment from September 1, 2012 to March 31, 2018. Five-year probabilities of all fractures, MOFs and central fractures were calculated using the FRISBEE prediction models. We identified incident non-traumatic fractures up to 5 years from population-based healthcare data sources. Performance characteristics included area under the receiver operating characteristic curve (AUROC), gradient of risk (hazard ratio [HR] per SD increase and across risk tertiles) from Cox regression analysis, and calibration (ratio 5-year observed cumulative incidence to predicted fracture probability).
resultsWe included 9716 women (mean age 70.7 + / - SD 5.3 years). During a mean observation time of 2.5 years, all fractures, MOFs and central fractures were identified in 377 (3.9%), 264 (2.7%) and 259 (2.7%) of the women. AUROC showed significant fracture risk stratification with the FRISBEE models (all fractures 0.69 [95%CI 0.67-0.72], MOFs 0.71 [95%CI 0.68-0.74], central fractures 0.72 [95%CI 0.69-0.75]). There was a strong gradient of risk for predicting fracture outcomes per SD increase (HRs from 1.98 to 2.26) and across risk tertiles (HRs for middle vs lowest from 2.25 to 2.41, HRs for highest vs lowest from 4.70 to 6.50). However, risk was overestimated for all fractures (calibration-in-the-large 0.63, calibration slope 0.63), MOF (calibration-in-the-large 0.51, calibration slope 0.57) and central fractures (calibration-in-the-large 0.55, calibration slope 0.60).
conclusionsFRISBEE 5-year prediction models were externally validated to stratify fracture risk similar to the derivation cohort, but would need recalibration for Canada as risk was overestimated.
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