Cappelle SI, et al. – Here, researchers depict the methodology of the FRISBEE study and aim to compare the distribution of clinical risk factors (CRFs) in this cohort with those reported in other large studies. In light of these outcomes, they observed considerable heterogeneity in the prevalence of CRFs between cohort studies. The effect of these differences on the predictive value of a specific CRF is unknown. They will construct a predictive model calibrated to the Belgian population. More importantly, the FRISBEE study ought to allow us to ascertain the predictive value of newly recognized CRFs in addition to the FRAX® algorithm to reliably estimate fracture risk.

Methods

• For this research, they designed a large prospective study {(the ‘Fracture Risk Brussels Epidemiological Enquiry) (FRISBEE)} .
• This study prospectively assesses a cohort of 3560 post–menopausal women (aged 60–85 years) followed yearly for the occurrence of fragility fractures.
• Multiple validated CRFs, densitometry (DXA) values and intake of medication was systematically registered at baseline.
• The distribution of the FRISBEE CRFs has been compared with the distributions of CRFs in the cohorts used to develop the FRAX® model and also in more recent cohorts.
• For these recent cohorts, they concentrated on CRFs not included in FRAX®.

Results

• They current study showed that the most frequently encountered CRFs utilized in FRAX® were a prior fragility fracture (27.1%) and a parental history of hip fracture (13.4%).
• The prevalence of some CRFs not integrated in FRAX® was relatively high, for example, the utilization of proton pump inhibitors (20.8%) and a history of fall(s) (19.7%).
• The prevalence of many CRFs was quite variable between cohorts; for example, the prevalence of ‘personal prior fragility fracture’ ranged from 9% to 51%.