Discriminating value of HR-pQCT for fractures in women with similar FRAX scores: A substudy of the FRISBEE cohort.

Areal bone mineral density (aBMD) has a low sensitivity to identify women at high fracture risk. The FRAX algorithm, by combining several clinical risk factors, might improve fracture prediction compared to aBMD alone. Several micro-architectural and biomechanical parameters which can be measured by high-resolution peripheral quantitative computed tomography (HR-pQCT) are associated with fracture risk. HR-pQCT in combination or not with finite element analysis (FEA) may be used to improve bone strength prediction. Our aim was to assess whether HR-pQCT measurements (densities, cortical and trabecular microarchitecture, biomechanical proprieties assessed by FEA) had an added value in predicting fractures in a subgroup of women belonging to the Belgian FRISBEE cohort. One hundred nineteen women who sustained a fracture (aged 60 to 85 years) during the initial follow-up of our cohort had a radius and tibia examination by HR-pQCT and were compared with controls matched for their FRAX score at baseline. We found that low distal radius total (OR = 1.41 [1.07-1.86] per SD, p < 0.05) and trabecular densities (OR = 1.45 [1.10-1.90], p < 0.01), trabecular number (OR = 1.32 [1.01-1.72], p < 0.05), intra individual distribution of separation (OR = 0.73 [0.54-0.99], p < 0.05) as several FEA parameters were significantly associated with fractures. At the distal tibia, impaired cortical density (OR = 1.32 [1.03-1.70] per SD, p < 0.05) and thickness (OR = 1.29 [1.01-1.63], p < 0.05) and apparent modulus (OR = 1.30 [1.01-1.66], p < 0.05) were significantly correlated with fractures. A low ultra distal radial aBMD (UDR) measured at the time of HR-pQCT was significantly associated with fractures (OR = 1.67 [1.22-2.28], p < 0.01). Women from both groups were followed further after the realization of the HR-pQCT and 46 new fractures were registered. In this second part of the study, low UDR aBMD (OR = 1.66 [1.18-2.35], p < 0.01), total (OR = 1.48 [1.08-2.03], p < 0.05), cortical (OR = 1.40 [1.04-1.87], p < 0.05) and trabecular (OR = 1.37 [1.01-1.85], p < 0.05) densities or apparent modulus (OR = 1.49 [1.07-2.05], p < 0.05) at the radius were associated with a significant increase of fracture risk. At the tibia, only the cortical density was significantly associated with the fracture risk (OR = 1.34 [1.02-2.76], p < 0.05). These results confirm the interest of HR-pQCT measurements for the evaluation of fracture risk, also in women matched for their baseline FRAX score. They also highlight that UDR aBMD contains pertinent information.

Distribution of clinical risk factors for fracture in a Brussels cohort of postmenopausal women: The FRISBEE study and comparison with other major cohort studies.

OBJECTIVES: The estimation of fracture risk using clinical risk factors (CRFs) is of primary concern in osteoporosis management, but only some risk factors have been thoroughly evaluated and incorporated in predictive models. We have launched a large prospective study, the 'Fracture Risk Brussels Epidemiological Enquiry' (FRISBEE), to develop a new predictive model for osteoporotic fractures. The aims of this report are to describe the methodology of the FRISBEE study and to compare the distribution of CRFs in our cohort with those reported in other large studies. STUDY DESIGN: FRISBEE is a new study that prospectively evaluates 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 were 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 as well as in more recent cohorts. For these recent cohorts, we focused on CRFs not included in FRAX®. RESULTS: The most frequently encountered CRFs used 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, such as the use 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%. CONCLUSION: We found considerable heterogeneity in the prevalence of CRFs between cohort studies. The impact of these differences on the predictive value of a particular CRF is unknown. We will construct a predictive model calibrated to the Belgian population. More importantly, the FRISBEE study should allow us to determine the predictive value of newly recognized CRFs in addition to the FRAX® algorithm to reliably estimate fracture risk.