BES2021 Belgian Endocrine Society 2021 Abstracts (26 abstracts)
Fragility fractures in postmenopausal women: development of 5-year prediction models using the FRISBEE study
Baleanu Felicia 1 , Moreau Michel 2 , Charles Alexia 3 , Iconaru Laura 1 , Karmali Rafik 1 , Surquin Murielle 4 , Benoit Florence 4 , Mugisha Aude 4 , Paesmans Marianne 2 , Rubinstein Michel 5 , Rozenberg Serge 6 , Bergmann Pierre 3 , 7 & Body Jean- Jacques 1,3
1Department of Endocrinology, CHU Brugmann, Universite Libre de Bruxe lles, Brusse ls, Belgium; 2Data Centre, Inst. J. Bordet, Universite Libre de Bruxelles, Brussels, Belgium; 3Unite de Recherche Translationne lle, CHU Brugmann, Universite Libre de Bruxelles, Brussels, Belgium; 4Department of Geria trics, CHU Brugmann, Universite Libre de Bruxelles, Brussels, Belgium; 5Department of Nuclear Medicine, Ixelles Hospital, Universite Libre de Bruxelles, Brussels, Belgium; 6Department of Gynecology, CHU St Pierre, Universite Libre de Bruxe lles, Brussels, Belgium; 7Department of Nuclear Medicine, CHU Brugmann, Universite Libre de Bruxelles, Brussels, Belgium
Context: Individualized fracture risk may help to select patients requiring a pharmacological treatment for osteoporosis. FRAX and the Garvan fracture risk calculators are the most used tools, though their external validation has shown significant differences in their risk prediction ability.
Objective and Methods: Using data from the FRISBEE study, a cohort of 3560 post-menopausal women aged 60-85 years, we aimed to construct original 5-year fracture risk prediction models using validated clinical risk factors (CRFs). Three models of competing risk analysis were developed to predict major osteoporotic fractures (MOFs), all fractures and central fractures (femoral neck, shoulder, clinical spine, pelvis, ribs, scapula, clavicle, sternum).
Results: Age [sHR per year 1.05, 95% CI 1.04-1.06, P < 0.000 l (for MOFs); sHR per year 1.03, 95% CI 1.02- 1.04, P < 0.0001 (for all fractures); sHR per year 1.06, 95% CI 1.04-1.07, P < 0.001 (for central fractures)], a history of fracture [sHR 1.56, 95% CI 1.30-1.85, P < 0.001 (for MOFs); sHR 1.50, 95%CI 1.28-1.75, P < 0.0001 (for all fractures); sHR 1.47, 95% CI 1.22-1.77, P < 0.001 (for central fractures)] and total hip BMD [sHR 1.32, 95% CI 1.20-1.45, P < 0.0001 (for MOFs); sHR 1.36, 95%CI 1.28-1.46, P < 0.0001 (for all fractures); sHR 1.39, 95%CI 1.25-1.53, p < 0.0001 (for central fractures)] or spine BMD [ sHR 1.10, 95% CI 1.03-1.19, P = 0.0l (for MOFs); sHR 1.08, 95%CI 1.004-1.66, P = 0.04 (for central fractures)] were predictors common to the three models . Excessive alcohol intake (sHR 1.39, 95% CI 1.01-1.90, P = 0.04), and the presence of comorbidities (sHR 1.27, 95% CI 1.00 -1.60, P = 0.04) were specific additional CRFs for MOFs, a history of fall (sHR 1.32, 95%CI 1.12-1.57, P = 0.001) for all fractures and rheumatoid arthritis (sHR 2.42 95%CI 1.33-4.39, P = 0.004) for central fractures. Our models predicted the fracture probability at 5-years with an acceptable precision (Brier scores ≤0.1) and had a good discrimination power (area under the receiver operating curve of 0.73 for MOFs and 0.72 for central fractures) when internally validated by bootstrap. Three simple nomograms, integrating significant CRFs and the mortality risk were constructed for different fracture sites. In conclusion, we derived three models predicting fractures with an acceptable accuracy, particularly for MOFs and central fractures. The models are based on a limited number of CRFs and we constructed nomograms for use in clinical practice.
Keywords: osteoporosis, competing risk analysis, fracture, risk assessment, risk factors, BMD.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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