Fragility Fractures in Postmenopausal Women: Development of 5-Year Prediction Models Using the FRISBEE Study

Author:

Baleanu Felicia1ORCID,Moreau Michel2,Charles Alexia3,Iconaru Laura1,Karmali Rafik1,Surquin Murielle4,Benoit Florence4,Mugisha Aude4,Paesmans Marianne2,Rubinstein Michel5,Rozenberg Serge6,Bergmann Pierre37,Body Jean-Jacques13

Affiliation:

1. Department of Endocrinology, CHU Brugmann, Université Libre de Bruxelles, Brussels, Belgium

2. Data Centre, Inst. J. Bordet, Université Libre de Bruxelles, Brussels, Belgium

3. Translational Research Unit, CHU Brugmann, Université Libre de Bruxelles, Brussels, Belgium

4. Department of Geriatrics, CHU Brugmann, Université Libre de Bruxelles, Brussels, Belgium

5. Department of Nuclear Medicine, Ixelles Hospital, Université Libre de Bruxelles, Brussels, Belgium

6. Department of Gynecology, CHU St Pierre, Université Libre de Bruxelles, Brussels, Belgium

7. Department of Nuclear Medicine, CHU Brugmann, Université Libre de Bruxelles, Brussels, Belgium

Abstract

Abstract 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, although their external validation has shown significant differences in their risk prediction ability. Objective and Methods Using data from the Fracture Risk Brussels Epidemiological Enquiry study, a cohort of 3560 postmenopausal women aged 60 to 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, a history of fracture, and hip or spine BMD were predictors common to the 3 models. Excessive alcohol intake and the presence of comorbidities were specific additional CRFs for MOFs, a history of fall for all fractures, and rheumatoid arthritis for central fractures. Our models predicted the fracture probability at 5 years with an acceptable accuracy (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 3 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.

Funder

IRIS-Recherche

CHU Brugmann

Publisher

The Endocrine Society

Subject

Biochemistry (medical),Clinical Biochemistry,Endocrinology,Biochemistry,Endocrinology, Diabetes and Metabolism

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