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Center for Outcomes Research (G.F., D.W.H., F.A.A., F.H.H., S.H.G.) University of Massachusetts Medical School, Worcester, Massachusetts 01605; University of Cambridge School of Clinical Medicine (J.E.C.), Addenbrooke's Hospital, Cambridge CB2 0QQ, United Kingdom; Division of Rheumatology (R.D.C.), INSERM Unité Mixte de Recherche 1033, Université de Lyon, and Department of Orthopedics and Rheumatology, Hôpital E. Herriot, 69003 Lyon, France; Department of Internal Medicine III (J.P.), Alfried Krupp Krankenhaus, Essen D-45276, Germany; Medical Research Council Lifecourse Epidemiology Unit (C.C.), University of Southampton, Southampton General Hospital, Southampton SO16 6YD, United Kingdom; National Institute for Health Research Musculoskeletal Biomedical Research Unit (C.C.), University of Oxford, Oxford OX1 3QX, United Kingdom; St Joseph's Hospital (J.D.A.), McMaster University, Hamilton, Ontario, Canada L8N 1Y2; Hospital del Mar-IMIM-Autonomous University of Barcelona (A.D.-P.), 08035 Barcelona, Spain; Research Network on Aging and Frailty, Le Fonds européen de développement régional (European Regional Development Fund), Instituto de Salud Carlos III, 28029 Madrid, Spain; University of Pittsburgh (S.L.G.), Pittsburgh, Pennsylvania 15213; Department of Endocrinology (J.C.N.), VU University Medical Centre, Amsterdam 2131PM Hoofddorp, The Netherlands; Helen Hayes Hospital and Columbia University (J.W.N.), West Haverstraw, New York 10993; Section of Rheumatology (M.R.), Department of Medicine, University of Verona, 37129 Verona, Italy; Mercy Health (N.B.W.), Cincinnati, Ohio 45236; Fred Hutchinson Cancer Research Center (A.Z.L.), Seattle, Washington 98109; University of Sydney Institute of Bone and Joint Research and Department of Rheumatology (L.M.), Royal North Shore Hospital, 2006 Sydney, Australia; Paris Descartes University and Cochin Hospital (C.R.), 75014 Paris, France; Division of Clinical Immunology and Rheumatology (K.G.S.), University of Alabama at Bir
Published: March 2014
AI Article Synopsis
Article Abstract
Context: Several fracture prediction models that combine fractures at different sites into a composite outcome are in current use. However, to the extent individual fracture sites have differing risk factor profiles, model discrimination is impaired.
Objective: The objective of the study was to improve model discrimination by developing a 5-year composite fracture prediction model for fracture sites that display similar risk profiles.
Design: This was a prospective, observational cohort study.
Setting: The study was conducted at primary care practices in 10 countries.
Patients: Women aged 55 years or older participated in the study.
Intervention: Self-administered questionnaires collected data on patient characteristics, fracture risk factors, and previous fractures.
Main Outcome Measure: The main outcome is time to first clinical fracture of hip, pelvis, upper leg, clavicle, or spine, each of which exhibits a strong association with advanced age.
Results: Of four composite fracture models considered, model discrimination (c index) is highest for an age-related fracture model (c index of 0.75, 47 066 women), and lowest for Fracture Risk Assessment Tool (FRAX) major fracture and a 10-site model (c indices of 0.67 and 0.65). The unadjusted increase in fracture risk for an additional 10 years of age ranges from 80% to 180% for the individual bones in the age-associated model. Five other fracture sites not considered for the age-associated model (upper arm/shoulder, rib, wrist, lower leg, and ankle) have age associations for an additional 10 years of age from a 10% decrease to a 60% increase.
Conclusions: After examining results for 10 different bone fracture sites, advanced age appeared the single best possibility for uniting several different sites, resulting in an empirically based composite fracture risk model.
