Gordon FitzGerald1, Juliet E Compston, Roland D Chapurlat, Johannes Pfeilschifter, Cyrus Cooper, David W Hosmer, Jonathan D Adachi, Frederick A Anderson, Adolfo Díez-Pérez, Susan L Greenspan, J Coen Netelenbos, Jeri W Nieves, Maurizio Rossini, Nelson B Watts, Frederick H Hooven, Andrea Z LaCroix, Lyn March, Christian Roux, Kenneth G Saag, Ethel S Siris, Stuart Silverman, Stephen H Gehlbach. 1. 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
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.
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.
Authors: Melissa Premaor; Richard A Parker; Steve Cummings; Kris Ensrud; Jane A Cauley; Li-Yung Lui; Theresa Hillier; Juliet Compston Journal: J Bone Miner Res Date: 2013-01 Impact factor: 6.741
Authors: Gordon FitzGerald; Steven Boonen; Juliet E Compston; Johannes Pfeilschifter; Andrea Z LaCroix; David W Hosmer; Frederick H Hooven; Stephen H Gehlbach Journal: J Bone Miner Res Date: 2012-09 Impact factor: 6.741
Authors: Daniel Prieto-Alhambra; Melissa O Premaor; Francesc Fina Avilés; Eduard Hermosilla; Daniel Martinez-Laguna; Cristina Carbonell-Abella; Xavier Nogués; Juliet E Compston; Adolfo Díez-Pérez Journal: J Bone Miner Res Date: 2012-02 Impact factor: 6.741
Authors: Melissa Orlandin Premaor; Lesley Pilbrow; Carol Tonkin; Richard A Parker; Juliet Compston Journal: J Bone Miner Res Date: 2010-02 Impact factor: 6.741
Authors: F H Hooven; J D Adachi; S Adami; S Boonen; J Compston; C Cooper; P Delmas; A Diez-Perez; S Gehlbach; S L Greenspan; A LaCroix; R Lindsay; J C Netelenbos; J Pfeilschifter; C Roux; K G Saag; P Sambrook; S Silverman; E Siris; N B Watts; F A Anderson Journal: Osteoporos Int Date: 2009-05-26 Impact factor: 4.507