Affiliation: | 1. Osteoporosis and Bone Biology, Garvan Institute of Medical Research, Sydney, Australia;2. Osteoporosis and Bone Biology, Garvan Institute of Medical Research, Sydney, Australia Vinmec Research Institute of Stem Cell and Gene Technology, Hanoi, Vietnam;3. Department of Data and Analytics, Máxima Medical Centre, Veldhoven, The Netherlands;4. Department of Medicine, McMaster University, Hamilton, Canada;5. Research Institute of the McGill University Health Centre, Montreal, Canada;6. Department of Internal Medicine, Subdivision of Rheumatology, Maastricht University Medical Center, Research School Nutrim, Maastricht, The Netherlands Department of Internal Medicine, VieCuri Medical Centre of Noord-Limburg, Venlo, The Netherlands Biomedical Research Institute, University Hasselt, Hasselt, Belgium;7. Biomedical Research Institute, University Hasselt, Hasselt, Belgium;8. Department of Medicine, McGill University, Montreal, Canada;9. Department of Medicine, University of Calgary, Calgary, Canada;10. Department of Medicine, University of Toronto, Toronto, Canada;11. Department of Medicine, Dalhousie University, Halifax, Canada;12. Faculty of Medicine, Memorial University, St. John's, Canada;13. School of Public Health, University of Minnesota, Twin Cities, Minneapolis, MN, USA;14. Department of Medicine and Endocrinology, University of British Columbia, Vancouver, Canada;15. Osteoporosis and Bone Biology, Garvan Institute of Medical Research, Sydney, Australia Clinical School, St Vincent's Hospital, Faculty of Medicine, UNSW Sydney, Sydney, Australia |
Abstract: | Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7–15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of −1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research. |