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A risk assessment tool for predicting fragility fractures and mortality in the elderly.

J Bone Miner Res. 2020 May 27;: Authors: Tran T, Bliuc D, Pham HM, van Geel T, Adachi JD, Berger C, van den Bergh J, Eisman JA, Geusens P, Goltzman D, Hanley DA, Josse RG, Kaiser SM, Kovacs CS, Langsetmo L, Prior JC, Nguyen TV, Center JR, CaMos Research Group

Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current under-management of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and 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 ascertained though contact with a family member or obituary review. We used 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 inter-relationships, 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 (IQR: 7, 15). The prediction model included gender, age, BMD, 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 following hip fractures to 15 years following 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% following a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualisation of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. This article is protected by copyright. All rights reserved. PMID: 32460361 [PubMed - as supplied by publisher]

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