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SP0119 Predicting fracture risk: accuracy and feasibility of tools
  1. AA Marques
  1. Rheumatology, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal

Abstract

Several therapeutic options and screening strategies are available to effectively decrease fracture risk. However the main clinical challenge still consists in accurately identifying and selecting individuals for bone densitometry and for pharmacological treatment, in order to increase efficiency and minimize individual and societal costs.

The World Health Organization provided an operational definition of osteoporosis as a bone mineral density (BMD) that lies 2.5 or more standard deviations below the average value for young healthy women of the same gender and ethnical background [T-score ≤-2.5]. However, BMD has limited sensitivity and specificity in the prediction of fracture. In fact, a large number of conditions have been firmly established as risk factors for the occurrence of fragility fractures, independently from BMD. These have been combined into prediction algorithms to estimate fracture probability and are currently available for calculate the risk of fractures. However, the existing tools differ in many relevant aspects: from their own feasibility, to the number and availability of clinical risk factors included, the accessibility of BMD measurements and, finally, their performance in different settings.

With this session we aim to identify and synthesize the best available evidence on the accuracy and feasibility of the currently available tools designed to predict fracture risk.

Several therapeutic options and screening strategies are available to effectively decrease fracture risk. However the main clinical challenge still consists in accurately identifying and selecting individuals for bone densitometry and for pharmacological treatment, in order to increase efficiency and minimize individual and societal costs.The World Health Organization provided an operational definition of osteoporosis as a bone mineral density (BMD) that lies 2.5 or more standard deviations below the average value for young healthy women of the same gender and ethnical background [T-score ≤-2.5]. However, BMD has limited sensitivity and specificity in the prediction of fracture. In fact, a large number of conditions have been firmly established as risk factors for the occurrence of fragility fractures, independently from BMD. These have been combined into prediction algorithms to estimate fracture probability and are currently available for calculate the risk of fractures. However, theexisting tools differ in many relevant aspects: from their own feasibility, to the number and availability of clinical risk factors included, the accessibility of BMD measurements and, finally, their performance in different settings.With this session we aim to identify and synthesize the best available evidence on the accuracy and feasibility of the currently available tools designed to predict fracture risk.

Disclosure of Interest None declared

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