z-logo
open-access-imgOpen Access
Potential Extensions of the US FRAX Algorithm
Author(s) -
L. Joseph Melton,
Elizabeth J. Atkinson,
Sara J. Achenbach,
John А. Kanis,
Terry M. Therneau,
Helena Johansson,
Sundeep Khosla,
Shreyasee Amin
Publication year - 2012
Publication title -
journal of osteoporosis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 19
eISSN - 2090-8059
pISSN - 2042-0064
DOI - 10.1155/2012/528790
Subject(s) - frax , medicine , algorithm , computer science , pathology , bone mineral , osteoporosis , osteoporotic fracture
To determine if the revised US FRAX can identify those at high risk for fractures at any skeletal site, we studied 250 women and 249 men ≥40 years old from an age-stratified random sample of Rochester, MN residents. At baseline, femoral neck (FN) bone density was assessed, as were the clinical risk factors included in FRAX, along with additional fracture risk factors such as bone turnover markers and fall history. Fracture ascertainment through periodic interviews and comprehensive medical record review was performed over 10 years of followup. In both women and men, a higher FRAX probability at baseline was associated with greater subsequent likelihood of a major osteoporotic fracture. However, a relative 10% increase in the FRAX 10-year fracture probability was also associated with a 1.4-fold increase (95% confidence interval (CI) 1.1–1.7) in other fractures in women and a 1.7-fold increase (95% CI 0.8–3.1) in men. Furthermore, FRAX predicted asymptomatic vertebral fractures and fractures generally in both sexes. The addition of risk factors not currently included in FRAX did not appear to improve the accuracy of fracture risk prediction. FRAX may provide a conservative estimate of risk for major osteoporotic fractures, but it also predicts fractures generally

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom