CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Clinical Risk Factors for Osteoporosis in Ireland and the UK: A Comparison of FRAX and QFractureScores
Authors
N. M. Cummins
O. M. O\u27Driscoll
+3 more
E. K. Poku
S. H. Ralston
Mark R. Towler
Publication date
1 August 2011
Publisher
Scholars\u27 Mine
Abstract
Recently two algorithms have become available to estimate the 10-year probability of fracture in patients suspected to have osteoporosis on the basis of clinical risk factors: the FRAX algorithm and QFractureScores algorithm (QFracture). The aim of this study was to compare the performance of these algorithms in a study of fracture patients and controls recruited from six centers in the United Kingdom and Ireland. A total of 246 postmenopausal women aged 50-85 years who had recently suffered a low-trauma fracture were enrolled and their characteristics were compared with 338 female controls who had never suffered a fracture. Femoral bone mineral density was measured by dual-energy X-ray absorptiometry, and fracture risk was calculated using the FRAX and QFracture algorithms. The FRAX algorithm yielded higher scores for fracture risk than the QFracture algorithm. Accordingly, the risk of major fracture in the overall study group was 9.5% for QFracture compared with 15.2% for FRAX. For hip fracture risk the values were 2.9% and 4.7%, respectively. The correlation between FRAX and QFracture was R = 0.803 for major fracture and R = 0.857 for hip fracture (P ≤ 0.0001). Both algorithms yielded high specificity but poor sensitivity for prediction of osteoporosis. We conclude that the FRAX and QFracture algorithms yield similar results in the estimation of fracture risk. Both of these tools could be of value in primary care to identify patients in the community at risk of osteoporosis and fragility fractures for further investigation and therapeutic intervention. © 2011 Springer Science+Business Media, LLC
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Missouri University of Science and Technology (Missouri S&T): Scholars' Mine
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:scholarsmine.mst.edu:che_b...
Last time updated on 05/03/2023