
A new study that shows how the inclusion of falls history, in addition to clinical risk factors (CRFs) and bone mineral density (BMD) values, would greatly improve the accuracy of fracture prediction models has been presented by researchers from the MRC Lifecourse Epidemiology Unit in Southampton, UK.
The research findings were presented today at the European Congress on Osteoporosis & Osteoarthritis in Valencia, Spain.
Using results from the Hertfordshire Cohort Study, the investigators examined the relative contributions of CRFs, BMD and falls history to fracture prediction. They concluded that fall history is an independent risk factor for fracture. Its inclusion in a fracture prediction model in men (in addition to CRFs and BMD) improved accuracy by 6%. The authors show that such models would have positive predictive values of 21.5% and 29.8% in men and women, respectively.
"Osteoporotic fractures can have debilitating effects on individuals and targeting preventative treatments to those at the highest risk is of great importance." Said Dr Mark Edwards, Academic Clinical Fellow at the MRC Lifecourse Epidemiology Unit, University of Southampton.
Source: Eurekalert