November 24, 2009 — Two new algorithms can predict the risk for osteoporotic fracture in a primary care setting without the need for laboratory measurements and will help identify patients at high risk who could benefit from risk-reducing interventions, according to a new report published in the November 19 Online First issue of the BMJ.
"Osteoporotic fractures are a major and increasing cause of morbidity in the population and a considerable burden to health services. Hip fractures, in particular, result in considerable pain, loss of function, and admission to hospital, making prevention a high priority for patients and physicians and for public health," write Julia Hippisley-Cox, MD, and Carol Coupland, MD, from the University of Nottingham, Nottingham, United Kingdom. "The challenge now is to improve methods for accurate identification of individuals at high risk who might benefit from a therapeutic or preventive intervention."
Two New Algorithms Developed
To that end, the investigators developed and validated 2 new fracture risk algorithms, called QFractureScores, for their value in estimating an individual's 10-year risk for osteoporotic or hip fracture.
They also compared the performance of the new algorithms vs the established fracture risk assessment (FRAX) algorithm, which includes age, sex, height, weight, previous fracture, parental history of hip fracture, current smoking, glucocorticoid treatment, rheumatoid arthritis, secondary osteoporosis, and 3 or more units of alcohol per day.
Another version of the FRAX includes bone mineral density measurements in the assessment of fracture risk, but this was not used as a comparator, the authors explain.
In building the QFractureScores, the authors collected data from 357 general practices in England and Wales on 1,183,663 women and 1,174,232 men aged 30 to 85 years during a 15-year period and recorded the diagnoses of incident osteoporotic fracture (vertebral, distal radius, or hip) and incident hip fracture.
There were 24,350 incident diagnoses of osteoporotic fracture in women and 7934 in men and 9302 incident diagnoses of hip fracture in women, and 5424 in men.
Risk Factors Shown
The data showed that the risk factors for fracture in men were age, body mass index, smoking status, alcohol use, rheumatoid arthritis, cardiovascular disease, type 2 diabetes, asthma, use of tricyclic antidepressants, history of falls, and liver disease. These variables were included in the QFractureScores algorithm.
The risk factors for fracture in women were the use of hormone replacement therapy, smoking status, use of alcohol, parental history of osteoporosis, rheumatoid arthritis, cardiovascular disease, type 2 diabetes, asthma, tricyclic antidepressants, use of corticosteroids, history of falls, menopausal symptoms, chronic liver disease, gastrointestinal tract malabsorption and other endocrine disorders, age, and body mass index. These factors were included in the QFractureScores algorithm.
The QFractureScore for estimating the 10-year absolute risk for osteoporotic fracture and hip fracture shows some evidence of improved discrimination and calibration vs the FRAX algorithm, the authors write.
It extends the age range and quantifies additional risk factors not fully taken into account by FRAX, including falls, type 2 diabetes, cardiovascular disease, use of hormone replacement therapy, menopausal symptoms, and use of tricyclic antidepressants.
An advantage of the new algorithm is that it does not require laboratory testing or clinical measurements, they add.
The study also provides information on risks associated with different types and doses of hormone replacement therapy. There was an overall protective effect of hormone replacement therapy with a decreased risk with unopposed estrogen, which was more marked for vertebral, distal radial, and hip fractures combined vs hip fracture alone. These findings are consistent with those from the Women's Health Initiative and other studies, the authors point out.
The QFractureScore was validated in general medical practices that did not contribute data to its development. The authors write that it had "good discrimination" or the ability to distinguish patients who subsequently had a fracture from those who did not.
Some Limitations
A limitation was that it used the same computer system that provided the information for the algorithm and so might contain "a degree of overoptimism," they note. In addition, missing values for alcohol use, body mass index, or smoking status for some of the patients might have led to some misclassification.
The authors conclude that further validation studies are needed to test the performance of the algorithms in independent populations in settings where they are likely to be used.
This study was funded by David Stables, medical director of EMIS, as part of a larger study examining risks and benefits of hormone replacement therapy. Dr. Hippisley-Cox has been codirector of QResearch, a not-for-profit organization that is a joint partnership between the University of Nottingham and EMIS. She is also director of ClinRisk, a producer of software that implements clinical risk algorithms within computer systems.
