The Fracture Risk (FRISK) Score is a new method for predicting fracture risk in patients with osteoporosis. The FRISK is obtained from an equation that incorporates bone mineral density (BMD) at the spine and femoral neck, history of falls in the past year, number of previous fractures, and body weight. Lead author Margaret Joy Henry, PhD, (University of Melbourne, Victoria, Australia) reports in Radiology that the score successfully predicted 75% of fractures 2 years after baseline measurements in a group of 231 women over age 60 with a history of previous low-trauma fracture.1

"The value of papers like FRISK is to demonstrate the variables that need to be considered in assessing osteoporotic patients. The specific equations are rarely clinically useful." —Kerry Siminoski, MD, FRCPC
"Currently, doctors use T-scores (comparison to a young reference group) and Z-scores (comparison to age-matched peers) at separate anatomical sites to assess a patient's fracture risk. However, there has not been a method to combine the contribution of the different anatomical sites to an overall individual's fracture risk. This study provides an evidence-based equation to aid doctors in combining fracture risk factors to help in assessing their patients' fracture risk," Dr. Henry told CIAOMed.

BMD, Previous Fractures, Falls, Weight, All Included

The FRISK score is calculated from the following equation: 9.304 – 4.735 (spine BMD) – 4.530 (femoral neck BMD) -+ 1.127 (fracture score) + 0.344 (number of previous falls) +  0.037 (body weight in kg).

"These risk factors were the best predictors of fracture out of a group of easily accessible risk factors for fracture," Dr. Henry said.

The BMD was measured at the posteroanterior spine and the left femoral neck with a Lunar DPX-L densitometer (Madison, Wisconsin). The falls score was determined from the number of falls in the previous year (score of 1 = none or few falls; 2 = falls "a few times"; 4 = regular falls).

For the subsequent 2-year period, patients with a baseline FRISK score of 5.4 or more were significantly more likely to have a fracture than those with lower scores. "For one unit increase in FRISK score, the odds of sustaining a fracture increased by 1.75," the authors write. They note that a 1.0 standard deviation decrease in spine BMD increased FRISK score by 0.6, similar to the effect of decreased femoral neck BMD by 1.1 standard deviations, increasing body weight by 17 kg, increasing the number of previous fractures by 1.9, or increasing the falls score by 0.6.

When applied to longitudinal data, the baseline FRISK score identified 75% of patients who sustained a fracture over the next 2 years, with a specificity of 68%.

But Some Doubt FRISK's Usefulness

Although Dr. Henry suggests that this equation could be routinely calculated for patients who have had BMD scans, other osteoporosis experts are not so sure it would be useful. Kerry Siminoski, MD, FRCPC, reviewed the FRISK study for CIAOMed. Dr. Siminoski, who is in the Departments of Radiology and Diagnostic Imaging at the University of Alberta, Edmonton, Canada, was lead author on the recently published Canadian Association of Rheumatologists' "Recommendations for Bone Mineral Density Reporting in Canada."2

"I don't see how a clinician would use this formula," Dr. Siminoski told CIAOMed. "In order to apply it, you have BMD results, fall history, fracture history, and weight, which are the things that currently drive intervention and monitoring. If the FRISK formula is used and the patient has a 'positive' score, what would one do differently? What if the score is 'negative'? Would one be less aggressive? No."

Dr. Siminoski also pointed to some specific problems with the FRISK approach, including the following:

• The machine-specific nature of BMD technology. "Readers who use other types of machine than Lunar (Hologic and Norland being the most common), cannot necessarily just plug in their own BMD results on individual patients."
• The formula is complex, with coefficients to 3 decimal places that need to be multiplied by some variables (like BMD) that also have 3 decimal places.
• The FRISK was tested in a small group of subjects: "Often, the predictive value deteriorates as such formulae are applied to other populations, from which the original equations were not derived."
• The formula does not include either sex or age: "Sex is the single greatest fracture predictor in osteoporosis, and age is the second; BMD is the third. This problem originates from the original case:control methodology, which used age-matched controls, and which further adjusted for age."
• The coefficients show that the BMD values are far more important than previous fracture, falls, or weight, and "the authors themselves present data in the paper showing that the additional variables add only a small amount of additional accuracy."

The Canadian BMD Reporting Guidelines were not based on modeling, "which always imposes assumptions," Dr. Siminoski said. The guidelines ended up incorporating sex, age, BMD (with an approach useable by the different machines), fracture history, and steroid history.

"Patients are given a fracture risk category, and this is specifically used to direct therapy and the timing of follow-up BMD studies," Dr. Siminoski said. "The value of papers like FRISK is to demonstrate the variables that need to be considered in assessing osteoporotic patients. The specific equations are rarely clinically useful."

Reference

1. Henry MJ, Pasco JA, Sanders KM, et al. Fracture risk (FRISK) score: Geelong Osteoporosis Study. Radiology. 2006;241:190-196.
2. Siminoski K, Leslie WD, Frame H, et al. Recommendations for bone mineral density reporting in Canada. Can Assoc Radiol J. 2005;56:178-188.