Risk for future fractures in postmenopausal women

Two new studies in the May 24 issue of The Archives of Internal Medicine, one of the JAMA/Archives journals, examines methods to accurately classify postmenopausal women with reduced bone mass and identify those with increased risk for future fractures.

According to information in the articles, the most important predictor of bone fracture in postmenopausal women without a previous fracture is bone mineral density (BMD). As bone mineral density decreases (as measured in terms of T scores) the risk of fracture increases. Women with even moderately low T scores (those with osteopenia), are also at risk for bone fracture. However, there is little agreement on the level of bone reduction (i.e., the ideal T score) at which to begin treatment (including dietary and pharmacological interventions) to reduce the risk for fractures.

According to the World Health Organization, a T score of -2.5 or lower indicates osteoporosis, and a T score of -1.0 to -2.49 indicates osteopenia. Many clinicians and reimbursement sources use the WHO definition of osteoporosis as the threshold for treatment. According to the National Osteoporosis Foundation (NOF), women with a T score of -2.0 or less or -1.5 or less with at least one risk factor should be treated to reduce the risk of fracture.

Ethel S. Siris, M.D., of Columbia-Presbyterian Medical Center, New York, and colleagues used data from 149,524 white postmenopausal women (average age, 64.5 years) enrolled in the National Osteoporosis Risk Assessment (NORA) study to examine the relationship between different treatment thresholds (based on T scores) and fracture incidence within a year of bone mineral density testing. Women received a bone mineral density assessment at the beginning of the study and were followed up for new fractures for 12 months.

New fractures were reported by 2,259 women, including 393 hip fractures, but only 6.4 percent of women reporting fractures had T scores of -2.5 or less (indicating osteoporosis, according to WHO criteria). The researchers write that although these women had the highest fracture rates, they experienced only 18 percent of the osteoporotic fractures and 26 percent of the hip fractures.

According to the NOF treatment guidelines, 22.6 percent of the women would be considered for treatment (having a T score of -2.0 or less, or -1.5 or less with at least one risk factor). Although fracture rates were lower in these women, they experienced 45 percent of osteoporotic fractures and 53 percent of hip fractures.

“Only 18 percent of the NORA women who had fractures would have been treatment candidates if the intervention threshold had been set at -2.5 or less,” the researchers write. “This would result in no intervention in 82 percent of the women who actually experienced a new fracture during the first year after BMD was measured.”

“The observation that more than half (52 percent) of the NORA women experiencing an incident [new] osteoporotic fracture within one year had a BMD T score of -1.0 to -2.5 underscores the unmet need to identify those women who are most likely to fracture and might benefit from targeted pharmacological intervention,” write the authors.

“We conclude that substantial reductions in the population burden of osteoporotic fractures experienced by postmenopausal women cannot be accomplished simply by aggressively treating women with T scores of -2.5 or less,” the authors write.

In a related article in the May 24 issue of The Archives of Internal Medicine, Paul D. Miller, M.D., of the Colorado Center for Bone Research, Lakewood, and colleagues developed a classification system to identify women with osteopenia (T scores of -2.5 to -1.0) who may be at an increased risk of fracture within one year of bone mineral density testing.

The researchers studied data from 57,421 postmenopausal white women from the NORA study with baseline T scores of -2.5 to -1.0 who were followed up for one year after bone mineral density testing for new fractures. The researchers used 32 risk factors for fracture to build an algorithm to predict future fracture events. They used this algorithm to see if it could correctly identify the women who experienced fractures over the one year follow-up period.

During the follow up period, 1,130 women had new fractures. Previous fracture, a T score at a peripheral site (e.g., heel, forearm) of -1.8 or less, self-rated poor health status, and poor mobility were identified as the most important predictors of fracture, and 55 percent of the women were identified as being at an increased risk for fracture.

The researchers found that women with a previous fracture, regardless of T score, had a risk of 4.1 percent, and women with T scores of -1.8 or less or with poor health status had a risk of 2.2 percent. Women with poor mobility had a risk of 1.9 percent. Altogether, the researchers’ algorithm correctly classified 74 percent of the women who experienced a fracture.

“This classification tool [the algorithm] accurately identified postmenopausal women with peripheral T scores of -2.5 to -1.0 who are at increased risk of fracture within 12 months,” write the authors. “It can be used in clinical practice to guide assessment and treatment decisions.”

http://archinternmed.com

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