Prior research indicates that fractures, as the most clinically relevant endpoint of osteoporosis, are associated with excess disability and mortality. Although the Fracture Risk Assessment Tool (FRAX)—currently, the most widely used tool for fracture risk assessment—has improved fracture prediction rates upon those achieved with bone mineral density T-scare method alone, its performance rate has been shown to vary among different study populations. “FRAX was calibrated with data from a predominantly Caucasian cohort,” says Qing Wu, MD, ScD. “For US minorities, FRAX estimated are adjusted based on race-specific hip fracture incidence and race-specific mortality rates, but this is not empirically based. Nevertheless, the hypothesis that racial/ethnic differences that influence fracture risk were not adequately taken into account by FRAX has never been tested before. Determining whether FRAX performs differently in people with different race and genetic backgrounds would allow further improvement in fracture prediction.”
Using genomic data on nearly 24,000 postmenopausal woman participants of the Women’s Health Initiative (WHI) study, Dr. Wu and colleagues conducted a study—published in first calculated genetic risk scores (GRSs) from 14 fracture-associated single nucleotide polymorphisms for each participant. FRAX without bone mineral density was used to estimate fracture probability. “We compared the FRAX-estimated, 10-year fracture risk with observed data among this patient population, stratified by race,” explains Dr. Wu. “The ratio between FRAX-predicted and observed fracture probability was then calculated for each group (race and GRS). Multivariable Cox proportional hazard models were employed to assess the effect GRS and race had on time to the first fracture or mortality.”
Probabilities by GRS & Race
The researchers found that FRAX significantly overestimated 10-year major osteoporotic fracture (MOF) probability among WHI participants. The most significant overestimations were seen among women who had a low GRS, with a FRAX-predicted probability of 6.02% versus an observed probability of 3.74%, or a predicted/observed ratio (POR) of 1.61, compared with PORs of 1.38 and 1.40 in the high and median GRS groups. “Compared with the low GRS group, the 10-year probabilities of MOF adjusted for FRAX score were 21% and 30% higher in the median and high GRS group, respectively,” adds Dr. Wu. While FRAX also overestimated 10-year hip fracture risk in all GRS groups, PORs were similar across all three.
According to Dr. Wu, the study results “provide compelling evidence that FRAX significantly overestimates 10-year MOF probability in postmenopausal women across all racial groups (Figure).” The greatest overestimation was observed among Asian-American women, with a POR of 3.5, followed by African-American women, with a POR of 2.59. Interestingly, “Asian-American, African-American, and Hispanic-American women had 78%, 76%, and 56% lower risks of hip fracture, respectively, than did Caucasian women after the FRAX score was adjusted,” explains Dr. Wu. FRAX also overestimated 10-year hip fracture risk among all racial groups, except American-Indian women, among whom the POR was 0.91.
“Fully integrating genetic profiling and racial factors into the existing fracture assessment model is very likely to improve the accuracy of fracture prediction,” notes Dr. Wu. “Thus, developing racial/ethnic-specific, individualized fracture risk-assessment models may provide more accurate fracture risk assessment. Further studies, especially those including men, larger samples of minorities, and more comprehensive fracture-associated genetic variants, are warranted. In the meantime, our findings demonstrate that the effect of race in osteoporotic fracture prediction has not adequately been taken into account by existing FRAX models,” says Dr. Wu. “The fracture risk derived from current FRAX scores should be interpreted with caution by clinicians.”
Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles