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FRAX, Falls, and Fracture Prediction: Predicting the Future: Comment on “ ‘Timed Up and Go’ Test and Bone Mineral Density Measurement for Fracture Prediction”

FRAX, Falls, and Fracture Prediction: Predicting the Future: Comment on “ ‘Timed Up and Go’ Test... These are interesting times for a clinician concerned about the prevention of fractures. Compared with even 10 years ago, the number of effective and Food and Drug Administration–approved treatments has increased several fold. Equally important, our ability to identify those at highest risk of fracture has improved so we can better target treatment to those most likely to benefit and avoid treatment in those who are at lower risk. The recent introduction of the fracture risk assessment tool (FRAX) is particularly noteworthy in this regard. FRAX is fracture risk assessment algorithm developed by the World Health Organization in 2008 that uses simple clinical risk factors (such as age, sex, body mass index, and previous fracture) and expected mortality to estimate the 10-year probability of hip and major osteoporotic fractures.1 FRAX was designed for use in primary care to assess fracture risk among men and women aged 40 to 90 years who have not previously received pharmacologic therapy to prevent fractures. Although not required, hip bone mineral density (BMD) is typically included in the FRAX calculation to further enhance fracture prediction. The FRAX calculator is available online (http://www.shef.ac.uk/FRAX) or as a smartphone application, and a number of practice guidelines, including those promoted by the National Osteoporosis Foundation in the United States, now incorporate FRAX calculations.2 Although FRAX is clearly a step in the right direction, there has already been considerable discussion among osteoporosis experts about how to improve it.3 One seemingly important omission is the lack of FRAX inputs that assess fall risk, which strongly predict hip and other nonvertebral fracture regardless of intrinsic skeletal strength. For example, previous prospective studies among older women have demonstrated that inability to rise from a chair without using one's arms is highly predictive of both falls and hip fracture,4 and repeated chair stand performance is highly predictive of hip fracture among older men.5 Importantly, these and other simple assessments of physical performance, such as gait speed, appear to predict fracture risk even after accounting for the effects of low BMD and other clinical risk factors for fracture. To improve existing fracture prediction algorithms, including FRAX, candidate fall risk factors should be easy to measure, reproducible, and strongly predictive of fracture independent of bone mass and other factors. Some fall risk factors are dichotomous, such as the presence or absence of previous falls or certain diseases (eg, Parkinson), and may apply to a relatively small proportion of the population. Preferred candidate fall risk factors are continuous and graded with evidence of a dose-response relationship with fracture. The Timed Up and Go test, or TUG, has many of these preferred attributes. In this issue, Zhu et al6 convincingly demonstrate a single baseline assessment of the TUG test (the time required to rise from a chair, walk 3 m, and returning to sit down) is associated with incident nonvertebral fracture in a population-based sample of older women followed for 10 years. In this study low, TUG performance, defined as more than 10.2 seconds, was observed in approximately one-third of women (mean age, 75 years) and was associated with a 54% increased risk of nonvertebral fracture (hazard ratio, 1.54; 95% CI, 1.15-2.07) after adjustment for BMD. Using newer reclassification techniques to assess the incremental value of individual risk factors,7 the authors found that after accounting for age and BMD, the addition of TUG performance correctly reclassified nonvertebral fracture risk in 8% of women (P = .01). Unfortunately, because TUG was the only physical performance measurement assessed in the study by Zhu et al,6 it cannot answer the important question of which performance test is optimal or if several different tests are better than one. Evidence from other studies suggest that gait speed, which is somewhat easier to measure than TUG, is as good as TUG for the prediction of falls.8 To build on the work of Zhu et al,6 next steps should include confirming these results in other prospective cohorts and then assembling and pooling the studies relating TUG (and perhaps other simple measurements of physical performance) to fracture risk in older individuals. Pooling studies will improve our confidence in the clinical utility of the TUG test across different populations and subgroups, allow investigators to search for dose-response relationships and assess optimal thresholds, and refine our ability to determine if TUG performance is associated with fracture risk independent of other risk factors for fracture. Ultimately, to assess the incremental value of adding the TUG test to FRAX, an important step will be to conduct prospective studies in which individual FRAX scores with and without the addition of TUG or other tests of physical performance are related to future fracture outcomes. Lastly, although improving our ability to predict fracture risk is itself important and useful, clinicians need to remember that existing pharmacologic treatments have been approved based on studies of individuals with low BMD and/or previous fracture. We have surprisingly little data that currently available treatments for fracture prevention, including the bisphosphonates, are effective when applied to those with elevated FRAX scores but without osteoporosis as defined by the presence of low BMD (hip or spine T-score less than −2.5) or preexisting vertebral fractures. Such studies need to be done to reassure clinicians that treatments prescribed on the basis of an elevated FRAX score, with or without TUG or other assessments of physical performance, will reduce the risk of fracture. Back to top Article Information Correspondence: Dr Bauer, University of California, San Francisco, 185 Berry, Ste 5700, San Francisco, CA 94107 (dbauer@psg.ucsf.edu). Financial Disclosure: Dr Bauer has received research support unrelated to this topic from Novartis and Amgen. References 1. Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E. FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int. 2008;19(4):385-39718292978PubMedGoogle ScholarCrossref 2. National Osteoporosis Foundation. Clinician's Guide to Prevention and Treatment of Osteoporosis. Washington, DC: National Osteoporosis Foundation; 2010 3. Kanis JA, Hans D, Cooper C, et al; Task Force of the FRAX Initiative. Interpretation and use of FRAX in clinical practice. Osteoporos Int. 2011;22(9):2395-241121779818PubMedGoogle ScholarCrossref 4. Cummings SR, Nevitt MC, Browner WS, et al; Study of Osteoporotic Fractures Research Group. Risk factors for hip fracture in white women. N Engl J Med. 1995;332(12):767-7737862179PubMedGoogle ScholarCrossref 5. Cawthon PM, Fullman RL, Marshall L, et al; Osteoporotic Fractures in Men (MrOS) Research Group. Physical performance and risk of hip fractures in older men. J Bone Miner Res. 2008;23(7):1037-104418302496PubMedGoogle ScholarCrossref 6. Zhu K, Devine A, Lewis JR, Dhaliwal SS, Prince RL. “Timed Up and Go” test and bone mineral density measurement for fracture prediction. Arch Intern Med. 2011;171(18):1655-1661Google ScholarCrossref 7. Donaldson MG, Cawthon PM, Schousboe JT, et al. Novel methods to evaluate fracture risk models. J Bone Miner Res. 2011;26(8):1767-177321351143PubMedGoogle ScholarCrossref 8. Viccaro LJ, Perera S, Studenski SA. Is timed up and go better than gait speed in predicting health, function, and falls in older adults? J Am Geriatr Soc. 2011;59(5):887-89221410448PubMedGoogle ScholarCrossref http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Internal Medicine American Medical Association

FRAX, Falls, and Fracture Prediction: Predicting the Future: Comment on “ ‘Timed Up and Go’ Test and Bone Mineral Density Measurement for Fracture Prediction”

Bauer, Douglas C.
Archives of Internal Medicine , Volume 171 (18) – Oct 10, 2011
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References (9)

Publisher
American Medical Association
Copyright
Copyright © 2011 American Medical Association. All Rights Reserved.
ISSN
0003-9926
eISSN
1538-3679
DOI
10.1001/archinternmed.2011.495
Publisher site
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Abstract

These are interesting times for a clinician concerned about the prevention of fractures. Compared with even 10 years ago, the number of effective and Food and Drug Administration–approved treatments has increased several fold. Equally important, our ability to identify those at highest risk of fracture has improved so we can better target treatment to those most likely to benefit and avoid treatment in those who are at lower risk. The recent introduction of the fracture risk assessment tool (FRAX) is particularly noteworthy in this regard. FRAX is fracture risk assessment algorithm developed by the World Health Organization in 2008 that uses simple clinical risk factors (such as age, sex, body mass index, and previous fracture) and expected mortality to estimate the 10-year probability of hip and major osteoporotic fractures.1 FRAX was designed for use in primary care to assess fracture risk among men and women aged 40 to 90 years who have not previously received pharmacologic therapy to prevent fractures. Although not required, hip bone mineral density (BMD) is typically included in the FRAX calculation to further enhance fracture prediction. The FRAX calculator is available online (http://www.shef.ac.uk/FRAX) or as a smartphone application, and a number of practice guidelines, including those promoted by the National Osteoporosis Foundation in the United States, now incorporate FRAX calculations.2 Although FRAX is clearly a step in the right direction, there has already been considerable discussion among osteoporosis experts about how to improve it.3 One seemingly important omission is the lack of FRAX inputs that assess fall risk, which strongly predict hip and other nonvertebral fracture regardless of intrinsic skeletal strength. For example, previous prospective studies among older women have demonstrated that inability to rise from a chair without using one's arms is highly predictive of both falls and hip fracture,4 and repeated chair stand performance is highly predictive of hip fracture among older men.5 Importantly, these and other simple assessments of physical performance, such as gait speed, appear to predict fracture risk even after accounting for the effects of low BMD and other clinical risk factors for fracture. To improve existing fracture prediction algorithms, including FRAX, candidate fall risk factors should be easy to measure, reproducible, and strongly predictive of fracture independent of bone mass and other factors. Some fall risk factors are dichotomous, such as the presence or absence of previous falls or certain diseases (eg, Parkinson), and may apply to a relatively small proportion of the population. Preferred candidate fall risk factors are continuous and graded with evidence of a dose-response relationship with fracture. The Timed Up and Go test, or TUG, has many of these preferred attributes. In this issue, Zhu et al6 convincingly demonstrate a single baseline assessment of the TUG test (the time required to rise from a chair, walk 3 m, and returning to sit down) is associated with incident nonvertebral fracture in a population-based sample of older women followed for 10 years. In this study low, TUG performance, defined as more than 10.2 seconds, was observed in approximately one-third of women (mean age, 75 years) and was associated with a 54% increased risk of nonvertebral fracture (hazard ratio, 1.54; 95% CI, 1.15-2.07) after adjustment for BMD. Using newer reclassification techniques to assess the incremental value of individual risk factors,7 the authors found that after accounting for age and BMD, the addition of TUG performance correctly reclassified nonvertebral fracture risk in 8% of women (P = .01). Unfortunately, because TUG was the only physical performance measurement assessed in the study by Zhu et al,6 it cannot answer the important question of which performance test is optimal or if several different tests are better than one. Evidence from other studies suggest that gait speed, which is somewhat easier to measure than TUG, is as good as TUG for the prediction of falls.8 To build on the work of Zhu et al,6 next steps should include confirming these results in other prospective cohorts and then assembling and pooling the studies relating TUG (and perhaps other simple measurements of physical performance) to fracture risk in older individuals. Pooling studies will improve our confidence in the clinical utility of the TUG test across different populations and subgroups, allow investigators to search for dose-response relationships and assess optimal thresholds, and refine our ability to determine if TUG performance is associated with fracture risk independent of other risk factors for fracture. Ultimately, to assess the incremental value of adding the TUG test to FRAX, an important step will be to conduct prospective studies in which individual FRAX scores with and without the addition of TUG or other tests of physical performance are related to future fracture outcomes. Lastly, although improving our ability to predict fracture risk is itself important and useful, clinicians need to remember that existing pharmacologic treatments have been approved based on studies of individuals with low BMD and/or previous fracture. We have surprisingly little data that currently available treatments for fracture prevention, including the bisphosphonates, are effective when applied to those with elevated FRAX scores but without osteoporosis as defined by the presence of low BMD (hip or spine T-score less than −2.5) or preexisting vertebral fractures. Such studies need to be done to reassure clinicians that treatments prescribed on the basis of an elevated FRAX score, with or without TUG or other assessments of physical performance, will reduce the risk of fracture. Back to top Article Information Correspondence: Dr Bauer, University of California, San Francisco, 185 Berry, Ste 5700, San Francisco, CA 94107 (dbauer@psg.ucsf.edu). Financial Disclosure: Dr Bauer has received research support unrelated to this topic from Novartis and Amgen. References 1. Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E. FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int. 2008;19(4):385-39718292978PubMedGoogle ScholarCrossref 2. National Osteoporosis Foundation. Clinician's Guide to Prevention and Treatment of Osteoporosis. Washington, DC: National Osteoporosis Foundation; 2010 3. Kanis JA, Hans D, Cooper C, et al; Task Force of the FRAX Initiative. Interpretation and use of FRAX in clinical practice. Osteoporos Int. 2011;22(9):2395-241121779818PubMedGoogle ScholarCrossref 4. Cummings SR, Nevitt MC, Browner WS, et al; Study of Osteoporotic Fractures Research Group. Risk factors for hip fracture in white women. N Engl J Med. 1995;332(12):767-7737862179PubMedGoogle ScholarCrossref 5. Cawthon PM, Fullman RL, Marshall L, et al; Osteoporotic Fractures in Men (MrOS) Research Group. Physical performance and risk of hip fractures in older men. J Bone Miner Res. 2008;23(7):1037-104418302496PubMedGoogle ScholarCrossref 6. Zhu K, Devine A, Lewis JR, Dhaliwal SS, Prince RL. “Timed Up and Go” test and bone mineral density measurement for fracture prediction. Arch Intern Med. 2011;171(18):1655-1661Google ScholarCrossref 7. Donaldson MG, Cawthon PM, Schousboe JT, et al. Novel methods to evaluate fracture risk models. J Bone Miner Res. 2011;26(8):1767-177321351143PubMedGoogle ScholarCrossref 8. Viccaro LJ, Perera S, Studenski SA. Is timed up and go better than gait speed in predicting health, function, and falls in older adults? J Am Geriatr Soc. 2011;59(5):887-89221410448PubMedGoogle ScholarCrossref

Journal

Archives of Internal Medicine – American Medical Association

Published: Oct 10, 2011

Keywords: bone mineral density,fractures,get up and go test

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