Osteoporosis International

, Volume 30, Issue 1, pp 1–2 | Cite as

FRAX: a coming of age

  • W.D. LeslieEmail author

“The stone age was marked man’s clever use of crude tools; the information age, to date, has been marked by man’s crude use of clever tools.”Anonymous

In 2018, the Fracture Risk Assessment (FRAX) tool celebrated its 10th birthday. It is timely, therefore, that Archives of Osteoporosis has published “A brief history of FRAX” from the architect and metaphorical father of FRAX, Professor John Kanis, and his team [1]. FRAX was a conceptual and clinical advance over treatment based upon bone mineral density (BMD) T-score alone [2], and has subsequently made its way into over 100 clinical practice guidelines worldwide [3]. In the modern age of data analytics, it may appear surprising that FRAX was “only” based upon 60,000 individuals [4]. However, for the time, this was a prodigious sample size derived from multiple international population-based prospective cohort studies and clearly up to the task since the core of the FRAX algorithm has not undergone any revision since it was released.

Looking back, the birth of FRAX was greeted with much hullaballoo and excitement. Expectations were unrealistically high. Many (mea culpa) naively believed that this would simplify osteoporosis treatment decision making. Subsequent experience has shown that this is far from the truth—the importance of clinical judgment has not been diminished with the emergence of FRAX and indeed remains a critical ingredient in the physician-patient encounter. Critics (and there have been many) have questioned various aspects of FRAX, not least whether fracture probability identifies a treatment-responsive risk. Those criticisms have at least in part been addressed in the recently published SCOOP trial which demonstrated a significant reduction in incident hip fractures among individuals selected for treatment based upon hip fracture probability, implying that high fracture probability as reflected in FRAX is responsive to appropriate osteoporosis management [5]. Moreover, post hoc analyses found that the effect on hip fracture reduction increased with higher baseline FRAX hip fracture probability, a most fortuitous but unexpected situation [6].

The review from Kanis et al. [1] concludes with “Teething troubles.” At the risk of straining the analogy, FRAX is now approaching its adolescent years, a time when more existential angst and turmoil is to be anticipated. Some of the limitations of FRAX have been openly acknowledged by the FRAX team [7], in part reflecting the inevitable tension between creating a tool that is more accurate (but unwieldly in the number of the risk factors) versus lacking sufficient detail to capture the variations commonly encountered in clinical practice [8]. As a tool intended for use by primary care practitioners, FRAX is easy to criticize—“too little” for some and “too much” for others. Arguably, one of the most important limitations of FRAX, which of course is intended to identify high fracture risk, is the effect of prior fracture on that risk assessment. FRAX accepts only a binary input for previous fracture, whereas clinicians know that all fractures are important but not all fractures are equal. Fractures involving the hip and spine carry a higher risk for recurrent fracture than fractures of the distal extremities [9], and also have an evidence base to support empiric therapy on the basis of fracture alone [10, 11]. Equally important is the concern that multiple fractures carry greater risk than a single fracture, yet this is not accommodated in FRAX as it is for other calculators [12, 13]. The fracture mechanism, simplistically reduced to traumatic versus fragility, represents another dimension. Some studies suggest that traumatic fractures carry the same risk for recurrent fractures as non-traumatic fractures [14, 15], though most clinicians and patients have difficulty seeing these as equal. More recently, the time-dependence of fracture risk has come into focus, with the suggestion that there is a period of imminent risk following a fracture event [16, 17]. In principle, this creates an opportunity for early intervention, potentially with more potent agents, to reverse that risk [18]. Whether any risk assessment tool will ever be able to capture all of these nuances is doubtful.

Enter the importance of clinical judgment which was important in the pre-FRAX era and will remain so far into the future no matter how fracture risk assessment evolves. Creation of a tool, even a clever evidence-based tool like FRAX, does not necessarily ensure that it will be used, be used correctly, or make measurable differences at the societal level. Translation from science to clinic to public health will require new strategies and alliances. Guidelines are clearly not enough, as evidenced by data showing that BMD still drives treatment decision making even when individuals qualify for therapy based upon high fracture probability or major fractures. We reported that primary care physicians embrace the concept of absolute fracture probability [19], and instantaneously reduced their proclivity to initiate treatment of osteopenia [20], but are still reluctant to treat women found to be at high risk of fracture in the absence of a BMD T-score in the osteoporotic range [21]. Moving beyond BMD T-scores remains a challenge to the osteoporosis community even 10 years after the birth of FRAX.

Of course, FRAX is not the only fracture prediction tool that has been developed (see review by Rubin et al. [8]). Each tool has its unique strengths and weaknesses, and the hope is that we can learn from each other to create better tools, more effective screening strategies, and (ultimately) improve the care of patients worldwide. To date, FRAX has been an only child. There is speculation about a sibling (FRAX II) and the extent to which this may or may not be able to address perceived limitations to FRAX itself. The wish list is long, and compromises will have to be made along the way that will disappoint some. But that is another tale for another time. In the meantime, I am happy to celebrate the successes of FRAX over its first decade of life, and wish it many happy returns.


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Conflicts of interest



  1. 1.
    Kanis JA, Johansson H, Harvey NC, McCloskey EV. A brief history of FRAX. Arch Osteoporos 2018;[epub]Google Scholar
  2. 2.
    Johansson H, Azizieh F, Al Ali N, Alessa T, Harvey NC, McCloskey E et al (2017) FRAX- vs. T-score-based intervention thresholds for osteoporosis. Osteoporos Int 28:3099–3105CrossRefGoogle Scholar
  3. 3.
    Kanis JA, Harvey NC, Cooper C, Johansson H, Oden A, McCloskey EV et al (2016) A systematic review of intervention thresholds based on FRAX : a report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11(1):25CrossRefGoogle Scholar
  4. 4.
    Kanis JA. Assessment of osteoporosis at the primary health-care level. Technical Report. Accessible at Published by the University of Sheffield; 2007
  5. 5.
    Shepstone L, Lenaghan E, Cooper C, Clarke S, Fong-Soe-Khioe R, Fordham R, Gittoes N, Harvey I, Harvey N, Heawood A, Holland R, Howe A, Kanis J, Marshall T, O’Neill T, Peters T, Redmond N, Torgerson D, Turner D, McCloskey E, Shepstone L, Lenaghan E, Cooper C, Clarke S, Fong-Soe-Khioe R, Fordham R, Gittoes N, Harvey I, Harvey N, Heawood A, Holland R, Howe A, Kanis J, Marshall T, O’Neill T, Peters T, Redmond N, Torgerson D, Turner D, McCloskey E, Crabtree N, Duffy H, Parle J, Rashid F, Stant K, Taylor K, Thomas C, Knox E, Tenneson C, Williams H, Adams D, Bion V, Blacklock J, Dyer T, Bratherton S, Fidler M, Knight K, McGurk C, Smith K, Young S, Collins K, Cushnaghan J, Arundel C, Bell K, Clark L, Collins S, Gardner S, Mitchell N (2018) Screening in the community to reduce fractures in older women (SCOOP): a randomised controlled trial. Lancet 391(10122):741–747CrossRefGoogle Scholar
  6. 6.
    McCloskey E, Johansson H, Harvey NC, Shepstone L, Lenaghan E, Fordham R, Harvey I, Howe A, Cooper C, Clarke S, Gittoes N, Heawood A, Holland R, Marshall T, O’Neill TW, Peters TJ, Redmond N, Torgerson D, Kanis JA, the SCOOP Study Team (2018) Management of patients with high baseline hip fracture risk by FRAX reduces hip fractures-a post hoc analysis of the SCOOP study. J Bone Miner Res 33:1020–1026CrossRefGoogle Scholar
  7. 7.
    Kanis JA, Hans D, Cooper C, Baim S, Bilezikian JP, Binkley N et al (2011) Interpretation and use of FRAX in clinical practice. Osteoporos Int 22(9):2395–2411CrossRefGoogle Scholar
  8. 8.
    Rubin KH, Friis-Holmberg T, Hermann AP, Abrahamsen B, Brixen K (2013) Risk assessment tools to identify women with increased risk of osteoporotic fracture: complexity or simplicity? A systematic review. J Bone Miner Res 28(8):1701–1717CrossRefGoogle Scholar
  9. 9.
    Morin SN, Lix LM, Leslie WD (2014) The importance of previous fracture site on osteoporosis diagnosis and incident fractures in women. J Bone Miner Res 29(7):1675–1680CrossRefGoogle Scholar
  10. 10.
    Lyles KW, Colon-Emeric CS, Magaziner JS, Adachi JD, Pieper CF, Mautalen C et al (2007) Zoledronic acid and clinical fractures and mortality after hip fracture. N Engl J Med 357(18):1799–1809CrossRefGoogle Scholar
  11. 11.
    Kanis JA, Barton IP, Johnell O (2005) Risedronate decreases fracture risk in patients selected solely on the basis of prior vertebral fracture. Osteoporos Int 16(5):475–482CrossRefGoogle Scholar
  12. 12.
    Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2008) Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks. Osteoporos Int 19(10):1431–1444CrossRefGoogle Scholar
  13. 13.
    Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2007) Development of a nomogram for individualizing hip fracture risk in men and women. Osteoporos Int 18(8):1109–1117CrossRefGoogle Scholar
  14. 14.
    Mackey DC, Black DM, Bauer DC, McCloskey EV, Eastell R, Mesenbrink P et al (2011) Effects of antiresorptive treatment on nonvertebral fracture outcomes. J Bone Miner Res 26(10):2411–2418CrossRefGoogle Scholar
  15. 15.
    Mackey DC, Lui LY, Cawthon PM, Bauer DC, Nevitt MC, Cauley JA, Hillier TA, Lewis CE, Barrett-Connor E, Cummings SR, Study of Osteoporotic Fractures (SOF) and Osteoporotic Fractures in Men Study (MrOS) Research Groups (2007) High-trauma fractures and low bone mineral density in older women and men. JAMA 298(20):2381–2388CrossRefGoogle Scholar
  16. 16.
    Johansson H, Siggeirsdottir K, Harvey NC, Oden A, Gudnason V, McCloskey E et al (2017) Imminent risk of fracture after fracture. Osteoporos Int 28(3):775–780CrossRefGoogle Scholar
  17. 17.
    Giangregorio LM, Leslie WD, Manitoba Bone Density P (2010) Time since prior fracture is a risk modifier for 10-year osteoporotic fractures. J Bone Miner Res 25(6):1400–1405CrossRefGoogle Scholar
  18. 18.
    Roux C, Briot K (2017) Imminent fracture risk. Osteoporos Int 28(6):1765–1769CrossRefGoogle Scholar
  19. 19.
    Leslie WD, Manitoba Bone Density Program C (2008) Absolute fracture risk reporting in clinical practice: a physician-centered survey. Osteoporos Int 19(4):459–463CrossRefGoogle Scholar
  20. 20.
    Leslie WD, Morin S, Lix LM (2010) A before-and-after study of fracture risk reporting and osteoporosis treatment initiation. Ann Intern Med 153(9):580–586CrossRefGoogle Scholar
  21. 21.
    Leslie WD, Seeman E, Morin SN, Lix LM, Majumdar SR (2018) The diagnostic threshold for osteoporosis impedes fracture prevention in women at high risk for fracture: a registry-based cohort study. Bone 114:298–303CrossRefGoogle Scholar

Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2018

Authors and Affiliations

  1. 1.Department of MedicineUniversity of ManitobaWinnipegCanada

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