Frequently Asked Questions
In young healthy individuals (with a low mortality) the one-year probability is approximately 10% of the 10-year probability. Thus, an individual with a 10-year fracture probability of 40% would have approximately a 1-year probability of 4%. Higher percentage figures are more readily understood by patients and clinicians. The relationship between short and long-term probabilities is more complex in patients with clinical risk factors and in the elderly. [Kanis JA, Johansson H, et al (2011) Guidance for the adjustment of FRAX according to the dose of glucocorticoids. Osteoporosis International, 22: 809–816 (doi: 10.1007/s00198-010-1524-7., https://pubmed.ncbi.nlm.nih.gov/21229233)].
The risk factors work similarly in men and women in different countries in terms of relative risk. However, absolute risk will vary since, at any given age, the absolute risk of fracture and absolute risk of death varies. In addition, risk factors have variable importance depending upon age (e.g. a family history), or on the presence or absence of other risk factors. For example, low BMI is much less of a risk factor when account is taken of BMD.
Yes. A template is available for translation from Professor EV McCloskey firstname.lastname@example.org.
It is known that dose-responses exist for many of the clinical risk factors. In addition to the number of previous fractures, they include smoking, use of glucocorticoids and consumption of alcohol. The model is, however, based on information that is common to all the cohorts that participated in its creation and such detail is not available. This means that clinical judgement needs to be used when interpreting probabilities. FRAXplus® provides access to adjustments that can illustrate the potential impact of taking additional information (e.g. the number of prior fractures) into account in decision-making.
It is known that dose-responses exist for many of the clinical risk factors. In addition to the number of previous fractures, they include smoking, use of glucocorticoids and consumption of alcohol. The model is, however, based on information that is common to all the cohorts that participated in its creation and such detail is not available. This means that clinical judgement needs to be used when interpreting probabilities. FRAXplus® provides access to adjustments that can illustrate the potential impact of taking additional information (e.g. a higher than average dose of glucocorticoids) into account in decision-making. An aid to the adjustment for dose of glucocorticoids is given in Kanis et al, 2010. [Kanis JA, Johansson H, et al (2011) Guidance for the adjustment of FRAX according to the dose of glucocorticoids. Osteoporosis International, 22: 809–816 (doi: 10.1007/s00198-010-1524-7., https://pubmed.ncbi.nlm.nih.gov/21229233)].
It is known that dose-responses exist for many of the clinical risk factors. In addition to the number of previous fractures, they include smoking, use of glucocorticoids and consumption of alcohol. The model is, however, based on information that is common to all the cohorts that participated in its creation and such detail is not available. This means that clinical judgement needs to be used when interpreting probabilities. It should be noted, however, that a prior morphometric and asymptomatic vertebral fracture carries approximately the same risk as any previous fracture. A clinical vertebral fracture, however, carries a much higher risk (see reference list, Kanis et al 2004 [Kanis JA, Johnell O, et al (2004) Risk and burden of vertebral fractures in Sweden. Osteoporosis International 15: 20-26 (doi: 10.1007/s00198-003-1463-7., https://pubmed.ncbi.nlm.nih.gov/14593450)]).
Both disorders incur a fracture risk over and above that accounted for by BMD. For other secondary causes of osteoporosis, it is conservatively assumed that the increase in major osteoporotic fracture risk is mediated by low BMD. This has been verified for inflammatory bowel disease [Targownik LE, Bernstein CN, et al (2013) Inflammatory bowel disease and the risk of fracture after controlling for FRAX. Journal of Bone and Mineral Research 28: 1007-1013. (doi: 10.1002/jbmr.1848., https://asbmr.onlinelibrary.wiley.com/doi/full/10.1002/jbmr.1848)] and non-dialysis chronic renal failure [Whitlock R, Leslie WD et al (2019) The Fracture Risk Assessment Tool (FRAX®) predicts fracture risk in patients with chronic kidney disease. Kidney International 95: 447-454. ( doi: 10.1016/j.kint.2018.09.022., https://www.sciencedirect.com/science/article/pii/S0085253818307750)].
This holds true for many fractures including major osteoporotic fractures (at the spine, hip, humerus and distal forearm) sustained within a two-year window. This is not accounted for in FRAX, but adjustment algorithms are now available in FRAXplus® to illustrate the impact of recency on fracture probabilities.
It is correct that high values for indices of bone turnover are associated with fracture risk independently of BMD. There is, however, no agreement on a reference analyte and insufficient world-wide experience to know how they might be incorporated. The manner in which the results of such tests are interpreted is a matter of clinical judgement.
FRAX is not sufficiently sensitive that it can be used to monitor treatment or provide treatment targets [Leslie WD, Lix LM, et al (2012) Does osteoporosis therapy invalidate FRAX for fracture prediction? Journal of Bone and Mineral Research 27: 1243-1251. (DOI: 10.1002/jbmr.1582., https://pubmed.ncbi.nlm.nih.gov/22392538/)]. However, FRAX can be used to assess fracture probability in patients recently on treatment or those on treatment if a change in therapy is envisaged [Leslie WD, Majumdar SR, et al (2014) Can change in FRAX score be used to “Treat-to-Target”? A population‐based cohort study. Journal of Bone and Mineral Research 29: 1061-1066. (DOI: 10.1002/jbmr.2151., https://pubmed.ncbi.nlm.nih.gov/24877235/)]
There were few data available at the time of creating the FRAX models. Additionally, pharmaceutical intervention had not been shown to reduce fracture risk in patients with type 2 diabetes. There is now robust data to support the inclusion of type 2 diabetes in future iterations of FRAX and is the topic of current research [Rubin MR, Schwartz AV, et al (2013) Osteoporosis Risk in Type 2 Diabetes Patients. Expert Review of Endocrinology & Metabolism 8: 423–425. (DOI: 10.1586/17446651.2013.835567, https://www.tandfonline.com/doi/full/10.1586/17446651.2013.835567)].
There are several ways that have been suggested [Leslie WD, Johansson H, et al (2018) Comparison of methods for improving fracture risk assessment in diabetes: The Manitoba BMD Registry. Journal of Bone and Mineral Research 33: 1923-1930. (doi: 10.1002/jbmr.3538., https://pubmed.ncbi.nlm.nih.gov/29953670/)]. The simplest way is to enter a yes response in the field for rheumatoid arthritis.
It is not - with the exception of the United States, Singapore and South Africa where there is sufficient epidemiological information to make the appropriate adjustments.
We don’t know but the present evidence is that even very longstanding emigres retain the FRAX characteristics of their motherland. If they are of Chinese ancestry, the Hong Kong FRAX model may be the more appropriate [Johansson H, Odén A, et al (2015) Is the Swedish FRAX model appropriate for Swedish immigrants? Osteoporosis International 26: 2617-2622. (doi: 10.1007/s00198-015-3180-4, https://pubmed.ncbi.nlm.nih.gov/26018091/) ].
There are web-based risk assessment algorithms available in Australia, Germany, Holland, Italy, UK and US. They provide national estimates of fracture incidence. FRAX is calibrated for each country and calculates a fracture probability and not an incidence [Kanis JA, Harvey NC, Johansson H, et al (2017) Overview of fracture prediction tools. Journal of Clinical Densitometry. 20: 360–367. (doi: 10.1016/j.jocd.2017.06.013., https://pubmed.ncbi.nlm.nih.gov/28716500/)]. Probability depends on the hazards of fracture as well as the hazards of death. Thus, even if fracture risk is very high, an individual is unlikely to fracture if death is expected tomorrow (i.e. high risk, low probability).
Use the country for which the epidemiology of osteoporosis most closely approximates your country. Examples of high risk countries are Denmark and Sweden. Low risk countries include Lebanon and China. New models are expected to be made available in later versions. Lobby your national society for a country specific model or a surrogate model.
There are two options. The first is to create a surrogate model which uses the risk of fracture from a country where similar fracture epidemiology is assumed but uses the death risk of the parent country. An example is India, which uses the death hazard of India but the fracture hazard of the Indian population in Singapore. The second option is to create an authentic FRAX model. The requirements for this are available [Population Data for Building a FRAX Model]
The model is constructed from real data in population-based cohorts around the world that have a limited age range. If you enter an age below 40 years, the tool will calculate the probability of fracture at the age of 40 years. You must use your clinical judgement to interpret the risk.
Missing values are not provided for in the current FRAX program. When calculating the 10-year probability it is assumed that every question (except BMD) can be answered. If you don't have information, for example on family history, you should answer no.
Incorporating all osteoporotic fractures is problematic because of limited information on their epidemiology. From Swedish data, the inclusion of other major osteoporotic fractures (e.g. pelvis, other femoral fractures and tibial fractures) would increase the values by about 10 percent (for example, in a patient with a calculated probability of major osteoporotic fractures of 5%, this might be uplifted to 5.5%). Including rib fractures would have a much larger effect. They are, however, difficult to diagnose.
Two reasons. The first is that the cohort data used to create the model reported falls in very different ways so that it was not possible to derive a standardized metric. Second, although plausible, pharmaceutical intervention had not been shown to reduce fracture risk in patients selected solely on the basis of a fall history. It is important that risk assessment models identify a risk that can be reduced by treatment. Note that FRAX is based on the inclusion of individuals who are at all levels of falls risk so, though not an input variable, falls are accounted for in the calculation of FRAX. The possible incorporation of falls history into FRAX is the topic of current research [Harvey NC, Odén A, et al (2018) Falls predict fractures independently of FRAX probability: A meta-analysis of the Osteoporotic Fractures in Men (MrOS) Study. Journal of Bone and Mineral Research 33: 510-516. (doi: 201710.1002/jbmr.3331., https://pubmed.ncbi.nlm.nih.gov/29220072)]. Some guidance is available for adjustment of probabilities [Masud T, Binkley N, et al (2011) Official Positions for FRAX® clinical regarding falls and frailty: can falls and frailty be used in FRAX®? Journal of Clinical Densitometry 14: 194-204., (https://pubmed.ncbi.nlm.nih.gov/21810525/)]. Adjustment algorithms are now available in FRAXplus® to illustrate the impact of the number of falls reported in the past year.
A prior morphometric fracture has the same significance as any other prior fragility fracture and can be entered into the FRAX® model. The output does not, however, include the probability of a morphometric fracture. This is a conservative position, since their clinical significance is controversial (other than for risk prediction). Nevertheless, this does not affect who would be eligible for treatment.
The FRAX® assessment does not tell you who to treat which remains a matter of clinical judgement. In many countries, guidelines are provided that are based on expert opinion and/or on health economic grounds [Kanis JA, Harvey NC, 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. Archives of Osteoporosis, Dec;11(1):25. (doi: 10.1007/s11657-016-0278-z., https://pubmed.ncbi.nlm.nih.gov/27465509/)]. In some countries, there is a direct link between the FRAX website and a country specific site that helps with interpretation of the results (e.g. Brazil, Finland, Lebanon, Romania, Russia and UK)
You should input a T-score for the femoral neck derived from the reference standard (the NHANES III database for female Caucasians aged 20-29 years as widely recommended). T-scores from local data bases or ethnic-specific reference ranges will give misleading results. Note that the same reference range is used for men (i.e. the NHANES III database for female Caucasians age 20-29 years). If you are uncertain about the T-score, input the manufacturer of the measurement device and the BMD result. The FRAX T-score will be calculated for you.
No. The model is constructed from real data in population-based cohorts where femoral neck BMD is available. T-score and Z-score vary according to the technology used and the site measured [Leslie WD, Lix LM, et al (2012) A comparative study of using non-hip bone density inputs with FRAX®. Osteoporosis International 23: 853-860. (doi: 10.1007/s00198-011-1814-8., https://pubmed.ncbi.nlm.nih.gov/22008881)].
Yes. But note that FRAX will overestimate the fracture probability in patients where the T-score for the lumbar spine is much higher than the T-score at the femoral neck BMD [Johansson H, Kanis JA, et al (2014) Impact of femoral neck and lumbar spine BMD discordances on FRAX probabilities in women: A meta-analysis of international cohorts. Calcified Tissue International 95:428–435. (DOI 10.1007/s00223-014-9911-2., https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4361897)]. FRAXplus® provides access to adjustments that can illustrate the potential impact of taking additional information (e.g. a discordance between lumbar spine and femoral neck BMD T-scores) into account in decision-making.
Significant changes will affect the accuracy of the model so that FRAX models need adjustment from time to time.