Calcified Tissue International

, Volume 98, Issue 5, pp 417–425 | Cite as

SIGN Guidelines for Scotland: BMD Versus FRAX Versus QFracture

  • John A. KanisEmail author
  • Juliet Compston
  • Cyrus Cooper
  • Nicholas C. Harvey
  • Helena Johansson
  • Anders Odén
  • Eugene V. McCloskey


Scottish Intercollegiate Guidelines Network (SIGN) recently issued guidance on the management of osteoporosis and the prevention of fragility fractures. The aim of this paper was to critically review the guidance. The SIGN guidance utilises risk factors for fracture as an initial step for assessment, but recommends treatment only in individuals with a T-score of −2.5. There are many problems with the sole use of BMD as the sole gateway to treatment. Moreover, the assessment tools to determine risk (FRAX or QFracture) are not designed to detect osteoporosis but rather fracture risk. Whereas SIGN assumes that FRAX overestimates fracture probability, there are compelling reasons to believe that the disparity is related to the inadequate calibration of QFracture. The disparities make the use of a single threshold for BMD testing problematic. The SIGN guidance for men at high risk of fracture provides a set of confused and inconsistent recommendations that are in direct conflict with regulatory authorizations and is likely to increase further the large treatment gap in men. For women, the number of women eligible for treatment (i.e. with osteoporosis) is 81,700 with the use of FRAX but only 12,300 with QFracture representing 8.2 and 1.2 % of the total population at risk, respectively. We conclude that serious problems with the SIGN guidance preclude its implementation.


Assessment guidelines FRAX QFracture osteoporosis Scotland QFracture 


Compliance with Ethical Standards

Conflict of interest

Professor Kanis led the team that developed FRAX as director of the WHO Collaborating Centre for Metabolic Bone Diseases; he has no financial interest in FRAX. Professors McCloskey, Oden, Harvey and Dr Johansson are members of the FRAX team. Professor Compston is Chairman of the National Osteoporosis Guideline Group, UK of which Professors Cooper, Kanis and McCloskey are members of its advisory body.


  1. 1.
    Kanis JA, Borgström F, Compston J, Dreinhöfer K, Nolte E, Jonsson L et al (2013) SCOPE: a scorecard for osteoporosis in Europe. Arch Osteoporos 8:144. doi: 10.1007/s11657-013-0144-1 CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Scottish Intercollegiate Guidelines Network (SIGN) (2015) Management of osteoporosis and the prevention of fragility fractures. Edinburgh: SIGN; 2015. (SIGN publication no. 142). Accessed May 11 2015
  3. 3.
    National Institute for Health and Care Excellence (2014) NICE Clinical Guideline 146. Osteoporosis: assessing the risk of fragility fracture. London, UK. Accessed 18 May 2015
  4. 4.
    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 19:1431–1444CrossRefPubMedGoogle Scholar
  5. 5.
    Hippisley-Cox J, Coupland C (2009) Predicting risk of osteoporotic fracture in men and women in England and Wales: prospective derivation and validation of QFracture Scores. BMJ 339:b4229CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Dachverband Osteologie e.V (2011) DVO guideline 2009 for prevention, diagnosis and therapy of osteoporosis in adults. Osteologie 20: 55–74. Accessed May 2012
  7. 7.
    Kanis JA, Delmas P, Burckhardt P, Cooper C, Torgerson D (1977) Guidelines for diagnosis and management of osteoporosis. Osteoporos Int 7:390–406CrossRefGoogle Scholar
  8. 8.
    Royal College of Physicians (1999) Osteoporosis: clinical guidelines for the prevention and treatment. RCP, LondonGoogle Scholar
  9. 9.
    Kanis JA, McCloskey EV, Harvey NC, Johansson H, Leslie WD (2015) Intervention thresholds and the diagnosis of osteoporosis. J Bone Miner Res. doi: 10.1002/jbmr.2531 Google Scholar
  10. 10.
    Cranney A, Jamal SA, Tsang JF, Josse RG, Leslie WD (2007) Low bone mineral density and fracture burden in postmenopausal women. CMAJ 177:575–580CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    World Health Organisation (1994) Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. WHO Technical Report Series 843. 1994. WHO, GenevaGoogle Scholar
  12. 12.
    Li Y, Wei FF, Thijs L, Boggia J, Asayama K, Hansen TW et al (2014) Ambulatory hypertension subtypes and 24-hour systolic and diastolic blood pressure as distinct outcome predictors in 8341 untreated people recruited from 12 populations. Circulation 130:466–474CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Kanis JA, Johnell O, Oden A, Jonsson B, De Laet C, Dawson A (2000) Risk of hip fracture according to World Health Organization criteria for osteoporosis and osteopenia. Bone 27:585–590CrossRefPubMedGoogle Scholar
  14. 14.
    Johansson H, Kanis JA, Oden A, Compston J, McCloskey E (2012) A comparison of case-finding strategies in the UK for the management of hip fractures. Osteoporos Int 23:907–915CrossRefPubMedGoogle Scholar
  15. 15.
    Kanis JA, McCloskey E, Johansson H, Oden A, Leslie WD (2012) FRAXs with and without BMD. Calcif Tissue Int 90:1–13CrossRefPubMedGoogle Scholar
  16. 16.
    Leslie WD, Majumdar SR, Lix L, Johansson H, McCloskey EV, Kanis JA (2012) High fracture probability with FRAX® usually indicates densitometric osteoporosis: implications for clinical practice. Osteoporos Int 23:391–397CrossRefPubMedGoogle Scholar
  17. 17.
    McCloskey E (2015) A BMD threshold for treatment efficacy in osteoporosis? A need to consider the whole evidence base. Osteoporos Int. doi: 10.1007/s00198-015-3406-5 PubMedCentralGoogle Scholar
  18. 18.
    Collins GS, Mallett S, Altman DG (2011) Predicting risk of osteoporotic and hip fracture in the United Kingdom: prospective independent and external validation of QFractureScores. BMJ 342:d3651CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Hippisley-Cox J, Coupland C (2014) Brindle P (2014) The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study. BMJ Open 4:e005809. doi: 10.1136/bmjopen-2014-005809 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Kanis JA (2015) on behalf of the World Health Organization Scientific Group. Assessment of osteoporosis at the primary health-care level. Technical Report. World Health Organization Collaborating Centre for Metabolic Bone Diseases, University of Sheffield, UK 2008. Accessed 14 July 2015
  21. 21.
    Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E (2008) FRAX™ and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19:385–397CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Kanis JA, Oden A, Johnell O, Johansson H, De Laet C, Brown J (2007) The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int 18:1033–1046CrossRefPubMedGoogle Scholar
  23. 23.
    Bolland MJ, Jackson R, Gamble GD, Grey A (2013) Discrepancies in predicted fracture risk in elderly people. BMJ 346:e8669CrossRefPubMedGoogle Scholar
  24. 24.
    Kanis JA, Oden A, Johansson H, McCloskey E (2012) Pitfalls in the external validation of FRAX. Osteoporos Int 23:423–431CrossRefPubMedGoogle Scholar
  25. 25.
    Nayak S, Edwards DL, Saleh AA, Greenspan SL (2015) Systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for osteoporosis or low bone density. Osteoporos Int 26:1543–1554CrossRefPubMedGoogle Scholar
  26. 26.
    Koh LK, Sedrine WB, Torralba TP, Kung A, Fujiwara S, Chan SP et al (2001) A simple tool to identify Asian women at increased risk of osteoporosis. Osteoporos Int 12:699–705CrossRefPubMedGoogle Scholar
  27. 27.
    Kanis JA, Harvey NC, McCloskey E (2014) Pre-screening young postmenopausal women for BMD testing. Bonekey Rep 11(3):544. doi: 10.1038/bonekey.2014.39.eCollection Google Scholar
  28. 28.
    Crandall CJ, Larson J, Gourlay ML, Donaldson MG, Lacroix A, Cauley JA et al (2014) Osteoporosis screening in postmenopausal women 50-64 years-old: comparison of U.S. Preventive Services Task Force strategy and two traditional strategies in the Women’s Health Initiative. J Bone Miner Res 29:1661–1666CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Hippisley-Cox J, Coupland C (2012) Derivation and validation of updated QFracture algorithm to predict risk of osteoporotic fracture in primary care in the United Kingdom: prospective open cohort study. BMJ 344:e3427. doi: 10.1136/bmj.e3427 CrossRefPubMedGoogle Scholar
  30. 30.
    Hippisley-Cox J, Coupland C (2011) Validation of QFracture compared with FRAX. Analysis prepared for NICE 2011. Accessed 15 May 2015
  31. 31.
    Davis S, Martyn-St James M, Sanderson J, Stevens J, Goka E, Rawdin A et al (2015) Bisphosphonates for preventing osteoporotic fragility fractures (including a partial update of NICE technology appraisal guidance 160 and 161). Technology Assessment ReportGoogle Scholar
  32. 32.
    Cummins NM, Poku EK, Towler MR, O’Driscoll OM, Ralston SH (2011) Clinical risk factors for osteoporosis in Ireland and the UK: a comparison of FRAX and Qfracture Scores. Calcif Tissue Int 89:172–177CrossRefPubMedGoogle Scholar
  33. 33.
    DeLusignan S, Valentin T, Chan T, Hague N, Wood O, van Vlymen J et al (2004) Problems with primary care data quality: osteoporosis as an exemplar. Inf Prim Care 12:147–156Google Scholar
  34. 34.
    Kanis JA, Johansson H, Oden A, Johnell O, De Laet C, Eisman JA et al (2004) A family history of fracture and fracture risk: a meta-analysis. Bone 35:1029–1037CrossRefPubMedGoogle Scholar
  35. 35.
    Klotzbuecher CM, Ross PD, Landsman PB, Abbott TA, Berger M (2000) Patients with prior fractures have an increased risk of future fractures: a summary of the literature and statistical synthesis. J Bone Miner Res 15:721–739CrossRefPubMedGoogle Scholar
  36. 36.
    Kanis JA, Johnell O, De Laet C, Johansson H, Oden A, Delmas P et al (2004) A meta-analysis of previous fracture and subsequent fracture risk. Bone 35:375–382CrossRefPubMedGoogle Scholar
  37. 37.
    Kanis JA, Oden A, Johnell O, Jonsson B, de Laet C, Dawson A (2001) The burden of osteoporotic fractures: a method for setting intervention thresholds. Osteoporos Int 12:417–427CrossRefPubMedGoogle Scholar
  38. 38.
    Siggeirsdottir K, Aspelund T, Johansson H, Gudmundsson EF, Mogensen B, Jonsson BY et al (2014) The incidence of a first major osteoporotic fracture in Iceland and implications for FRAX. Osteoporos Int 25:2445–2451CrossRefPubMedGoogle Scholar
  39. 39.
    Lam A, Leslie WD, Lix LM, Yogendran M, Morin SN, Majumdar SR (2014) Major osteoporotic to hip fracture ratios in Canadian men and women with Swedish comparisons: a population-based analysis. J Bone Miner Res 29:1067–1073CrossRefPubMedGoogle Scholar
  40. 40.
    Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA (2010) Manitoba bone density program. Independent clinical validation of a Canadian FRAX((R)) tool: fracture prediction and model calibration. J Bone Miner Res 25:2350–2358CrossRefPubMedGoogle Scholar
  41. 41.
    Brennan SL, Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E et al (2014) FRAX provides robust fracture prediction regardless of socioeconomic adversity. Osteoporos Int 25:61–69CrossRefPubMedGoogle Scholar
  42. 42.

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • John A. Kanis
    • 1
    Email author
  • Juliet Compston
    • 2
  • Cyrus Cooper
    • 3
  • Nicholas C. Harvey
    • 3
  • Helena Johansson
    • 1
  • Anders Odén
    • 1
  • Eugene V. McCloskey
    • 1
  1. 1.Centre for Metabolic DiseasesUniversity of Sheffield Medical SchoolSheffieldUK
  2. 2.Cambridge Biomedical CampusCambridgeUK
  3. 3.MRC Lifecourse Epidemiology UnitUniversity of SouthamptonSouthamptonUK

Personalised recommendations