Maturitas
Volume 65, Issue 2 , Pages 143-148, February 2010

Individualizing fracture risk prediction

  • Tineke A.C.M. van Geel

      Affiliations

    • Department of General Practice, Maastricht University/Caphri, P.O. Box 616, 6200 MD Maastricht, The Netherlands
    • Corresponding Author InformationCorresponding author. Tel.: +31 43 3882272; fax: +31 43 3619344.
  • ,
  • Joop P.W. van den Bergh

      Affiliations

    • Department of Internal Medicine, Maastricht University Medical Center/Caphri, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
    • Viecuri Medical Center Noord Limburg, Venlo, The Netherlands
  • ,
  • Geert-Jan Dinant

      Affiliations

    • Department of General Practice, Maastricht University/Caphri, P.O. Box 616, 6200 MD Maastricht, The Netherlands
  • ,
  • Piet P. Geusens

      Affiliations

    • Department of Internal Medicine, Maastricht University Medical Center/Caphri, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
    • Biomedical Research institute, University Hasselt, Belgium

Received 27 November 2009; received in revised form 1 December 2009; accepted 1 December 2009. published online 23 December 2009.

Abstract 

Low bone mineral density (BMD) and clinical factors (CRF) have been identified as factors associated with an increased relative risk of fractures. From this observation and for clinical decision making, the concept of prediction of the individual absolute risk of fractures has emerged. It refers to the individual's risk for fractures over a certain time period, e.g. the next 5 and 10 years. Two individualized fracture risk calculation tools that are increasingly used and are available on the web are the FRAX algorithm and the Garvan fracture risk calculator. These tools integrate BMD and CRFs for fracture risk calculation in the individual patient in daily practice. Although both tools include straightforward risk factors, such as age, sex, previous fractures, body weight and BMD, they differ in several aspects, such as the inclusion of other CRFs, fall risks and number of previous fractures. Both models still need to be validated in different populations before they can be generalized to other populations, since the background risk for fractures is population specific. Further studies will be needed to validate their contribution in selecting patients who will achieve fracture risk reduction with anti-osteoporosis therapy.

Keywords: Bone fractures, Osteoporosis, Elderly, Prevention, FRAX, Garvan fracture risk calculator

To access this article, please choose from the options below

Login to an existing account or Register a new account.

  • Purchase this article for 31.50 USD (You must login/register to purchase this article)

    Online access for 24 hours. The PDF version can be downloaded as your permanent record.

  • Subscribe to this title

    Get unlimited online access to this article and all other articles in this title 24/7 for one year.

  • Claim access now

    For current subscribers with Society Membership or Account Number.

  • Visit SciVerse ScienceDirect to see if you have access via your institution.
 

PII: S0378-5122(09)00462-9

doi:10.1016/j.maturitas.2009.12.007

Maturitas
Volume 65, Issue 2 , Pages 143-148, February 2010