Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/10707
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dc.contributor.authorvan Geel, Tineke A. C. M.-
dc.contributor.authorVAN DEN BERGH, Joop-
dc.contributor.authorDinant, Geert Jan-
dc.contributor.authorGEUSENS, Piet-
dc.date.accessioned2010-03-13T09:39:11Z-
dc.date.available2010-03-13T09:39:11Z-
dc.date.issued2010-
dc.identifier.citationMATURITAS, 65(2). p. 143-148-
dc.identifier.issn0378-5122-
dc.identifier.urihttp://hdl.handle.net/1942/10707-
dc.description.abstractLow 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. (C) 2009 Elsevier Ireland Ltd. All rights reserved.-
dc.language.isoen-
dc.publisherELSEVIER IRELAND LTD-
dc.subject.otherBone fractures; Osteoporosis; Elderly; Prevention; FRAX; Garvan fracture risk calculator-
dc.subject.otherBone fractures; Osteoporosis; Elderly; Prevention; FRAX; Garvan fracture risk calculator-
dc.titleIndividualizing fracture risk prediction-
dc.typeJournal Contribution-
dc.identifier.epage148-
dc.identifier.issue2-
dc.identifier.spage143-
dc.identifier.volume65-
local.format.pages6-
local.bibliographicCitation.jcatA1-
dc.description.notes[van Geel, Tineke A. C. M.; Dinant, Geert Jan] Maastricht Univ Caphri, Dept Gen Practice, NL-6200 MD Maastricht, Netherlands. [van den Bergh, Joop P. W.; Geusens, Piet P.] Maastricht Univ, Med Ctr Caphri, Dept Internal Med, NL-6202 AZ Maastricht, Netherlands. [van den Bergh, Joop P. W.] Viecuri Med Ctr Noord Limburg, Venlo, Netherlands. [Geusens, Piet P.] Univ Hasselt, Biomed Res Inst, Diepenbeek, Belgium. t.vangeel@hag.unimaas.nl-
local.type.refereedRefereed-
local.type.specifiedReview-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1016/j.maturitas.2009.12.007-
dc.identifier.isi000274944600011-
item.fulltextWith Fulltext-
item.fullcitationvan Geel, Tineke A. C. M.; VAN DEN BERGH, Joop; Dinant, Geert Jan & GEUSENS, Piet (2010) Individualizing fracture risk prediction. In: MATURITAS, 65(2). p. 143-148.-
item.validationecoom 2011-
item.accessRightsRestricted Access-
item.contributorvan Geel, Tineke A. C. M.-
item.contributorVAN DEN BERGH, Joop-
item.contributorDinant, Geert Jan-
item.contributorGEUSENS, Piet-
crisitem.journal.issn0378-5122-
crisitem.journal.eissn1873-4111-
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