Individualizing fracture risk prediction

被引:25
|
作者
van Geel, Tineke A. C. M. [1 ]
van den Bergh, Joop P. W. [2 ,3 ]
Dinant, Geert Jan [1 ]
Geusens, Piet P. [2 ,4 ]
机构
[1] Maastricht Univ Caphri, Dept Gen Practice, NL-6200 MD Maastricht, Netherlands
[2] Maastricht Univ, Med Ctr Caphri, Dept Internal Med, NL-6202 AZ Maastricht, Netherlands
[3] Viecuri Med Ctr Noord Limburg, Venlo, Netherlands
[4] Univ Hasselt, Biomed Res Inst, Diepenbeek, Belgium
关键词
Bone fractures; Osteoporosis; Elderly; Prevention; FRAX; Garvan fracture risk calculator; BONE-MINERAL DENSITY; HIP FRACTURE; POSTMENOPAUSAL WOMEN; VERTEBRAL FRACTURE; SUBSEQUENT FRACTURE; CLINICAL FRACTURES; TERM RISK; OSTEOPOROSIS; MANAGEMENT; MEN;
D O I
10.1016/j.maturitas.2009.12.007
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
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. (C) 2009 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:143 / 148
页数:6
相关论文
共 50 条
  • [21] Capture the vertebral fracture: Risk factors as a prediction
    Zvekic-Svorcan, Jelena
    Aleksic, Jelena
    Jankovic, Tanja
    Filipovic, Karmela
    Cvetkovic, Milan
    Vuksanovic, Miljanka
    Filipov, Predrag
    JOURNAL OF BACK AND MUSCULOSKELETAL REHABILITATION, 2019, 32 (02) : 269 - 276
  • [22] Vertebral fracture risk (VFR) score for fracture prediction in postmenopausal women
    Lillholm, M.
    Ghosh, A.
    Pettersen, P. C.
    de Bruijne, M.
    Dam, E. B.
    Karsdal, M. A.
    Christiansen, C.
    Genant, H. K.
    Nielsen, M.
    OSTEOPOROSIS INTERNATIONAL, 2011, 22 (07) : 2119 - 2128
  • [23] Improved fracture risk prediction by adding VFA-identified vertebral fracture data to BMD by DXA and clinical risk factors used in FRAX
    Johansson, L.
    Johansson, H.
    Axelsson, K. F.
    Litsne, H.
    Harvey, N. C.
    Liu, E.
    Leslie, W. D.
    Vandenput, L.
    McCloskey, E.
    Kanis, J. A.
    Lorentzon, M.
    OSTEOPOROSIS INTERNATIONAL, 2022, 33 (08) : 1725 - 1738
  • [24] Geographic variation of bone mineral density and selected risk factors for prediction of incident fracture among Canadians 50 and older
    Langsetmo, Lisa
    Hanley, David A.
    Kreiger, Nancy
    Jamal, Sophie A.
    Prior, Jerilynn
    Adachi, Jonathan D.
    Davison, K. Shawn
    Kovacs, Christopher
    Anastassiades, Tassos
    Tenenhouse, Alan
    Goltzman, David
    BONE, 2008, 43 (04) : 672 - 678
  • [25] Efficacy and efficiency of fracture liaison services to reduce the risk of recurrent osteoporotic fractures
    Javaid, M. K.
    AGING CLINICAL AND EXPERIMENTAL RESEARCH, 2021, 33 (08) : 2061 - 2067
  • [26] Prediction of vertebral fractures in cancer patients undergoing hormone deprivation therapies: Reliability of who fracture risk assessment tool (frax) and bone mineral density in real-life clinical practice
    Mazziotti, Gherardo
    Vena, Walter
    Pedersini, Rebecca
    Piccini, Sara
    Morenghi, Emanuela
    Cosentini, Deborah
    Zucali, Paolo
    Torrisi, Rosalba
    Sporeni, Silvio
    Simoncini, Edda L.
    Maroldi, Roberto
    Balzarini, Luca
    Lania, Andrea G.
    Berruti, Alfredo
    JOURNAL OF BONE ONCOLOGY, 2022, 33
  • [27] Frequency of FRAX risk factors in osteopenic postmenopausal women with and without history of fragility fracture
    Baro, Francesc
    Cano, Antonio
    Sanchez Borrego, Rafael
    Ferrer, Javier
    Gonzalez Rodriguez, Silvia Pilar
    Luis Neyro, Jose
    Rodriguez Bueno, Esteban
    Sancho, Cristina
    Inaraja, Veronica
    Fernandez, Cristina
    Corral, Carlos
    MENOPAUSE-THE JOURNAL OF THE NORTH AMERICAN MENOPAUSE SOCIETY, 2012, 19 (11): : 1193 - 1199
  • [28] Estimating osteoporotic fracture risk following a wrist fracture: a tale of two systems
    Beattie, Karen
    Adachi, Jonathan
    Ioannidis, George
    Papaioannou, Alexandra
    Leslie, William D.
    Grewal, Ruby
    MacDermid, Joy
    Hodsman, Anthony B.
    ARCHIVES OF OSTEOPOROSIS, 2015, 10 (01)
  • [29] Fracture risk prediction with FRAX in Slovak postmenopausal women
    Nemethova, Eva
    Killinger, Zdenko
    Payer, Juraj
    CENTRAL EUROPEAN JOURNAL OF MEDICINE, 2013, 8 (05): : 571 - 576
  • [30] 10-Year Fracture Risk in Postmenopausal Women with Osteopenia and Osteoporosis in South Korea
    Baek, Yeon-Hee
    Cho, Sun Wook
    Jeong, Han Eol
    Kim, Ju Hwan
    Hwang, Yunji
    Lange, Jeffrey L.
    Shin, Ju-Young
    ENDOCRINOLOGY AND METABOLISM, 2021, 36 (06) : 1178 - 1188