Literature DB >> 31317250

How well do the FRAX (Australia) and Garvan calculators predict incident fractures? Data from the Geelong Osteoporosis Study.

K L Holloway-Kew1, Y Zhang2, A G Betson3, K B Anderson3, D Hans4, N K Hyde3, G C Nicholson5, N A Pocock6, M A Kotowicz3,4,7, J A Pasco3,4,7.   

Abstract

This study reports that both FRAX and Garvan calculators underestimated fractures in Australian men and women, particularly in those with osteopenia or osteoporosis. Major osteoporotic fractures were poorly predicted, while both calculators performed acceptably well for hip fractures.
INTRODUCTION: This study assessed the ability of the FRAX (Australia) and Garvan calculators to predict fractures in Australian women and men.
METHODS: Women (n = 809) and men (n = 821) aged 50-90 years, enrolled in the Geelong Osteoporosis Study, were included. Fracture risk was estimated using FRAX and Garvan calculators with and without femoral neck bone mineral density (BMD) (FRAXBMD, FRAXnoBMD, GarvanBMD, GarvannoBMD). Incident major osteoporotic (MOF), fragility, and hip fractures over the following 10 years were verified radiologically. Differences between observed and predicted numbers of fractures were assessed using a chi-squared test. Diagnostics indexes were calculated.
RESULTS: In women, 115 MOF, 184 fragility, and 42 hip fractures occurred. For men, there were 73, 109, and 17 fractures, respectively. FRAX underestimated MOFs, regardless of sex or inclusion of BMD. FRAX accurately predicted hip fractures, except in women with BMD (20 predicted, p = 0.004). Garvan underestimated fragility fractures except in men using BMD (88 predicted, p = 0.109). Garvan accurately predicted hip fractures except for women without BMD (12 predicted, p < 0.001). Fractures were underestimated primarily in the osteopenia and osteoporosis groups; MOFs in the normal BMD group were only underestimated by FRAXBMD and fragility fractures by GarvannoBMD, both in men. AUROCs were not different between scores with and without BMD, except for fragility fractures predicted by Garvan in women (0.696, 95% CI 0.652-0.739 and 0.668, 0.623-0.712, respectively, p = 0.008) and men, which almost reached significance (0.683, 0.631-0.734, and 0.667, 0.615-0.719, respectively, p = 0.051). Analyses of sensitivity and specificity showed overall that MOFs and fragility fractures were poorly predicted by both FRAX and Garvan, while hip fractures were acceptably predicted.
CONCLUSIONS: Overall, the FRAX and Garvan calculators underestimated MOF and fragility fractures, particularly in individuals with osteopenia or osteoporosis. Hip fractures were predicted better by both calculators. AUROC analyses suggest that GarvanBMD performed better than GarvannoBMD for prediction of fragility fractures.

Entities:  

Keywords:  Absolute fracture risk calculator; FRAX; Garvan; Geelong osteoporosis study

Mesh:

Year:  2019        PMID: 31317250     DOI: 10.1007/s00198-019-05088-2

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  29 in total

1.  Evaluation of the FRAX and Garvan fracture risk calculators in older women.

Authors:  Mark J Bolland; Amanda Ty Siu; Barbara H Mason; Anne M Horne; Ruth W Ames; Andrew B Grey; Greg D Gamble; Ian R Reid
Journal:  J Bone Miner Res       Date:  2011-02       Impact factor: 6.741

2.  Morphometric vertebral fractures of the lower thoracic and lumbar spine, physical function and quality of life in men.

Authors:  J A Pasco; M J Henry; S Korn; G C Nicholson; M A Kotowicz
Journal:  Osteoporos Int       Date:  2008-09-19       Impact factor: 4.507

3.  Half the burden of fragility fractures in the community occur in women without osteoporosis. When is fracture prevention cost-effective?

Authors:  Kerrie M Sanders; Geoffrey C Nicholson; Jennifer J Watts; Julie A Pasco; Margaret J Henry; Mark A Kotowicz; Ego Seeman
Journal:  Bone       Date:  2006-02-28       Impact factor: 4.398

4.  Probability of fractures predicted by FRAX® and observed incidence in the Spanish ECOSAP Study cohort.

Authors:  Jesús González-Macías; Fernando Marin; Joan Vila; Adolfo Díez-Pérez
Journal:  Bone       Date:  2011-11-20       Impact factor: 4.398

Review 5.  Pitfalls in the external validation of FRAX.

Authors:  J A Kanis; A Oden; H Johansson; E McCloskey
Journal:  Osteoporos Int       Date:  2011-11-26       Impact factor: 4.507

6.  Identification of incident fractures: the Geelong Osteoporosis Study.

Authors:  J A Pasco; M J Henry; T M Gaudry; G C Nicholson; M A Kotowicz
Journal:  Aust N Z J Med       Date:  1999-04

Review 7.  Epidemiology and outcomes of osteoporotic fractures.

Authors:  Steven R Cummings; L Joseph Melton
Journal:  Lancet       Date:  2002-05-18       Impact factor: 79.321

8.  The FRAX tool in French women: How well does it describe the real incidence of fracture in the OFELY cohort?

Authors:  Elisabeth Sornay-Rendu; Françoise Munoz; Pierre D Delmas; Roland D Chapurlat
Journal:  J Bone Miner Res       Date:  2010-10       Impact factor: 6.741

9.  Vertebral fracture assessment using a semiquantitative technique.

Authors:  H K Genant; C Y Wu; C van Kuijk; M C Nevitt
Journal:  J Bone Miner Res       Date:  1993-09       Impact factor: 6.741

10.  Prognosis of fracture: evaluation of predictive accuracy of the FRAX algorithm and Garvan nomogram.

Authors:  S K Sandhu; N D Nguyen; J R Center; N A Pocock; J A Eisman; T V Nguyen
Journal:  Osteoporos Int       Date:  2009-07-25       Impact factor: 4.507

View more
  8 in total

1.  Comparison between real-world practice and application of the FRAX algorithm in the treatment of osteoporosis.

Authors:  Francesca Zoccarato; Chiara Ceolin; Caterina Trevisan; Anna Citron; Labjona Haxhiaj; Aurelio Guarnaccia; Matteo Panozzo; Carlotta Campodall'Orto; Alessandra Coin; Sandro Giannini; Giuseppe Sergi
Journal:  Aging Clin Exp Res       Date:  2022-08-16       Impact factor: 4.481

Review 2.  Prediction Models for Osteoporotic Fractures Risk: A Systematic Review and Critical Appraisal.

Authors:  Xuemei Sun; Yancong Chen; Yinyan Gao; Zixuan Zhang; Lang Qin; Jinlu Song; Huan Wang; Irene Xy Wu
Journal:  Aging Dis       Date:  2022-07-11       Impact factor: 9.968

3.  Comparison of fracture risk calculators in elderly fallers: a hospital-based cross-sectional study.

Authors:  Georgi Todorov; Susan Brook; Nicole Quah Qin Xian; Sophia Von Widekind; Bernard Freudenthal; Alexander N Comninos
Journal:  BMJ Open       Date:  2022-07-12       Impact factor: 3.006

4.  Five-year fracture risk assessment in postmenopausal women, using both the POL-RISK calculator and the Garvan nomogram: the Silesia Osteo Active Study.

Authors:  Piotr Zagórski; Elżbieta Tabor; Katarzyna Martela-Tomaszek; Piotr Adamczyk; Wojciech Pluskiewicz
Journal:  Arch Osteoporos       Date:  2021-02-16       Impact factor: 2.617

5.  Performance of HR-pQCT, DXA, and FRAX in the discrimination of asymptomatic vertebral fracture in postmenopausal Chinese women.

Authors:  Meiling Huang; Vivian Wing-Yin Hung; Tsz Kiu Li; Sheung Wai Law; Yulong Wang; Shangjie Chen; Ling Qin
Journal:  Arch Osteoporos       Date:  2021-09-04       Impact factor: 2.617

6.  Bisphosphonate Use for Glucocorticoid-Induced Osteoporosis in Elderly Patients with Immune Thrombocytopenia Receiving Prolonged Steroid Therapy: A Single Institute Retrospective Study.

Authors:  Satoshi Yamasaki; Kenjiro Kamezaki; Yoshikiyo Ito; Takahiko Horiuchi
Journal:  Hematol Rep       Date:  2022-09-19

7.  Systematic review of major osteoporotic fracture to hip fracture incidence rate ratios worldwide: implications for Fracture Risk Assessment Tool (FRAX)-derived estimates.

Authors:  Marlene Chakhtoura; Hiba Dagher; Sima Sharara; Sara Ajjour; Nariman Chamoun; Jane Cauley; Ziyad Mahfoud; Robert Boudreau; Ghada El Hajj Fuleihan
Journal:  J Bone Miner Res       Date:  2021-07-31       Impact factor: 6.390

8.  Association between dairy intake and fracture in an Australian-based cohort of women: a prospective study.

Authors:  Hajara Aslam; Kara L Holloway-Kew; Mohammadreza Mohebbi; Felice N Jacka; Julie A Pasco
Journal:  BMJ Open       Date:  2019-11-21       Impact factor: 2.692

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.