Prognosis of fracture: evaluation of predictive accuracy of the FRAX™ algorithm and Garvan nomogram
- S. K. SandhuAffiliated withOsteoporosis and Bone Biology Program, Garvan Institute of Medical ResearchSt. Vincent’s Hospital
- , N. D. NguyenAffiliated withOsteoporosis and Bone Biology Program, Garvan Institute of Medical Research
- , J. R. CenterAffiliated withOsteoporosis and Bone Biology Program, Garvan Institute of Medical ResearchSt. Vincent’s HospitalUniversity of New South Wales
- , N. A. PocockAffiliated withSt. Vincent’s Hospital
- , J. A. EismanAffiliated withOsteoporosis and Bone Biology Program, Garvan Institute of Medical ResearchSt. Vincent’s HospitalUniversity of New South Wales
- , T. V. NguyenAffiliated withOsteoporosis and Bone Biology Program, Garvan Institute of Medical ResearchUniversity of New South Wales Email author
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We evaluated the prognostic accuracy of fracture risk assessment tool (FRAX™) and Garvan algorithms in an independent Australian cohort. The results suggest comparable performance in women but relatively poor fracture risk discrimination in men by FRAX™. These data emphasize the importance of external validation before widespread clinical implementation of prognostic tools in different cohorts.
Absolute risk assessment is now recognized as a preferred approach to guide treatment decision. The present study sought to evaluate accuracy of the FRAX™ and Garvan algorithms for predicting absolute risk of osteoporotic fracture (hip, spine, humerus, or wrist), defined as major in FRAX™, in a clinical setting in Australia.
A retrospective validation study was conducted in 144 women (69 fractures and 75 controls) and 56 men (31 fractures and 25 controls) aged between 60 and 90 years. Relevant clinical data prior to fracture event were ascertained. Based on these variables, predicted 10-year probabilities of major fracture were calculated from the Garvan and FRAX™ algorithms, using US (FRAX-US) and UK databases (FRAX-UK). Area under the receiver operating characteristic curves (AUC) was computed for each model.
In women, the average 10-year probability of major fracture was consistently higher in the fracture than in the nonfracture group: Garvan (0.33 vs. 0.15), FRAX-US (0.30 vs. 0.19), and FRAX-UK (0.17 vs. 0.10). In men, although the Garvan model yielded higher average probability of major fracture in the fracture group (0.32 vs. 0.14), the FRAX™ algorithm did not: FRAX-US (0.17 vs. 0.19) and FRAX-UK (0.09 vs. 0.12). In women, AUC for the Garvan, FRAX-US, and FRAX-UK algorithms were 0.84, 0.77, and 0.78, respectively, vs. 0.76, 0.54, and 0.57, respectively, in men.
In this analysis, although both approaches were reasonably accurate in women, FRAX™ discriminated fracture risk poorly in men. These data support the concept that all algorithms need external validation before clinical implementation.
KeywordsFracture risk Prognostic models Validation
- Prognosis of fracture: evaluation of predictive accuracy of the FRAX™ algorithm and Garvan nomogram
Volume 21, Issue 5 , pp 863-871
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- Fracture risk
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- Author Affiliations
- 1. Osteoporosis and Bone Biology Program, Garvan Institute of Medical Research, 384 Victoria Street, 2010, Sydney, New South Wales, Australia
- 2. St. Vincent’s Hospital, Sydney, New South Wales, Australia
- 3. University of New South Wales, Sydney, New South Wales, Australia