Pitfalls in the external validation of FRAX

Kanis, John А.; Odén, Anders; Johansson, Helena; McCloskey, Eugène

doi:10.1007/s00198-011-1846-0

Cited by 99 publications

(64 citation statements)

References 51 publications

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“…The question of a limited value of comparative studies, focusing on the validation of different fracture risk or probability calculators, was discussed in detail by Kanis et al in the recently published opinion paper [18]. But, regardless of all the presented criticisms, one should agree that the direct comparison of different calculators is still justified by the fact that those diagnostic tools are dedicated to the same practical applications.…”

Section: Discussionmentioning

confidence: 99%

FRAX calculator and Garvan nomogram in male osteoporotic population

et al. 2014

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Section: Discussionmentioning

confidence: 99%

FRAX calculator and Garvan nomogram in male osteoporotic population

et al. 2014

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“…The FRAX algorithm generated an area under the ROC curve (AUC) value of 0.845 for female hip fracture and QFractureScores had a value of 0.89 for the same event. Using this data for a direct comparison of FRAX and QFractureScores may however not be appropriate due to the difficulties encountered in comparing AUCs between studies, particularly when adjustments have not been made for differences in major predictive factors such as age between studies [18]. Recent work in an independent UK and Irish based population using only CRFs indicated that FRAX and QFractureScores were reasonably well correlated (R=0.857) for hip fracture suggesting that both tools could be of value in primary care settings [19].…”

Section: A Comparison Of Frax and Qfracturescoresmentioning

confidence: 99%

Developing Novel Prognostic Biomarkers for Multivariate Fracture Risk Prediction Algorithms

et al. 2012

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Multivariate prediction algorithms such as FRAX ® and QFractureScores provide an opportunity for new prognostic biomarkers to be developed and incorporated, potentially leading to better fracture prediction. As more research is conducted into these novel biomarkers, a number of factors need to be considered for their successful development for inclusion in these algorithms. This review paper describes two well-known multivariate prediction algorithms for osteoporosis fracture risk applicable to the UK population, FRAXand QFractureScores, and comments on the current prognostic tools available for fracture risk, dual x-ray assessment (DXA), quantitative ultrasound (QUS), genomic and biochemical markers and highlights the factors that need to be considered in the development of new biomarkers. These factors include the requirement for prospective data, collected in new cohort studies or using archived samples, the need for adequate stability data to be provided and appropriate storage methods to be used when retrospective data is required. AUC measures have been found to have limited utility in assessing the impact of the addition of new risk factors on the predictive performance multivariate algorithms. New performance evaluation measures, such as net reclassification index (NRI) and integrated discrimination improvement (IDI) are increasingly important in the evaluation of the impact of the addition of new markers to multivariate algorithms and these are also discussed.

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“…In the discussion the authors indicate the importance of having coherent data and models 25 . Among these authors is John Kanis, one of the creators of the FRAX ® model and defender of the validity of this system against various criticisms it has received 26 . Thus, in the search for new options to improve the understanding of the epidemiology of osteoporosis in Spain and increase the options for strategic approaches to this pathology, we present the baseline risk of expected fractures in our cohort using the Spanish FRAX ® model, along with a comparative exercise by applying the models of other European countries.…”

Section: Discussionmentioning

confidence: 99%

Riesgo de fractura en la cohorte FRODOS: estudio comparativo de la aplicación del modelo FRAX® español, francés, inglés y sueco

Kanterewicz

Sierra

Puigoriol

et al. 2014

Rev Osteoporos Metab Miner

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SummaryBackground and objectives: Studies on the validation of FRAX ® in Spain show an underestimation of the risk of principal osteoporotic fractures (POFs) and more accurate predictions for femoral fractures (FF). It has been suggested that this algorithm may be improved with more specific data on the epidemiology of these fractures in Spain. The objectives of this work were to describe the baseline risk of fractures according to the Spanish FRAX ® model in the participants of the FRODOS cohort, and to compare these data with the application of other European models of FRAX ® in the same cohort. Methods: Observational study in a population cohort of 2,968 postmenopausal women (59-70 years of age). The online desktop version of FRAX ® was used for multiple data entries to calculate the risk of POFs and FFs at 10 years using the Spanish, French, British and Swedish models in the same cohort. Results: The lowest risk corresponded to the Spanish model: FF: 1.22% (36 expected fractures) and POF: 5.28% (n=197), while the highest risk was for the Swedish model: FF: 3.15% and POF 13.51% (n=401). The models for France and the United Kingdom had intermediate values. Conclusion:In a Spanish cohort of 2,968 postmenopausal women the percentage risk of expected fractures at 10 years increased following a south-north latitude gradient when different European FRAX

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Pitfalls in the external validation of FRAX

Abstract: Cohort studies that have evaluated the performance of FRAX need to be interpreted with caution and preferably re-evaluated.

Cited by 99 publications

References 51 publications

FRAX calculator and Garvan nomogram in male osteoporotic population

FRAX calculator and Garvan nomogram in male osteoporotic population

Developing Novel Prognostic Biomarkers for Multivariate Fracture Risk Prediction Algorithms

Riesgo de fractura en la cohorte FRODOS: estudio comparativo de la aplicación del modelo FRAX® español, francés, inglés y sueco

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