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      Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women

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          Abstract

          Background

          The FRAX® tool estimates the risk of a fragility fracture among the population and many countries have been evaluating its performance among their populations since its creation in 2007.

          The purpose of this study is to update the first FRIDEX cohort analysis comparing FRAX with the bone mineral density (BMD) model, and its predictive abilities.

          Methods

          The discriminatory ability of the FRAX was assessed using the ‘area under curve’ of the receiver operating characteristic (AUC-ROC). Predictive ability was assessed by comparing estimated risk fractures with incidence fractures after a 10-year follow up period.

          Results

          One thousand three hundred eight women ≥ 40 and ≤ 90 years followed up during a 10-year period. The AUC for major osteoporotic fractures using FRAX without DXA was 0.686 (95 % CI 0.630–0.742) and using FN T-score of DXA 0.714 (95 % CI 0.661–0.767). Using only the traditional parameters of DXA (FN T-score), the AUC was 0.706 (95 % CI 0.652–0.760). The AUC for hip osteoporotic fracture was 0.883 (95 % CI 0.827–0.938), 0.857 (95 % CI 0.773–0.941), and 0.814 (95 % CI 0.712–0.916) respectively. For major osteoporotic fractures, the overall predictive value using the ratio Observed fractures/Expected fractures calculated with FRAX without T-score of DXA was 2.29 and for hip fractures 2.28 and with the inclusion of the T-score 2.01 and 1.83 respectively. However, for hip fracture in women < 65 years was 1.53 and 1.24 respectively.

          Conclusions

          The FRAX tool has been found to show a good discriminatory capacity for detecting women at high risk of fragility fracture, and is better for hip fracture than major fracture. The test of sensibility shows that it is, at least, not inferior than when using BMD model alone. The predictive capacity of FRAX tool needs some adjustment. This capacity is better for hip fracture prediction and better for women < 65 years. Further studies in Catalonia and other regions of Spain are needed to fine tune the FRAX tool’s predictive capability.

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          Most cited references41

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          European guidance for the diagnosis and management of osteoporosis in postmenopausal women

          Summary Guidance is provided in a European setting on the assessment and treatment of postmenopausal women at risk of fractures due to osteoporosis. Introduction The International Osteoporosis Foundation and European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis published guidance for the diagnosis and management of osteoporosis in 2008. This manuscript updates these in a European setting. Methods Systematic literature reviews. Results The following areas are reviewed: the role of bone mineral density measurement for the diagnosis of osteoporosis and assessment of fracture risk, general and pharmacological management of osteoporosis, monitoring of treatment, assessment of fracture risk, case finding strategies, investigation of patients and health economics of treatment. Conclusions A platform is provided on which specific guidelines can be developed for national use.
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            Predictive value of BMD for hip and other fractures.

            The relationship between BMD and fracture risk was estimated in a meta-analysis of data from 12 cohort studies of approximately 39,000 men and women. Low hip BMD was an important predictor of fracture risk. The prediction of hip fracture with hip BMD also depended on age and z score. The aim of this study was to quantify the relationship between BMD and fracture risk and examine the effect of age, sex, time since measurement, and initial BMD value. We studied 9891 men and 29,082 women from 12 cohorts comprising EVOS/EPOS, EPIDOS, OFELY, CaMos, Rochester, Sheffield, Rotterdam, Kuopio, DOES, Hiroshima, and 2 cohorts from Gothenburg. Cohorts were followed for up to 16.3 years and a total of 168,366 person-years. The effect of BMD on fracture risk was examined using a Poisson model in each cohort and each sex separately. Results of the different studies were then merged using weighted coefficients. BMD measurement at the femoral neck with DXA was a strong predictor of hip fractures both in men and women with a similar predictive ability. At the age of 65 years, risk ratio increased by 2.94 (95% CI = 2.02-4.27) in men and by 2.88 (95% CI = 2.31-3.59) in women for each SD decrease in BMD. However, the effect was dependent on age, with a significantly higher gradient of risk at age 50 years than at age 80 years. Although the gradient of hip fracture risk decreased with age, the absolute risk still rose markedly with age. For any fracture and for any osteoporotic fracture, the gradient of risk was lower than for hip fractures. At the age of 65 years, the risk of osteoporotic fractures increased in men by 1.41 per SD decrease in BMD (95% CI = 1.33-1.51) and in women by 1.38 per SD (95% CI = 1.28-1.48). In contrast with hip fracture risk, the gradient of risk increased with age. For the prediction of any osteoporotic fracture (and any fracture), there was a higher gradient of risk the lower the BMD. At a z score of -4 SD, the risk gradient was 2.10 per SD (95% CI = 1.63-2.71) and at a z score of -1 SD, the risk was 1.73 per SD (95% CI = 1.59-1.89) in men and women combined. A similar but less pronounced and nonsignificant effect was observed for hip fractures. Data for ultrasound and peripheral measurements were available from three cohorts. The predictive ability of these devices was somewhat less than that of DXA measurements at the femoral neck by age, sex, and BMD value. We conclude that BMD is a risk factor for fracture of substantial importance and is similar in both sexes. Its validation on an international basis permits its use in case finding strategies. Its use should, however, take account of the variations in predictive value with age and BMD.
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              A meta-analysis of previous fracture and subsequent fracture risk.

              Previous fracture is a well-documented risk factor for future fracture. The aim of this study was to quantify this risk on an international basis and to explore the relationship of this risk with age, sex, and bone mineral density (BMD). We studied 15259 men and 44902 women from 11 cohorts comprising EVOS/EPOS, OFELY, CaMos, Rochester, Sheffield, Rotterdam, Kuopio, DOES, Hiroshima, and two cohorts from Gothenburg. Cohorts were followed for a total of 250000 person-years. The effect of a prior history of fracture on the risk of any fracture, any osteoporotic fracture, and hip fracture alone was examined using a Poisson model for each sex from each cohort. Covariates examined were age, sex, and BMD. The results of the different studies were merged by using the weighted beta-coefficients. A previous fracture history was associated with a significantly increased risk of any fracture compared with individuals without a prior fracture (RR = 1.86; 95% CI = 1.75-1.98). The risk ratio was similar for the outcome of osteoporotic fracture or for hip fracture. There was no significant difference in risk ratio between men and women. Risk ratio (RR) was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any fracture (8%) and for hip fracture (22%). The risk ratio was stable with age except in the case of hip fracture outcome where the risk ratio decreased significantly with age. We conclude that previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by measurement of BMD. Its validation on an international basis permits the use of this risk factor in case finding strategies.
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                Author and article information

                Contributors
                +34 972 245 350 , +34 972 405 402 , mzwart.girona.ics@gencat.cat
                Journal
                BMC Musculoskelet Disord
                BMC Musculoskelet Disord
                BMC Musculoskeletal Disorders
                BioMed Central (London )
                1471-2474
                17 June 2016
                17 June 2016
                2016
                : 17
                : 262
                Affiliations
                [ ]Department of Medicine, Universitat Autònoma de Barcelona, ps/Vall de Hebron 119, 08135 Barcelona, Spain
                [ ]Health Center Badia del Valles, Institut Català de la Salut, GROIMAP-USR MN-IDIAP Jordi Gol, c/Bética s/n, 08214 Badia del Vallés, Barcelona Spain
                [ ]QuironSalud-Hospital General de Catalunya, Universitat Internacional de Catalunya, c/Josep Trueta s/n, 08195 Sant Cugat del Vallès, Barcelona Spain
                [ ]Health Center Can Gibert del Plà (ICS), Institut Català de la Salut, GROIMAP-USR Girona-IDIAP Jordi Gol, c/San Sebastian 9, 17005 Girona, Spain
                [ ]Department of Nuclear Medicine, Valle de Hebron Hospital, Institut Català de la Salut, Ps/Valle de Hebron 119-129, 08035 Barcelona, Spain
                [ ]Health Center Granollers-Centre, Institut Català de la Salut, c/Museu 19, 08400 Granollers, Barcelona Spain
                [ ]Department of Basic Sciences, Biostatistics Unit, Universitat Internacional de Catalunya, c/Josep Trueta s/n, 08195 Sant Cugat del Valles, Barcelona Spain
                [ ]Health Center Barberà del Vallès, Institut Català de la Salut, GROIMAP-USR MN-IDIAP Jordi Gol, c/Verge de l’Assumpció s/n, 08210 Barberà del Vallès, Barcelona Spain
                [ ]Health Center Canaletes, Institut Català de la Salut, GROIMAP-USR MN-IDIAP Jordi Gol, c/Ps d’Horta 17, 08290 Cerdanyola del Vallès, Barcelona Spain
                [ ]Department of Medicine, Universitat Internacional de Catalunya, c/Josep Trueta s/n, 08195 Sant Cugat del Valles, Barcelona Spain
                [ ]Urgencies Service, Hospital of Sabadell, Corporació Sanitaria i Universitaria Parc Tauli, Parc Tauli s/n, 08208, Sabadell, Barcelona Spain
                [ ]Unit of Infections and Cancer (UNIC), Cancer Epidemiology Research Program (CERP), Catalan Institute of Oncology (ICO)-IDIBELL, Av Gran Via, 199-203, 08908 L’Hospitalet de Llobregat, Barcelona Spain
                [ ]Departament d’Economia i Història Econòmica, Grups de Recerca d’Àfrica i Amèrica Llatines (GRAAL), Unitat de Fonaments de l’Anàlisi Econòmica, Universitat Autònoma de Barcelona, c/Emprius 2, 08202 Sabadell, Barcelona Spain
                [ ]Health Center Cornellà 2 (Sant Ildefons), Institut Català de la Salut, GROIMAP-USR MN-IDIAP Jordi Gol, c/Republica Argentina s/n, 08940 Cornellá, Barcelona Spain
                [ ]Biostatistics Unit, CUPESSE European Project, Universitat Pompeu Fabra, Ed Jaume I-Campus Ciutadella, 08003 Barcelona, Spain
                [ ]Unitat Supor Recerca Metropolitana Nord, IDIAP Jordi Gol, ctra de Barcelona 473, 08204 Sabadell, Barcelona Spain
                [ ]Department of Nursing, Universitat Autònoma de Barcelona, avda Can Domenech s/n, 08193 Cerdanyola del Valles, Barcelona Spain
                Article
                1096
                10.1186/s12891-016-1096-6
                4912785
                27317560
                391d1bbf-752e-48d2-9829-5dede668ef85
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 18 February 2016
                : 24 May 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004587, Instituto de Salud Carlos III;
                Award ID: PI09/90507
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Orthopedics
                osteoporosis,fracture,frax,fridex,study cohort,algorithm
                Orthopedics
                osteoporosis, fracture, frax, fridex, study cohort, algorithm

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