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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
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912785/ https://www.ncbi.nlm.nih.gov/pubmed/27317560 http://dx.doi.org/10.1186/s12891-016-1096-6 |
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author | Azagra, Rafael Zwart, Marta Encabo, Gloria Aguyé, Amada Martin-Sánchez, Juan Carlos Puchol-Ruiz, Nuria Gabriel-Escoda, Paula Ortiz-Alinque, Sergio Gené, Emilio Iglesias, Milagros Moriña, David Diaz-Herrera, Miguel Angel Utzet, Mireia Manresa, Josep Maria |
author_facet | Azagra, Rafael Zwart, Marta Encabo, Gloria Aguyé, Amada Martin-Sánchez, Juan Carlos Puchol-Ruiz, Nuria Gabriel-Escoda, Paula Ortiz-Alinque, Sergio Gené, Emilio Iglesias, Milagros Moriña, David Diaz-Herrera, Miguel Angel Utzet, Mireia Manresa, Josep Maria |
author_sort | Azagra, Rafael |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4912785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49127852016-06-19 Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women Azagra, Rafael Zwart, Marta Encabo, Gloria Aguyé, Amada Martin-Sánchez, Juan Carlos Puchol-Ruiz, Nuria Gabriel-Escoda, Paula Ortiz-Alinque, Sergio Gené, Emilio Iglesias, Milagros Moriña, David Diaz-Herrera, Miguel Angel Utzet, Mireia Manresa, Josep Maria BMC Musculoskelet Disord Research Article 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. BioMed Central 2016-06-17 /pmc/articles/PMC4912785/ /pubmed/27317560 http://dx.doi.org/10.1186/s12891-016-1096-6 Text en © 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. |
spellingShingle | Research Article Azagra, Rafael Zwart, Marta Encabo, Gloria Aguyé, Amada Martin-Sánchez, Juan Carlos Puchol-Ruiz, Nuria Gabriel-Escoda, Paula Ortiz-Alinque, Sergio Gené, Emilio Iglesias, Milagros Moriña, David Diaz-Herrera, Miguel Angel Utzet, Mireia Manresa, Josep Maria Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women |
title | Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women |
title_full | Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women |
title_fullStr | Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women |
title_full_unstemmed | Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women |
title_short | Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women |
title_sort | rationale of the spanish frax model in decision-making for predicting osteoporotic fractures: an update of fridex cohort of spanish women |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912785/ https://www.ncbi.nlm.nih.gov/pubmed/27317560 http://dx.doi.org/10.1186/s12891-016-1096-6 |
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