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      Comparisons of Different Screening Tools for Identifying Fracture/Osteoporosis Risk Among Community-Dwelling Older People

      , MD, MS, , MS, , MD, , RN, MS, , MS, , PhD

      Medicine

      Wolters Kluwer Health

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          Abstract

          A prospective study was conducted to compare criterion, predictive, and construct validities of 9 fracture/osteoporosis assessment tools, including calcaneal quantitative ultrasonography (QUS), Age Bulk One or Never Estrogens (ABONE), body weight criterion (BWC), Fracture Risk Assessment Tool (FRAX), Garvan fracture risk calculator (GARVAN), Osteoporosis Risk Assessment Instrument (ORAI), Osteoporosis Index of Risk (OSIRIS), Osteoporosis Self-Assessment Tool for Asians (OSTA), and Simple Calculated Osteoporosis Risk Estimation (SCORE), among older men and women in Taiwan.

          Using the femoral neck dual-energy x-ray absorptiometry (DXA) T-score as an external criterion, the sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and the area under the receiver operating characteristic curve (AUC) for each tool were calculated. The ability of these tools to predict injurious falls was examined. A principal component analysis was applied to understand whether these tools were measuring the same underlying construct.

          The FRAX, BWC, ORAI, OSIRIS, OSTA, and SCORE had AUCs of ≥0.8 in men, while the GARVAN, OSIRIS, OSTA, and SCORE had AUCs of ≥0.8 in women. The sensitivity, negative predictive value, and likelihood ratio of the ABONE, BWC, ORAI, OSIRIS, OSTA, and SCORE tools in both men and women were 100%, ≥90%, and 0.0, respectively; the specificity and positive predictive value and likelihood ratio were far from satisfactory. The GARVAN displayed the best predictive ability of a fall in both men (AUCs, 0.653–0.686) and women (AUCs, 0.560–0.567), despite being smaller in women. The 9 screening tools and 2 central DXA measurements assessed 5 different factors, while the ABONE, BWC, ORAI, OSIRIS, OSTA, and SCORE measured the same one.

          Simple self-assessment tools can serve as initial screening instruments to rule out persons who have osteoporosis; however, these tools may measure a different construct other than fracture/osteoporosis risk.

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          Most cited references 22

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          Interventions for preventing falls in older people living in the community

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            Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group.

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              Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks.

              We have developed clinical nomograms for predicting 5-year and 10-year fracture risks for any elderly man or woman. The nomograms used age and information concerning fracture history, fall history, and BMD T-score or body weight. Although many fracture risk factors have been identified, the translation of these risk factors into a prognostic model that can be used in primary care setting has not been well realized. The present study sought to develop a nomogram that incorporates non-invasive risk factors to predict 5-year and 10-year absolute fracture risks for an individual man and woman. The Dubbo Osteoporosis Epidemiology Study was designed as a community-based prospective study, with 1358 women and 858 men aged 60+ years as at 1989. Baseline measurements included femoral neck bone mineral density (FNBMD), prior fracture, a history of falls and body weight. Between 1989 and 2004, 426 women and 149 men had sustained a low-trauma fracture (not including morphometric vertebral fractures). Two prognostic models based on the Cox's proportional hazards analysis were considered: model I included age, BMD, prior fracture and falls; and model II included age, weight, prior fracture and fall. Analysis of the area under the receiver operating characteristic curve (AUC) suggested that model I (AUC = 0.75 for both sexes) performed better than model II (AUC = 0.72 for women and 0.74 for men). Using the models' estimates, we constructed various nomograms for individualizing the risk of fracture for men and women. If the 5-year risk of 10% or greater is considered "high risk", then virtually all 80-year-old men with BMD T-scores < -1.0 or 80-year-old women with T-scores < -2.0 were predicted to be in the high risk group. A 60-year-old woman's risk was considered high risk only if her BMD T-scores < or = -2.5 and with a prior fracture; however, no 60-year-old men would be in the high risk regardless of their BMD and risk profile. These data suggest that the assessment of fracture risk for an individual cannot be based on BMD alone, since there are clearly various combinations of factors that could substantially elevate an individual's risk of fracture. The nomograms presented here can be useful for individualizing the short- and intermediate-term risk of fracture and identifying high-risk individuals for intervention to reduce the burden of fracture in the general population.
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                Author and article information

                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MEDI
                Medicine
                Wolters Kluwer Health
                0025-7974
                1536-5964
                May 2016
                20 May 2016
                : 95
                : 20
                Affiliations
                From the Department of Emergency Medicine (S-JC), Tri-Service General Hospital, National Defense Medical Center; Graduate Institute of Injury Prevention and Control (S-JC, C-YC, M-RL), College of Public Health and Nutrition, Taipei Medical University; Department of Nursing (Y-JC), Cathay General Hospital, Taipei; Department of Emergency Medicine (C-HC), Taichung Branch, Tzu-Chi General Hospital, Taichung, and Department of Nursing (Hei-FH), National Taipei University of Nursing and Health Science, Taipei, Taiwan.
                Author notes
                Correspondence: Mau-Roung Lin, Graduate Institute of Injury Prevention and Control, College of Public Health and Nutrition, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan (e-mail: mrlin@ 123456tmu.edu.tw ).
                Article
                03415
                10.1097/MD.0000000000003415
                4902389
                27196447
                Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.

                This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0

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