Literature DB >> 19727909

Selecting men for bone densitometry: performance of osteoporosis risk assessment tools in Portuguese men.

P Machado1, M Coutinho, J A P da Silva.   

Abstract

SUMMARY: Clinicians need tools to identify patients most likely to benefit from bone mineral density (BMD) testing, for which cost-effectiveness does not allow generalized screening. This study supports the utility of osteoporosis risk assessment tools in selecting men for BMD testing. Different cutoff values may be appropriate for different countries and/or ethnic origins.
INTRODUCTION: Our aim was to evaluate the utility of three osteoporosis (OP) risk assessment tools in a large group of Portuguese men aged 50 or more and to determine the best cutoff value to be used for selecting men for bone densitometry.
METHODS: We assessed the performance of three simple tools in 202 randomly selected men: body weight criterion (BWC), osteoporosis self-assessment tool for Asians (OSTA), and a modified version of the OSTA equation (OST). Previously published cutoff values (validated in postmenopausal women) and three additional cutoff values were tested. Sensitivity (SE), specificity (SP), predictive values, and area under the receiver operating characteristic (AUROC) curve for correctly selecting men with OP (defined by BMD testing) were determined.
RESULTS: Mean age of the cohort was 63.8 years. According to the World Health Organization diagnostic categories, 16.8% had osteoporosis. The best performing cutoffs for correctly selecting men with OP for BMD testing were OST < 3 (SE = 75.5%, SP = 50.0%, AUROC = 0.632), OSTA < 3 (SE = 73.5%, SP = 58.3%, AUROC = 0.659), and BWC < 75 kg (SE = 73.5%, SP = 61.3%, AUROC = 0.674).
CONCLUSIONS: OP risk assessment tools seem to be useful in men aged 50 or more. Best cutoff values are different from those recommended for postmenopausal women. Different cutoff values may be appropriate for different countries and/or ethnic origins.

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Mesh:

Year:  2009        PMID: 19727909     DOI: 10.1007/s00198-009-1036-5

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  43 in total

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Authors:  J A Kanis; O Johnell; A Oden; C De Laet; D Mellstrom
Journal:  Calcif Tissue Int       Date:  2004-05-27       Impact factor: 4.333

2.  [Recommendations for the diagnosis and management of osteoporosis].

Authors:  Viviana Tavares; Helena Canhão; José António Melo Gomes; Eugénia Simões; José Carlos Romeu; Paulo Coelho; Rui André Santos; Armando Malcata; Domingos Araújo; Carlos Vaz; Jaime Branco
Journal:  Acta Reumatol Port       Date:  2007 Jan-Mar       Impact factor: 1.290

3.  An assessment tool for predicting fracture risk in postmenopausal women.

Authors:  D M Black; M Steinbuch; L Palermo; P Dargent-Molina; R Lindsay; M S Hoseyni; O Johnell
Journal:  Osteoporos Int       Date:  2001       Impact factor: 4.507

4.  Clinical use of bone densitometry: clinical applications.

Authors:  David W Bates; Dennis M Black; Steven R Cummings
Journal:  JAMA       Date:  2002-10-16       Impact factor: 56.272

5.  Identification of high-risk individuals for hip fracture: a 14-year prospective study.

Authors:  Nguyen D Nguyen; Chatlert Pongchaiyakul; Jacqueline R Center; John A Eisman; Tuan V Nguyen
Journal:  J Bone Miner Res       Date:  2005-05-31       Impact factor: 6.741

6.  FRAX and the assessment of fracture probability in men and women from the UK.

Authors:  J A Kanis; O Johnell; A Oden; H Johansson; E McCloskey
Journal:  Osteoporos Int       Date:  2008-02-22       Impact factor: 4.507

7.  An evaluation of osteoporosis screening tools for the osteoporotic fractures in men (MrOS) study.

Authors:  H S Lynn; J Woo; P C Leung; E L Barrett-Connor; M C Nevitt; J A Cauley; R A Adler; E S Orwoll
Journal:  Osteoporos Int       Date:  2008-02-01       Impact factor: 4.507

8.  Utility of screening tools for the prediction of low bone mass in African American men.

Authors:  B Sinnott; S Kukreja; E Barengolts
Journal:  Osteoporos Int       Date:  2006-03-08       Impact factor: 4.507

9.  Development and validation of the osteoporosis prescreening risk assessment (OPERA) tool to facilitate identification of women likely to have low bone density.

Authors:  Fausto Salaffi; Ferdinando Silveri; Andrea Stancati; Walter Grassi
Journal:  Clin Rheumatol       Date:  2004-11-12       Impact factor: 2.980

Review 10.  Diagnosis of osteoporosis in men, premenopausal women, and children.

Authors: 
Journal:  J Clin Densitom       Date:  2004       Impact factor: 2.963

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  7 in total

Review 1.  Systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for osteoporosis or low bone density.

Authors:  S Nayak; D L Edwards; A A Saleh; S L Greenspan
Journal:  Osteoporos Int       Date:  2015-02-03       Impact factor: 4.507

2.  Association of Osteoporosis Self-Assessment Tool for Asians (OSTA) Score with Clinical Presentation and Expenditure in Hospitalized Trauma Patients with Femoral Fractures.

Authors:  Chien-Chang Chen; Cheng-Shyuan Rau; Shao-Chun Wu; Pao-Jen Kuo; Yi-Chun Chen; Hsiao-Yun Hsieh; Ching-Hua Hsieh
Journal:  Int J Environ Res Public Health       Date:  2016-10-10       Impact factor: 3.390

3.  Association between the Osteoporosis Self-Assessment Tool for Asians Score and Mortality in Patients with Isolated Moderate and Severe Traumatic Brain Injury: A Propensity Score-Matched Analysis.

Authors:  Cheng-Shyuan Rau; Pao-Jen Kuo; Shao-Chun Wu; Yi-Chun Chen; Hsiao-Yun Hsieh; Ching-Hua Hsieh
Journal:  Int J Environ Res Public Health       Date:  2016-12-03       Impact factor: 3.390

4.  Epidemiology of Bone Fracture in Female Trauma Patients Based on Risks of Osteoporosis Assessed using the Osteoporosis Self-Assessment Tool for Asians Score.

Authors:  Cheng-Shyuan Rau; Shao-Chun Wu; Pao-Jen Kuo; Yi-Chun Chen; Peng-Chen Chien; Hsiao-Yun Hsieh; Ching-Hua Hsieh
Journal:  Int J Environ Res Public Health       Date:  2017-11-13       Impact factor: 3.390

Review 5.  Performance of Osteoporosis Self-Assessment Tool (OST) in Predicting Osteoporosis-A Review.

Authors:  Shaanthana Subramaniam; Soelaiman Ima-Nirwana; Kok-Yong Chin
Journal:  Int J Environ Res Public Health       Date:  2018-07-09       Impact factor: 3.390

6.  Brachial-ankle pulse wave velocity is associated with the risk of osteoporosis: a cross-sectional evidence from a Chinese community-based cohort.

Authors:  Kun Tang; Qiao Zhang; Nianchun Peng; Ying Hu; Shujing Xu; Miao Zhang; Rui Wang; Lixin Shi
Journal:  J Orthop Surg Res       Date:  2021-01-04       Impact factor: 2.359

7.  A New Predictive Index for Osteoporosis in Men under 70 Years of Age: An Index to Identify Male Candidates for Osteoporosis Screening by Bone Mineral Density.

Authors:  Lee Oh Kim; Hyeon-Ju Kim; Mi Hee Kong
Journal:  J Osteoporos       Date:  2014-03-03
  7 in total

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