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DOI: 10.1055/s-0041-1741408
Performance of the Fracture Risk Assessment Tool Associated with Muscle Mass Measurements and Handgrip to Screen for the Risk of Osteoporosis in Young Postmenopausal Women
Desempenho da ferramenta de avaliação de risco de fraturas associada à medida de massa muscular e à preensão manual no rastreio de risco de osteoporose em mulheres jovens pós-menopáusicas![](https://www.thieme-connect.de/media/10.1055-s-00030576/202201/lookinside/thumbnails/10-1055-s-0041-1741408_200393-1.jpg)
Abstract
Objective To evaluate the improvement in screening accuracy of the Fracture Risk Assessment Tool (FRAX) for the risk of developing osteoporosis among young postmenopausal women by associating with it clinical muscle mass measures.
Methods A sample of postmenopausal women was submitted to calcaneal quantitative ultrasound (QUS), application of the FRAX questionnaire, and screening for the risk of developing sarcopenia at a health fair held in the city of São Bernardo do Campo in 2019. The sample also underwent anthropometric measurements, muscle mass, walking speed and handgrip tests. A major osteoporotic fracture (MOF) risk ≥ 8.5% on the FRAX, a classification of medium risk on the clinical guideline of the National Osteoporosis Guideline Group (NOGG), and a QUS T-score ≤ -1.8 sd were considered risks of having low bone mass, and QUS T-score ≤ -2.5sd, risk of having fractures.
Results In total, 198 women were evaluated, with a median age of 64 ± 7.7 years, median body mass index (BMI) of 27.3 ± 5.3 kg/m2 and median QUS T-score of −1.3 ± 1.3 sd. The accuracy of the FRAX with a MOF risk ≥ 8.5% to identify women with T-scores ≤ -1.8 sd was poor, with an area under the curve (AUC) of 0.604 (95% confidence interval [95%CI]: 0.509–0.694) for women under 65 years of age, and of 0.642 (95%CI: 0.571–0.709) when age was not considered. Including data on muscle mass in the statistical analysis led to a significant improvement for the group of women under 65 years of age, with an AUC of 0,705 (95%CI: 0.612–0.786). The ability of the high-risk NOGG tool to identify T-scores ≤ -1.8 sd was limited.
Conclusion Clinical muscle mass measurements increased the accuracy of the FRAX to screen for osteoporosis in women aged under 65 years.
Resumo
Objetivo Avaliar a melhora da precisão da Fracture Risk Assessment Tool (Ferramenta de Avaliação do Risco de Fraturas, FRAX, em inglês) no rastreio do risco de desenvolver osteoporose em mulheres jovens pós-menopáusicas com a associação de medidas clínicas de massa muscular e preensão manual.
Métodos Uma amostra de mulheres pós-menopáusicas foi submetida a ultrassom quantitativo (USQ) de calcâneo, à aplicação do questionário FRAX, e rastreadas quanto ao risco de desenvolver sarcopenia em uma feira de saúde realizada em 2019 em São Bernardo do Campo. Além disso, a amostra também foi submetida a antropometria, e a testes de massa muscular, velocidade de marcha, e preensão manual. Um risco de grandes fraturas osteoporóticas (GFOs) ≥ 8,5% no FRAX, classificação de médio risco nas diretrizes clínicas do National Osteoporosis Guideline Group (NOGG), e T-score no USQ ≤ -1,8 dp foram considerados riscos de ter baixa massa óssea, e T-score no QUS ≤ -2,5 sd, risco de ter fraturas.
Resultados Ao todo, 198 mulheres foram avaliadas, com idade média de 64 ± 7,7 anos, índice de massa corporal (IMC) médio de 27,3 ± 5,3 kg/m2, e T-score médio no USQ de -1,3 ± 1,3 sd. A precisão do FRAX com um risco de GFO ≥ 8,5% para identificar mulheres com T-score ≤ -1,8 dp foi precária, com uma área sob a curva (ASC) de 0,604 (intervalo de confiança de 95% [IC95%]: 0,509–0,694), para mulheres menores de 65 anos de idade, e de 0,642 (IC95%: 0,571–0,709) quando a idade não foi considerada. A inclusão de dados da massa muscular na análise estatística levou a uma melhora significativa no grupo menor de 65 anos de idade, com uma ASC de 0,705 (IC95%: 0,612–0,786). A habilidade da ferramenta NOGG de alto risco para identificar T-scores ≤ -1,8 dp foi limitada.
Conclusão As medidas clínicas da massa muscular aumentaram a precisão do FRAX no rastreio de osteoporose em mulheres menores de 65 anos de idade.
Contributors
All authors participated in the concept and design of the study, in the analysis and interpretation of data, in the draft or revision of the manuscript, and they have approved the manuscript as submitted. All authors are responsible for the reported research.
Publication History
Received: 05 October 2020
Accepted: 13 October 2021
Article published online:
29 January 2022
© 2022. Federação Brasileira de Ginecologia e Obstetrícia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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References
- 1 Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int 2006; 17 (12) 1726-1733 DOI: 10.1007/s00198-006-0172-4.
- 2 International Osteoporosis Foundation (IOF). Capture the fracture [Internet]. 2012 [cited 2017 Mar 9]. Available from: https://www.osteoporosis.foundation/capture-fracture-pt
- 3 Moayyeri A, Adams JE, Adler RA, Krieg MA, Hans D, Compston J. et al. Quantitative ultrasound of the heel and fracture risk assessment: an updated meta-analysis. Osteoporos Int 2012; 23 (01) 143-153 DOI: 10.1007/s00198-011-1817-5.
- 4 Reid IR. Short-term and long-term effects of osteoporosis therapies. Nat Rev Endocrinol 2015; 11 (07) 418-428 DOI: 10.1038/nrendo.2015.71.
- 5 Järvinen TL, Michaëlsson K, Aspenberg P, Sievänen H. Osteoporosis: the emperor has no clothes. J Intern Med 2015; 277 (06) 662-673 DOI: 10.1111/joim.12366.
- 6 Pecina JL, Romanovsky L, Merry SP, Kennel KA, Thacher TD. Comparison of clinical risk tools for predicting osteoporosis in women ages 50–64. J Am Board Fam Med 2016; 29 (02) 233-239 DOI: 10.3122/jabfm.2016.02.150237.
- 7 Dawson-Hughes B, Tosteson AN, Melton III LJ, Baim S, Favus MJ, Khosla S. et al. National Osteoporosis Foundation Guide Committee. Implications of absolute fracture risk assessment for osteoporosis practice guidelines in the USA. Osteoporos Int 2008; 19 (04) 449-458 DOI: 10.1007/s00198-008-0559-5.
- 8 Radominski SC, Bernardo W, Paula AP, Albergaria BH, Moreira C, Fernandes CE. et al. Diretrizes brasileiras para o diagnóstico e tratamento da osteoporose em mulheres na pós-menopausa. Rev Bras Reumatol 2017; 57 (Suppl. 02) 452-466 DOI: 10.1016/j.rbr.2017.06.001.
- 9 Bastos-Silva Y, Aguiar LB, Pinto-Neto AM, Baccaro LF, Costa-Paiva L. Correlation between osteoporotic fracture risk in Brazilian postmenopausal women calculated using the FRAX with and without the inclusion of bone densitometry data. Arch Osteoporos 2016; 11: 16 DOI: 10.1007/s11657-015-0255-y.
- 10 Oudshoorn C, Hartholt KA, Zillikens MC, Panneman MJ, van der Velde N, Colin EM. et al. Emergency department visits due to vertebral fractures in the Netherlands, 1986-2008: steep increase in the oldest old, strong association with falls. Injury 2012; 43 (04) 458-461 DOI: 10.1016/j.injury.2011.09.014.
- 11 Su Y, Leung J, Kwok T. The role of previous falls in major osteoporotic fracture prediction in conjunction with FRAX in older Chinese men and women: the Mr. OS and Ms. OS cohort study in Hong Kong. Osteoporos Int 2018; 29 (02) 355-363 DOI: 10.1007/s00198-017-4277-8.
- 12 Crandall CJ, Larson JC, Watts NB, Gourlay ML, Donaldson MG, LaCroix A. et al. Comparison of fracture risk prediction by the US Preventive Services Task Force strategy and two alternative strategies in women 50-64 years old in the Women's Health Initiative. J Clin Endocrinol Metab 2014; 99 (12) 4514-4522 DOI: 10.1210/jc.2014-2332.
- 13 Ibrahim K, Mullee M, Yao GL, Zhu S, Baxter M, Tilly S. et al. Southampton Arm Fracture Frailty and Sarcopenia Study (SAFFSS): a study protocol for the feasibility of assessing frailty and sarcopenia among older patients with an upper limb fracture. BMJ Open 2019; 9 (08) e031275 DOI: 10.1136/bmjopen-2019-031275.
- 14 Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T. et al. Writing Group for the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and the Extended Group for EWGSOP2. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 2019; 48 (01) 16-31 DOI: 10.1093/ageing/afy169.
- 15 Greco EA, Pietschmann P, Migliaccio S. Osteoporosis and sarcopenia increase frailty syndrome in the elderly. Front Endocrinol (Lausanne) 2019; 10: 255 DOI: 10.3389/fendo.2019.00255.
- 16 Malmstrom TK, Miller DK, Simonsick EM, Ferrucci L, Morley JE. SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes. J Cachexia Sarcopenia Muscle 2016; 7 (01) 28-36 DOI: 10.1002/jcsm.12048.
- 17 Reginster JY, Beaudart C, Buckinx F, Bruyère O. Osteoporosis and sarcopenia: two diseases or one?. Curr Opin Clin Nutr Metab Care 2016; 19 (01) 31-36 DOI: 10.1097/MCO.0000000000000230.
- 18 Lee RC, Wang Z, Heo M, Ross R, Janssen I, Heymsfield SB. Total-body skeletal muscle mass: development and cross-validation of anthropometric prediction models. Am J Clin Nutr 2000; 72 (03) 796-803 DOI: 10.1093/ajcn/72.3.796.
- 19 Chien MY, Huang TY, Wu YT. Prevalence of sarcopenia estimated using a bioelectrical impedance analysis prediction equation in community-dwelling elderly people in Taiwan. J Am Geriatr Soc 2008; 56 (09) 1710-1715 DOI: 10.1111/j.1532-5415.2008.01854.x.
- 20 Newman AB, Haggerty CL, Goodpaster B, Harris T, Kritchevsky S, Nevitt M. et al. Health Aging And Body Composition Research Group. Strength and muscle quality in a well-functioning cohort of older adults: the Health, Aging and Body Composition Study. J Am Geriatr Soc 2003; 51 (03) 323-330 DOI: 10.1046/j.1532-5415.2003.51105.x.
- 21 Delmonico MJ, Harris TB, Lee JS, Visser M, Nevitt M, Kritchevsky SB. et al. Health, Aging and Body Composition Study. Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc 2007; 55 (05) 769-774 DOI: 10.1111/j.1532-5415.2007.01140.x.
- 22 Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR. et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998; 147 (08) 755-763 DOI: 10.1093/oxfordjournals.aje.a009520.
- 23 Barbosa-Silva TG, Menezes AM, Bielemann RM, Malmstrom TK, Gonzalez MC. Grupo de Estudos em Composição Corporal e Nutrição (COCONUT). Enhancing SARC-F: improving sarcopenia screening in the clinical practice. J Am Med Dir Assoc 2016; 17 (12) 1136-1141 DOI: 10.1016/j.jamda.2016.08.004.
- 24 Studenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB. et al. The FNIH sarcopenia project: rationale, study description, conference recommendations, and final estimates. J Gerontol A Biol Sci Med Sci 2014; 69 (05) 547-558 DOI: 10.1093/gerona/glu01.
- 25 Lohman TG, Roche AF, Martorell R. Eds. Anthropometric standardization reference manual. Champaign: Human Kinetics; 1988
- 26 Dodds RM, Syddall HE, Cooper R, Benzeval M, Deary IJ, Dennison EM. et al. Grip strength across the life course: normative data from twelve British studies. PLoS One 2014; 9 (12) e113637 DOI: 10.1371/journal.pone.0113637.
- 27 Bischoff HA, Stähelin HB, Monsch AU, Iversen MD, Weyh A, von Dechend M. et al. Identifying a cut-off point for normal mobility: a comparison of the timed ‘up and go’ test in community-dwelling and institutionalised elderly women. Age Ageing 2003; 32 (03) 315-320 DOI: 10.1093/ageing/32.3.315.
- 28 World Health Organization. WHO scientific group on the assessment of osteoporosis at primary health care level [Internet]. Geneva: WHO; 2007 [cited 2020 Jun 17]. Available from: http://who.int/chp/topics/Osteoporosis.pdf
- 29 Frost ML, Blake GM, Fogelman I. Can the WHO criteria for diagnosing osteoporosis be applied to calcaneal quantitative ultrasound?. Osteoporos Int 2000; 11 (04) 321-330 DOI: 10.1007/s001980070121.
- 30 DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988; 44 (03) 837-845
- 31 Farmer ME, Harris T, Madans JH, Wallace RB, Cornoni-Huntley J, White LR. Anthropometric indicators and hip fracture. The NHANES I epidemiologic follow-up study. J Am Geriatr Soc 1989; 37 (01) 9-16 DOI: 10.1111/j.1532-5415.1989.tb01562.x.
- 32 Faulkner KG, Cummings SR, Black D, Palermo L, Glüer CC, Genant HK. Simple measurement of femoral geometry predicts hip fracture: the study of osteoporotic fractures. J Bone Miner Res 1993; 8 (10) 1211-1217 DOI: 10.1002/jbmr.5650081008.
- 33 Doherty DA, Sanders KM, Kotowicz MA, Prince RL. Lifetime and five-year age-specific risks of first and subsequent osteoporotic fractures in postmenopausal women. Osteoporos Int 2001; 12 (01) 16-23 DOI: 10.1007/s001980170152.