A systematic review on the performance of fracture risk assessment tools: FRAX, DeFRA, FRA-HS

Journal of Endocrinological Investigation - Tập 46 - Trang 2287-2297 - 2023
G. Adami1, A. Biffi2,3, G. Porcu2,3, R. Ronco2,3, R. Alvaro4, R. Bogini5, A. P. Caputi6, L. Cianferotti7, B. Frediani8, D. Gatti1, S. Gonnelli9, G. Iolascon10, A. Lenzi11, S. Leone12, S. Migliaccio13, T. Nicoletti14, M. Paoletta10, A. Pennini4, E. Piccirilli15,16, U. Tarantino15,16, M. L. Brandi7, G. Corrao2,3, M. Rossini1, R. Michieli17
1Rheumatology Unit, University of Verona, Verona, Italy
2Department of Statistics and Quantitative Methods, National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
3Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
4Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
5Local Health Unit (USL) Umbria, Perugia, Italy
6Department of Pharmacology, School of Medicine, University of Messina, Messina, Italy
7Italian Bone Disease Research Foundation (FIRMO), Florence, Italy
8Department of Medicine, Surgery and Neurosciences, Rheumatology Unit, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
9Department of Medicine, Surgery and Neuroscience, Policlinico Le Scotte, University of Siena, Siena, Italy
10Department of Medical and Surgical Specialties and Dentistry, University of Campania “Luigi Vanvitelli”, Naples, Italy
11Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
12AMICI ONLUS, Associazione nazionale per le Malattie Infiammatorie Croniche dell’Intestino, Milan, Italy
13Department of Movement, Human and Health Sciences, Foro Italico University, Rome, Italy
14Coordinamento Nazionale delle Associazioni dei Malati Cronici e rari di Cittadinanzattiva, CnAMC, Rome, Italy
15Department of Clinical Sciences and Translational Medicine, University of Rome Tor Vergata, Rome, Italy
16Department of Orthopedics and Traumatology, “Policlinico Tor Vergata” Foundation, Rome, Italy
17Italian Society of General Medicine and Primary Care (SIMG), Florence, Italy

Tóm tắt

Preventing fragility fractures by treating osteoporosis may reduce disability and mortality worldwide. Algorithms combining clinical risk factors with bone mineral density have been developed to better estimate fracture risk and possible treatment thresholds. This systematic review supported panel members of the Italian Fragility Fracture Guidelines in recommending the use of best-performant tool. The clinical performance of the three most used fracture risk assessment tools (DeFRA, FRAX, and FRA-HS) was assessed in at-risk patients. PubMed, Embase, and Cochrane Library were searched till December 2020 for studies investigating risk assessment tools for predicting major osteoporotic or hip fractures in patients with osteoporosis or fragility fractures. Sensitivity (Sn), specificity (Sp), and areas under the curve (AUCs) were evaluated for all tools at different thresholds. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies-2; certainty of evidence (CoE) was evaluated using the Grading of Recommendations Assessment, Development and Evaluation approach. Forty-three articles were considered (40, 1, and 2 for FRAX, FRA-HS, and DeFRA, respectively), with the CoE ranging from very low to high quality. A reduction of Sn and increase of Sp for major osteoporotic fractures were observed among women and the entire population with cut-off augmentation. No significant differences were found on comparing FRAX to DeFRA in women (AUC 59–88% vs. 74%) and diabetics (AUC 73% vs. 89%). FRAX demonstrated non-significantly better discriminatory power than FRA-HS among men. The task force formulated appropriate recommendations on the use of any fracture risk assessment tools in patients with or at risk of fragility fractures, since no statistically significant differences emerged across different prediction tools.

Tài liệu tham khảo

Kanis JA, Norton N, Harvey NC, Jacobson T, Johansson H, Lorentzon M et al (2021) SCOPE 2021: a new scorecard for osteoporosis in Europe. Arch Osteoporos 16:82 Black DM, Rosen CJ (2016) Clinical practice. Postmenopausal osteoporosis. N Engl J Med 374:254–262 Bouxsein ML, Eastell R, Lui LY, Wu LA, de Papp AE, Grauer A et al (2019) Change in bone density and reduction in fracture risk: a meta-regression of published trials. J Bone Miner Res 34:632–642 Watts NB, Manson JE (2017) Osteoporosis and fracture risk evaluation and management: shared decision making in clinical practice. JAMA 317:253–254 Adami S, Bianchi G, Brandi ML, Di Munno O, Frediani B, Gatti D et al (2010) Validation and further development of the WHO 10-year fracture risk assessment tool in Italian postmenopausal women: project rationale and description. Clin Exp Rheumatol 28:561–570 Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E (2008) FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19:385–397 Adami S, Bertoldo F, Gatti D, Minisola G, Rossini M, Sinigaglia L et al (2013) Treatment thresholds for osteoporosis and reimbursability criteria: Perspectives associated with fracture risk-assessment tools. Calcif Tissue Int 93:195–200 Francesco L, Elisa B, Raffaella M, Alessandro P, Iacopo C, Giampiero M et al (2017) Assessing risk of osteoporotic fractures in primary care: development and validation of the FRA-HS algorithm. Calcif Tissue Int 100:537–549 Bonaccorsi G, Fila E, Cervellati C, Romani A, Giganti M, Rossini M et al (2015) Assessment of fracture risk in a population of postmenopausal italian women: a comparison of two different tools. Calcif Tissue Int 97:50–57 Milan Bicocca University and Italian National Institute of Health (2021) Diagnosi, stratificazione del rischio e continuità assistenziale delle Fratture da Fragilità. SNLG Sistema Nazionale per le Linee Guida. https://snlg.iss.it/wp-content/uploads/2023/01/LG-392_Fratture-da-Fragilit%C3%A0_v3.pdf. Accessed 3 May 2022 Italian National Institute of Health. Platform for the Italian Guidelines SNLG Sistema Nazionale per le Linee Guida. https://www.iss.it/en/lineeguida-snlg. Accessed 3 May 2022 Schünemann HJ, Wiercioch W, Brozek J, Etxeandia-Ikobaltzeta I, Mustafa RA, Manja V et al (2017) GRADE evidence to decision (EtD) frameworks for adoption, adaptation, and de novo development of trustworthy recommendations: GRADE-ADOLOPMENT. J Clin Epidemiol 81:101–110 Centro Nazionale per l’Eccellenza Clinica, la Qualità e la Sicurezza delle Cure (2019) Manuale metodologico per la produzione di linee guida di pratica clinica. Italian National Institute of Health. https://snlg.iss.it/wp-content/uploads/2021/08/MM_v1.3.2_apr_2019.pdf. Accessed 3 May 2022 Programma Nazionale per le Linee guida (2019) Come produrre, diffondere e aggiornare raccomandazioni per la pratica clinica. Manuale metodologico. Italian National Institute of Health. http://www.snlg-iss.it/manuale_metodologico_SNLG. Accessed 3 May 2022 National Osteporosis Society (2008) Fracture Risk Assessment Tool (FRAX). World Health Organization collaborating center of the University of Sheffield, UK. http://www.shef.ac.uk/FRAX. Accessed 3 May 2022 Italian Society for Osteoporosis, Mineral Metabolism, and Bone Diseases (SIOMMMS) and the Italian Society of Rheumatology (SIR) (2010). DeFRA - l’algoritmo per la stima del rischio di frattura. https://defra-osteoporosi.it/. Accessed 3 May 2022 Italian Society of General Practitioners (SIMG) (2016) FRAHS: Il nuovo Score per la valutazione del rischio di frattura osteoporotica. https://www.simg.it/sicilia/frahs-il-nuovo-score-per-la-valutazione-del-rischio-di-frattura-osteoporotica. Accessed 3 May 2022 Page MJ, Moher D (2017) Evaluations of the uptake and impact of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and extensions: a scoping review. Syst Rev 6:263 Whiting PF, Rutjes AWS, Westwood ME, Mallett S, Deeks JJ, Reitsma JB et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536 Balshem H, Helfand M, Schünemann HJ, Oxman AD, Kunz R, Brozek J et al (2011) GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol 64:401–406 Bolland MJ, Siu AT, Mason BH, Horne AM, Ames RW, Grey AB et al (2011) Evaluation of the FRAX and Garvan fracture risk calculators in older women. J Bone Miner Res 26:420–427 Briot K, Paternotte S, Kolta S, Eastell R, Felsenberg D, Reid DM et al (2013) FRAX®: prediction of major osteoporotic fractures in women from the general population: the OPUS study. PLoS One 8:e83436 Chandran M, McCloskey EV, Thu WPP, Logan S, Hao Y, Tay D et al (2018) FRAX® based intervention thresholds for management of osteoporosis in Singaporean women. Arch Osteoporos 13:130 Cherian KE, Kapoor N, Shetty S, Naik D, Thomas N, Paul TV (2018) Evaluation of different screening tools for predicting femoral neck osteoporosis in rural south Indian postmenopausal women. J Clin Densitom 21:119–124 Cheung E, Cheung CL, Kung AWC, Tan KCB (2014) Possible FRAX-based intervention thresholds for a cohort of Chinese postmenopausal women. Osteoporos Int 25:1017–1023 Tebé Cordomí C, Del Río LM, Di Gregorio S, Casas L, Estrada MD, Kotzeva A et al (2013) Validation of the FRAX predictive model for major osteoporotic fracture in a historical cohort of Spanish women. J Clin Densitom 16:231–237 Crandall CJ, Larson J, Gourlay ML, Donaldson MG, LaCroix A, Cauley JA et al (2014) Osteoporosis screening in postmenopausal women 50 to 64 years old: comparison of US preventive services task force strategy and two traditional strategies in the women’s health initiative. J Bone Miner Res 29:1661–1666 Czerwiński E, Borowy P, Kumorek A, Amarowicz J, Górkiewicz M, Milert A (2013) Fracture risk prediction in outpatients from Krakow Region using FRAX tool versus fracture risk in 11-year follow-up. Ortop Traumatol Rehabil 15:617–628 El Maghraoui A, Sadni S, Jbili N, Rezqi A, Mounach A, Ghozlani I (2014) The discriminative ability of FRAX, the WHO algorithm, to identify women with prevalent asymptomatic vertebral fractures: a cross-sectional study. BMC Musculoskelet Disord 15:365 Ensrud KE, Lui LY, Taylor BC, Schousboe JT, Donaldson MG, Fink HA et al (2009) A comparison of prediction models for fractures in older women: is more better? Arch Intern Med 169:2087–2094 González-Macías J, Marin F, Vila J, Díez-Pérez A (2012) Probability of fractures predicted by FRAX® and observed incidence in the Spanish ECOSAP Study cohort. Bone 50:373–377 Henry MJ, Pasco JA, Merriman EN, Zhang Y, Sanders KM, Kotowicz MA et al (2011) Fracture risk score and absolute risk of fracture. Radiology 259:495–501 Indhavivadhana S, Rattanachaiyanont M, Angsuwathana S, Techatraisak K, Tanmahasamut P, Leerasiri P (2016) Validation of osteoporosis risk assessment tools in middle-aged Thai women. Climacteric 19:588–593 Kharroubi A, Saba E, Ghannam I, Darwish H (2017) Evaluation of the validity of osteoporosis and fracture risk assessment tools (IOF One Minute Test, SCORE, and FRAX) in postmenopausal Palestinian women. Arch Osteoporos 12:6 Kral R, Osima M, Borgen TT, Vestgaard R, Richardsen E, Bjørnerem Å (2017) Increased cortical porosity and reduced cortical thickness of the proximal femur are associated with nonvertebral fracture independent of Fracture Risk Assessment Tool and Garvan estimates in postmenopausal women. PLoS One 12:e0185363 Liu S, Chen R, Ding N, Wang Q, Huang M, Liu H et al (2021) Setting the new FRAX reference threshold without bone mineral density in Chinese postmenopausal women. J Endocrinol Invest 44:347–352 Pluskiewicz W, Adamczyk P, Franek E, Leszczynski P, Sewerynek E, Wichrowska H et al (2010) Ten-year probability of osteoporotic fracture in 2012 Polish women assessed by FRAX and nomogram by Nguyen et al.-Conformity between methods and their clinical utility. Bone 46:1661–1667 Rubin KH, Abrahamsen B, Friis-Holmberg T, Hjelmborg JVB, Bech M, Hermann AP et al (2013) Comparison of different screening tools (FRAX®, OST, ORAI, OSIRIS, SCORE and age alone) to identify women with increased risk of fracture. A population-based prospective study. Bone 56:16–22 Sornay-Rendu E, Munoz F, Delmas PD, Chapurlat RD (2010) The FRAX tool in French women: how well does it describe the real incidence of fracture in the OFELY cohort? J Bone Miner Res 25:2101–2107 Tamaki J, Iki M, Kadowaki E, Sato Y, Kajita E, Kagamimori S et al (2011) Fracture risk prediction using FRAX®: a 10-year follow-up survey of the Japanese Population-Based Osteoporosis (JPOS) Cohort Study. Osteoporos Int 22:3037–3045 Trémollieres FA, Pouillès JM, Drewniak N, Laparra J, Ribot CA, Dargent-Molina P (2010) Fracture risk prediction using BMD and clinical risk factors in early postmenopausal women: sensitivity of the WHO FRAX tool. J Bone Miner Res 25:1002–1009 van Geel TACM, Eisman JA, Geusens PP, van den Bergh JPW, Center JR, Dinant GJ (2014) The utility of absolute risk prediction using FRAX® and Garvan Fracture Risk Calculator in daily practice. Maturitas 77:174–179 Villa P, Lassandro AP, Moruzzi MC, Amar ID, Vacca L, Di Nardo F et al (2016) A non-invasive prevention program model for the assessment of osteoporosis in the early postmenopausal period: a pilot study on FRAX(®) and QUS tools advantages. J Endocrinol Invest 39:191–198 Lin J, Yang Y, Fei Q, Zhang X, Ma Z, Wang Q et al (2016) Validation of three tools for identifying painful new osteoporotic vertebral fractures in older Chinese men: bone mineral density, Osteoporosis Self-Assessment Tool for Asians, and fracture risk assessment tool. Clin Interv Aging 11:461–469 Pluskiewicz W, Adamczyk P, Franek E, Sewerynek E, Leszczynski P, Wichrowska H et al (2014) FRAX calculator and Garvan nomogram in male osteoporotic population. Aging Male 17:174–182 Zhang X, Lin J, Yang Y, Wu H, Li Y, Yang X et al (2018) Comparison of three tools for predicting primary osteoporosis in an elderly male population in Beijing: a cross-sectional study. Clin Interv Aging 13:201–209 Fraser LA, Langsetmo L, Berger C, Ioannidis G, Goltzman D, Adachi JD et al (2011) Fracture prediction and calibration of a Canadian FRAX® tool: a population-based report from CaMos. Osteoporos Int 22:829–837 Friis-Holmberg T, Rubin KH, Brixen K, Tolstrup JS, Bech M (2014) Fracture risk prediction using phalangeal bone mineral density or FRAX(®)?-A Danish cohort study on men and women. J Clin Densitom 17:7–15 Goldshtein I, Gerber Y, Ish-Shalom S, Leshno M (2018) Fracture risk assessment with FRAX Using real-world data in a population-based cohort from Israel. Am J Epidemiol 187:94–102 Hoff M, Meyer HE, Skurtveit S, Langhammer A, Søgaard AJ, Syversen U et al (2017) Validation of FRAX and the impact of self-reported falls among elderly in a general population: the HUNT study, Norway. Osteoporos Int 28:2935–2944 Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA et al (2010) Independent clinical validation of a Canadian FRAX tool: fracture prediction and model calibration. J Bone Miner Res 25:2350–2358 Marques A, Lucas R, Simões E, Verstappen SMM, Jacobs JWG, da Silva JAP (2017) Do we need bone mineral density to estimate osteoporotic fracture risk? A 10-year prospective multicentre validation study. RMD Open 3:e000509 Sandhu SK, Nguyen ND, Center JR, Pocock NA, Eisman JA, Nguyen TV (2010) Prognosis of fracture: evaluation of predictive accuracy of the FRAX algorithm and Garvan nomogram. Osteoporos Int 21:863–871 Su Y, Leung J, Hans D, Lamy O, Kwok T (2017) The added value of trabecular bone score to FRAX® to predict major osteoporotic fractures for clinical use in Chinese older people: the Mr. OS and Ms. OS cohort study in Hong Kong. Osteoporos Int 28:111–117 Yu R, Leung J, Woo J (2014) Sarcopenia combined with FRAX probabilities improves fracture risk prediction in older Chinese men. J Am Med Dir Assoc 15:918–923 Hippisley-Cox J, Coupland C (2009) Predicting risk of osteoporotic fracture in men and women in England and Wales: prospective derivation and validation of QFractureScores. BMJ 339:b4229 Tanaka S, Yoshimura N, Kuroda T, Hosoi T, Saito M, Shiraki M (2010) The fracture and immobilization score (FRISC) for risk assessment of osteoporotic fracture and immobilization in postmenopausal women–a joint analysis of the Nagano, Miyama, and Taiji Cohorts. Bone 47:1064–1070 Sambrook PN, Flahive J, Hooven FH, Boonen S, Chapurlat R, Lindsay R et al (2011) Predicting fractures in an international cohort using risk factor algorithms without BMD. J Bone Miner Res 26:2770–2777 Cummins NM, Poku EK, Towler MR, O’Driscoll OM, Ralston SH (2011) clinical risk factors for osteoporosis in Ireland and the UK: a comparison of FRAX and QFractureScores. Calcif Tissue Int 89:172–177 Dagan N, Cohen-Stavi C, Leventer-Roberts M, Balicer RD (2017) External validation and comparison of three prediction tools for risk of osteoporotic fractures using data from population based electronic health records: retrospective cohort study. BMJ 356:i6755 Bonaccorsi G, Messina C, Cervellati C, Maietti E, Medini M, Rossini M et al (2018) Fracture risk assessment in postmenopausal women with diabetes: comparison between DeFRA and FRAX tools. Gynecol Endocrinol 34:404–408 Marques A, Ferreira RJO, Santos E, Loza E, Carmona L, da Silva JAP (2015) The accuracy of osteoporotic fracture risk prediction tools: a systematic review and meta-analysis. Ann Rheum Dis 74:1958–1967