{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T14:31:39Z","timestamp":1790087499388,"version":"4.0.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T00:00:00Z","timestamp":1715817600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T00:00:00Z","timestamp":1715817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Arch Osteoporos"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Summary<\/jats:title>\n                <jats:p>In the longitudinal, retrospective study, the ability of the FRAX, Garvan, and POL-RISK algorithms to predict osteoporotic fractures was compared in a group of 457 women. Using the rigid threshold of 10% showed a significant discrepancy in sensitivity and specificity of all tools. New thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds allow for improving the diagnostic accuracy of all three calculators.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Introduction<\/jats:title>\n                <jats:p>The aim of the longitudinal, retrospective study was to compare three tools designed to assess fracture risk: FRAX, Garvan, and POL-RISK in their prediction of fracture incidence.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Material<\/jats:title>\n                <jats:p>The study group consisted of 457 postmenopausal women with a mean age of 64.21\u2009\u00b1\u20095.94\u00a0years from the Gliwice Osteoporosis (GO) Study. Comprehensive data on clinical factors related to fractures were collected for all participants. Bone densitometry was performed at the proximal femur using the Prodigy device (GE, USA). Fracture risk was established using the FRAX, Garvan, and POL-RISK algorithms. Data on the incidence of osteoporotic fractures were collected over the last 10\u00a0years.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>During the period of observation 72, osteoporotic fractures occurred in 63 subjects. For a preliminary comparison of the predictive value of analyzed diagnostic tools, the fracture risk threshold of 10% was used. For FRAX, the fracture probability exceeding 10% was observed only in 11 subjects who experienced fractures; thus, the fracture was properly predicted only in 22.9% of women. For Garvan, the respective value was 90.5%, and for POL-RISK, it was 98.4%. That gave a very low true positive value for FRAX and a very high false positive value for Garvan and POL-RISK. Based on ROC curves, new thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds improve the diagnostic accuracy of all compared fracture prediction tools.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>The current study showed that different fracture risk assessment tools, although having similar clinical purposes, require different cut-off thresholds for making therapeutic decisions. Better identification of patients requiring therapy based on such an approach may help reduce the number of new fractures.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11657-024-01392-5","type":"journal-article","created":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T22:01:30Z","timestamp":1715896890000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Fracture risk prediction in postmenopausal women from GO Study: the comparison between FRAX, Garvan, and POL-RISK algorithms"],"prefix":"10.1007","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1839-6560","authenticated-orcid":false,"given":"W.","family":"Pluskiewicz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6098-0088","authenticated-orcid":false,"given":"A.","family":"Werner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6239-7790","authenticated-orcid":false,"given":"M.","family":"Bach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9557-221X","authenticated-orcid":false,"given":"P.","family":"Adamczyk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2287-6842","authenticated-orcid":false,"given":"B.","family":"Drozdzowska","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,16]]},"reference":[{"key":"1392_CR1","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1359\/jbmr.2000.15.4.721","volume":"15","author":"CM Klotzbuecher","year":"2000","unstructured":"Klotzbuecher CM, Ross PD, Landsman PD, Abbot PA, Berger M (2000) Patients with prior fractures have increased risk of future fracture: a summary of the literature and statistical synthesis. J Bone Miner Res 15:721\u2013727","journal-title":"J Bone Miner Res"},{"key":"1392_CR2","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1007\/s00198-007-0543-5","volume":"19","author":"JA Kanis","year":"2008","unstructured":"Kanis JA, Johnell O, Oden A et al (2008) FRAX\u2122 and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19:385\u2013397","journal-title":"Osteoporos Int"},{"key":"1392_CR3","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1007\/s00198-007-0362-8","volume":"18","author":"ND Nguyen","year":"2007","unstructured":"Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2007) Development of a nomogram for individualizing hip fracture risk in men and women. Osteoporos Int 18:1109\u20131117","journal-title":"Osteoporos Int"},{"key":"1392_CR4","doi-asserted-by":"publisher","first-page":"1431","DOI":"10.1007\/s00198-008-0588-0","volume":"19","author":"ND Nguyen","year":"2008","unstructured":"Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2008) Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks. Osteoporos Int 19:1431\u20131434","journal-title":"Osteoporos Int"},{"issue":"2","key":"1392_CR5","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.jocd.2017.07.005","volume":"21","author":"P Adamczyk","year":"2018","unstructured":"Adamczyk P, Werner A, Bach M et al (2018) Risk factors for fractures identified in the algorithm developed in 5-year follow-up of postmenopausal women from RAC-OST-POL Study. J Clin Densitom 21(2):213\u2013219","journal-title":"J Clin Densitom"},{"key":"1392_CR6","doi-asserted-by":"publisher","unstructured":"Pluskiewicz W, Adamczyk P, Werner A, Bach M, Drozdzowska B. (2023) POL-RISK: an algorithm for 10-year fracture risk prediction in the postmenopausal women from the RAC-OST-POL Study. Pol Arch Intern Med\u00a0133:16395. https:\/\/doi.org\/10.20452\/pamw.16395","DOI":"10.20452\/pamw.16395"},{"key":"1392_CR7","doi-asserted-by":"publisher","first-page":"1767","DOI":"10.1002\/jbmr.371","volume":"26","author":"MG Donaldson","year":"2011","unstructured":"Donaldson MG, Cawthon PM, Schousboe JT et al (2011) Novel methods to evaluate risk models. J Bone Miner Res 26:1767\u20131773","journal-title":"J Bone Miner Res"},{"key":"1392_CR8","doi-asserted-by":"publisher","first-page":"1701","DOI":"10.1002\/jbmr.1956","volume":"28","author":"KH Rubin","year":"2013","unstructured":"Rubin KH, Friis-Holmberg T, Hermann AP, Abrahamsen B, Brixen K (2013) Risk assessment tools to identify women with increased risk of osteoporotic fracture: complexity or simplicity? A systematic review. J Bone Miner Res 28:1701\u20131717","journal-title":"J Bone Miner Res"},{"key":"1392_CR9","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1007\/s00198-019-04919-6","volume":"30","author":"C Beaudoin","year":"2019","unstructured":"Beaudoin C, Moore L, Gagne M et al (2019) Performance of predictive tools to identify individuals at risk of non-traumatic fracture: a systematic review, meta-analysis and meta-regression. Osteoporos Int 30:721\u2013740","journal-title":"Osteoporos Int"},{"issue":"20","key":"1392_CR10","doi-asserted-by":"publisher","first-page":"e3415","DOI":"10.1097\/MD.0000000000003415","volume":"95","author":"SY Chen","year":"2016","unstructured":"Chen SY, Chen YJ, Cheng CH, Hwang HF, Chen CY, Lin MR (2016) Comparison of different screening tools for identifying fracture\/osteoporosis risk among community-dwelling older people. Medicine 95(20):e3415","journal-title":"Medicine"},{"key":"1392_CR11","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1016\/j.jocd.2017.06.023","volume":"20","author":"TV Nguyen","year":"2017","unstructured":"Nguyen TV, Eisman JA (2017) Fracture risk assessment: from population to individual. J Clin Densitom 20:368\u2013378","journal-title":"J Clin Densitom"},{"key":"1392_CR12","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.afos.2018.03.001","volume":"4","author":"TV Nguyen","year":"2018","unstructured":"Nguyen TV (2018) Individualized fracture risk assessment: state-of-the-art and room for improvement. Osteoporosis and Sarcopenia 4:2\u201310","journal-title":"Osteoporosis and Sarcopenia"},{"key":"1392_CR13","doi-asserted-by":"publisher","first-page":"1661","DOI":"10.1016\/j.bone.2010.02.012","volume":"46","author":"W Pluskiewicz","year":"2010","unstructured":"Pluskiewicz W, Adamczyk P, Franek E, Leszczynski P, Sewerynk 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. \u2013 conformity between methods and their clinical utility. Bone 46:1661\u20137","journal-title":"Bone"},{"key":"1392_CR14","doi-asserted-by":"publisher","first-page":"174","DOI":"10.3109\/13685538.2013.875991","volume":"17","author":"W Pluskiewicz","year":"2014","unstructured":"Pluskiewicz W, Adamczyk P, Franek E et al (2014) FRAX calculator and Garvan nomogram in male osteoporotic population. Aging Male 17:174\u2013182","journal-title":"Aging Male"},{"key":"1392_CR15","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1002\/jbmr.215","volume":"26","author":"MJ Bolland","year":"2011","unstructured":"Bolland MJ, Siu AT, Manson BH et al (2011) Evaluation of the FRAX and Garvan fracture risk calculators in older women. J Bone Miner Res 26:420\u2013427","journal-title":"J Bone Miner Res"},{"key":"1392_CR16","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.maturitas.2013.10.021","volume":"77","author":"TACM van Geel","year":"2014","unstructured":"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\u2013179","journal-title":"Maturitas"},{"key":"1392_CR17","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.maturitas.2015.12.003","volume":"85","author":"EO Billington","year":"2016","unstructured":"Billington EO, Gamble GD, Reid IR (2016) Reasons for discrepancy in hip fracture risk estimates using FRAX and Garvan calculators. Maturitas 85:11\u201318","journal-title":"Maturitas"},{"key":"1392_CR18","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/s11606-018-4696-z","volume":"34","author":"CJ Crandall","year":"2018","unstructured":"Crandall CJ, Larson J, LaCroix A et al (2018) Predicting fracture risk in younger postmenopausal women: comparison of the Garvan and FRAX risk calculators in the women\u2019s Health Initiative Study. J Gen Intern Med 34:235\u2013242","journal-title":"J Gen Intern Med"},{"key":"1392_CR19","doi-asserted-by":"publisher","first-page":"2129","DOI":"10.1007\/s00198-019-05088-2","volume":"30","author":"KL Holloway-Kew","year":"2019","unstructured":"Holloway-Kew KL, Zhang Y, Betson AG et al (2019) How well do FRAX (Australia) and Garvan calculators predict incident fractures? Data from the Geelong Osteoporosis Study. Osteoporos Int 30:2129\u20132139","journal-title":"Osteoporos Int"},{"issue":"9","key":"1392_CR20","doi-asserted-by":"publisher","first-page":"e10532","DOI":"10.1002\/jbm4.10532","volume":"5","author":"F Baleanu","year":"2021","unstructured":"Baleanu F, Iconaru L, Charles A et al (2021) Indepedent external validation of FRAX and Garvan fracture risk calculators: a sub-study of the FRISBEE Cohort. JBMR Plus (WOA) 5(9):e10532","journal-title":"JBMR Plus (WOA)"},{"key":"1392_CR21","doi-asserted-by":"publisher","first-page":"i6755","DOI":"10.1136\/bmj.i6755","volume":"356","author":"N Dagan","year":"2017","unstructured":"Dagan N, Cohen-Stavi Ch, 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. https:\/\/doi.org\/10.1136\/bmj.i6755","journal-title":"BMJ"},{"key":"1392_CR22","doi-asserted-by":"publisher","first-page":"e060282","DOI":"10.1136\/bmjopen-2021-060282","volume":"12","author":"G Todorow","year":"2022","unstructured":"Todorow G, Brook S, Quah Qin Xian N, Von Widekind S, Freudenthal B, Comninos AN (2022) Comparison of fracture risk calculators in elderly fallers: a hospital-based cross-sectional study. BMJ Open 12:e060282. https:\/\/doi.org\/10.1136\/bmjopen-2021-060282","journal-title":"BMJ Open"},{"key":"1392_CR23","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1002\/jbmr.4432","volume":"37","author":"L Iconaru","year":"2022","unstructured":"Iconaru L, Charles A, Baleanu F et al (2022) Prediction model of an imminent fracture after an index fracture \u2013 models derived from the Frisbee Cohort. J Bone Miner Res 37:59\u201367","journal-title":"J Bone Miner Res"},{"key":"1392_CR24","doi-asserted-by":"publisher","first-page":"14009","DOI":"10.1111\/ijcp.14009","volume":"75","author":"W Pluskiewicz","year":"2021","unstructured":"Pluskiewicz W, Adamczyk P, Drozdzowska B (2021) The significance of height loss in postmenopausal women. The results from GO Study. Int J Clin Pract 75:14009. https:\/\/doi.org\/10.1111\/ijcp.14009","journal-title":"Int J Clin Pract"},{"key":"1392_CR25","doi-asserted-by":"publisher","first-page":"2043","DOI":"10.1007\/s00198-021-05941-3","volume":"32","author":"W Pluskiewicz","year":"2021","unstructured":"Pluskiewicz W, Adamczyk P, Drozdzowska B (2021) Height loss in postmenopausal women-do we need more for fracture risk assessment? Results from the GO Study. Osteoporos Int 32:2043\u20132049","journal-title":"Osteoporos Int"},{"key":"1392_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5603\/EP.2017.0062","volume":"68","author":"R Lorenc","year":"2017","unstructured":"Lorenc R, G\u0142uszko P, Franek E et al (2017) Recommendations for diagnostic and therapeutic management in osteoporosis in Poland\u2013 update [in Polish]. Endokrynol Pol 68:1\u201318","journal-title":"Endokrynol Pol"},{"key":"1392_CR27","unstructured":"Werner A, Bach M, Pluskiewicz W (2016) The study of preprocessing methods\u2019 utility in analysis of multidimensional and highly imbalanced medical data.\u00a0In: Rosta\u0144ski M, Pikiewicz P, Buchwald P, Maczka K (eds)\u00a0Proceedings of the 11th Scientific Conference IIIS,\u00a0Scientific publisher of WSB University in D\u0105browa G\u00f3rnicza"},{"issue":"1","key":"1392_CR28","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1007\/s11657-023-01346-3","volume":"18","author":"W Pluskiewicz","year":"2023","unstructured":"Pluskiewicz W, Werner A, Bach M, Adamczyk P, Drozdzowska B (2023) Optimal fracture prediction thresholds for therapy onset, established from FRAX and Garvan algorithms: a longitudinal observation of the population representative female cohort from the RAC-OST-POL Study. Arch Osteoporos 18(1):136","journal-title":"Arch Osteoporos"}],"container-title":["Archives of Osteoporosis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11657-024-01392-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11657-024-01392-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11657-024-01392-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T12:06:43Z","timestamp":1734350803000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11657-024-01392-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,16]]},"references-count":28,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["1392"],"URL":"https:\/\/doi.org\/10.1007\/s11657-024-01392-5","relation":{},"ISSN":["1862-3514"],"issn-type":[{"value":"1862-3514","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,16]]},"assertion":[{"value":"5 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"A.W. and M.B. participated in the calculations and in the statistical analyses and identified the appropriate indicators\/measures to compare the predictive powers of the compared fracture risk assessment tools, which could be described as the implementation of tasks in the Information and Communication Technology discipline, defined by the Polish Ministry of Education. W. Pluskiewicz, A. Werner, M. Bach, P. Adamczyk, and B. Drozdzowska declare that they have no conflict of interest related to this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}],"article-number":"39"}}