{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T04:58:36Z","timestamp":1793422716230,"version":"4.5.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T00:00:00Z","timestamp":1761868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100024075","name":"Region of Southern Denmark","doi-asserted-by":"publisher","award":["22\/26197"],"award-info":[{"award-number":["22\/26197"]}],"id":[{"id":"10.13039\/501100024075","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Osteoporosis is a major health concern in older individuals. Efficient case-finding is essential for timely risk assessment and treatment for high-risk patients. To prevent fractures and reduce the risk of subsequent disability, approaches offering clinically sufficient sensitivity with acceptable specificity are warranted. Although pharmaceutical osteoporosis treatment is effective, it is often diagnosed at a late stage, for instance, following a fracture. The aim of this study was to extend the existing Fracture Risk Evaluation Model (FREM), which identifies individuals at risk of an imminent (1-yr) major osteoporotic fracture (MOF) based on administrative health data. This extension (FREMVer2) included data on morbidity and medications and evaluated age-specific risk cut-offs to enhance the risk assessment of MOF and hip fracture (HF) risk, respectively. We included the entire population of Denmark aged \u226545\u00a0yr at baseline (2022; N\u2009=\u20092\u2009493\u2009180), not previously diagnosed with osteoporosis or receiving osteoporosis treatment. The cohort was divided into 4 groups stratified by sex and age (&amp;lt;65\u00a0yr, \u226565\u00a0yr). Each of the 4 groups was randomly split into a 60% development, a 20% model validation, and a 20% cut-off validation cohort. All diagnoses from Danish hospitals and filled prescriptions from Danish pharmacies from 2007 to 2021 were used as possible predictors for MOF. These predictors correspond to information that in Denmark is automatically transferred to general practitioner\u2019s electronic health records; hence, prediction would be possible in general practice. Models were constructed by logistic regression with LASSO regularization, determining the preferred regularization hyper parameter by cross-validation and forcing categorical age to be included. Across subgroups, the models obtained poor to acceptable area under the curves (AUCs) of 0.656-0.714 for MOF, and acceptable AUCs of 0.728-0.764 for HFs. Additionally, the models achieved sensitivities of around 80% or higher in almost all subgroups. This performance, together with the available predictors, makes FREMver2 a feasible decision support system as a step toward an opportunistic screening program in health care settings with access to administrative data.<\/jats:p>","DOI":"10.1093\/jbmr\/zjaf156","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T12:38:54Z","timestamp":1761568734000},"page":"25-37","source":"Crossref","is-referenced-by-count":4,"title":["An enhanced Fracture Risk Evaluation Model (FREM) using national health data on morbidity and medications"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0858-4269","authenticated-orcid":false,"given":"S\u00f6ren","family":"M\u00f6ller","sequence":"first","affiliation":[{"name":"Research Unit OPEN, Department of Clinical Research, University of Southern Denmark , 5000 Odense ,","place":["Denmark"]},{"name":"Open Patient data Explorative Network (OPEN), Odense University Hospital , 5000 Odense ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marlene","family":"Rietz","sequence":"additional","affiliation":[{"name":"Research Unit OPEN, Department of Clinical Research, University of Southern Denmark , 5000 Odense ,","place":["Denmark"]},{"name":"Division of Clinical Physiology, Department of Laboratory Medicine, Karolinska Institutet , 17177 Stockholm ,","place":["Sweden"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frederik Lykke","family":"Petersen","sequence":"additional","affiliation":[{"name":"Open Patient data Explorative Network (OPEN), Odense University Hospital , 5000 Odense ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan Christian","family":"Br\u00f8nd","sequence":"additional","affiliation":[{"name":"Department of Sports Science and Clinical Biomechanics, Research Unit for Exercise Epidemiology, Centre of Research in Childhood Health, University of Southern Denmark , 5230 Odense ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael Kriegbaum","family":"Skj\u00f8dt","sequence":"additional","affiliation":[{"name":"Research Unit OPEN, Department of Clinical Research, University of Southern Denmark , 5000 Odense ,","place":["Denmark"]},{"name":"Department of Medicine, Herlev Hospital , 2730 Copenhagen ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jens","family":"S\u00f8ndergaard","sequence":"additional","affiliation":[{"name":"Research Unit of General Practice, Department of Public Health, University of Southern Denmark , 5230 Odense ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2730-6080","authenticated-orcid":false,"given":"Bo","family":"Abrahamsen","sequence":"additional","affiliation":[{"name":"Research Unit OPEN, Department of Clinical Research, University of Southern Denmark , 5000 Odense ,","place":["Denmark"]},{"name":"Department of Medicine 1, Holb\u00e6k Hospital , 4300 Holb\u00e6k ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5045-536X","authenticated-orcid":false,"given":"Katrine Hass","family":"Rubin","sequence":"additional","affiliation":[{"name":"Research Unit OPEN, Department of Clinical Research, University of Southern Denmark , 5000 Odense ,","place":["Denmark"]},{"name":"Open Patient data Explorative Network (OPEN), Odense University Hospital , 5000 Odense ,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,10,31]]},"reference":[{"issue":"10169","key":"2026010500012713900_ref2","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/S0140-6736(18)32112-3","article-title":"Osteoporosis","volume":"393","author":"Compston","year":"2019","journal-title":"Lancet."},{"issue":"1","key":"2026010500012713900_ref3","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1007\/s11657-013-0136-1","article-title":"Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA)","volume":"8","author":"Hernlund","year":"2013","journal-title":"Arch Osteoporos"},{"issue":"2","key":"2026010500012713900_ref4","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1007\/s00198-020-05557-z","article-title":"The osteoporosis treatment gap in patients at risk of fracture in European primary care: a multi-country cross-sectional observational study","volume":"32","author":"McCloskey","year":"2021","journal-title":"Osteoporos Int"},{"issue":"5","key":"2026010500012713900_ref5","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1007\/s00198-010-1348-5","article-title":"Prevalence of risk factors for fractures and use of DXA scanning in Danish women. A regional population-based study","volume":"22","author":"Rubin","year":"2011","journal-title":"Osteoporos Int"},{"issue":"5","key":"2026010500012713900_ref6","doi-asserted-by":"crossref","first-page":"1507","DOI":"10.1007\/s00198-016-3894-y","article-title":"Mind the (treatment) gap: a global perspective on current and future strategies for prevention of fragility fractures","volume":"28","author":"Harvey","year":"2017","journal-title":"Osteoporos Int"},{"issue":"9","key":"2026010500012713900_ref7","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1002\/jbmr.2301","article-title":"The osteoporosis treatment gap","volume":"29","author":"Kanis","year":"2014","journal-title":"J Bone Miner Res"},{"issue":"8","key":"2026010500012713900_ref8","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1016\/S2213-8587(24)00153-0","article-title":"The potential role for artificial intelligence in fracture risk 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