{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T10:14:13Z","timestamp":1774692853243,"version":"3.50.1"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T00:00:00Z","timestamp":1738886400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T00:00:00Z","timestamp":1738886400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003035","name":"Aase og Ejnar Danielsens Fond","doi-asserted-by":"publisher","award":["22-10-0403"],"award-info":[{"award-number":["22-10-0403"]}],"id":[{"id":"10.13039\/501100003035","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Odense University Hospital"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Arch Osteoporos"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>\n                      <jats:italic>Summary<\/jats:italic>\n                    <\/jats:title>\n                    <jats:p>Obtaining accurate self-reports on clinical risk factors, such as parental hip fracture or alcohol and tobacco use, limits the utility of conventional risk scores for fracture risk. We demonstrate that fracture-risk prediction based on administrative health data alone performs equally to prediction based on self-reported clinical risk factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Accurate assessment of fracture risk is crucial. Unlike established risk prediction tools that rely on patient recall, the Fracture Risk Evaluation Model (FREM) utilises register data to estimate the risk of major osteoporotic fracture (MOF). We investigated whether adding self-reported clinical risk factors for osteoporosis to the FREM algorithm improved the prediction of 1-year fracture risk by comparing three approaches: the FREM algorithm (FREM\n                      <jats:sup>orig<\/jats:sup>\n                      ), clinical risk factors (CRF\n                      <jats:sup>only<\/jats:sup>\n                      ), and FREM combined with clinical risk factors (FREM-CRF).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>Clinical risk factor information was obtained through questionnaires sent to women aged 65\u201380\u00a0years living in the Region of Southern Denmark in 2010, who participated in the Risk-stratified Osteoporosis Strategy Evaluation study. Register data was obtained through national health registers and linked to the survey data. Positive and negative predictive values and concordance statistics were calculated for the performance of each approach using logistic regression and Cox proportional hazards models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of the 18,605 women included, 280 sustained a MOF within 1\u00a0year. All three approaches performed similarly in 1-year fracture risk prediction for low- and high-risk individuals. However, the FREM\n                      <jats:sup>orig<\/jats:sup>\n                      and FREM-CRF approach slightly overestimated fracture risk for medium-risk individuals.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Adding self-reported clinical data to FREM did not increase precision in predicting 1-year MOF risk. The discrimination of FREM\n                      <jats:sup>orig<\/jats:sup>\n                      was similar to that of CRF\n                      <jats:sup>only<\/jats:sup>\n                      , suggesting it may be possible to estimate fracture risk with the same precision by using register data instead of self-reported risk information. Register-based prediction models may be applicable in individualised risk monitoring or large-scale osteoporosis screening programmes.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11657-024-01493-1","type":"journal-article","created":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T15:18:12Z","timestamp":1738941492000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Prediction of imminent osteoporotic fracture risk in Danish postmenopausal women\u2014can the addition of self-reported clinical risk factors improve the prediction of the register-based FREM algorithm?"],"prefix":"10.1007","volume":"20","author":[{"given":"Emilie Rosenfeldt","family":"Christensen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kasper Westphal","family":"Leth","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frederik Lykke","family":"Petersen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tanja Gram","family":"Petersen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S\u00f6ren","family":"M\u00f6ller","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Abrahamsen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katrine Hass","family":"Rubin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,7]]},"reference":[{"key":"1493_CR1","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1007\/s11657-020-00871-9","volume":"16","author":"JA Kanis","year":"2021","unstructured":"Kanis JA, Norton N, Harvey NC, Jacobson T, Johansson H, Lorentzon M, McCloskey EV, Willers C, Borgstr\u00f6m F (2021) SCOPE 2021: a new scorecard for osteoporosis in Europe. Arch Osteoporos 16:82","journal-title":"Arch Osteoporos"},{"key":"1493_CR2","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1186\/s12877-016-0332-0","volume":"16","author":"SM Dyer","year":"2016","unstructured":"Dyer SM, Crotty M, Fairhall N, Magaziner J, Beaupre LA, Cameron ID, Sherrington C (2016) A critical review of the long-term disability outcomes following hip fracture. BMC Geriatr 16:158","journal-title":"BMC Geriatr"},{"key":"1493_CR3","doi-asserted-by":"publisher","first-page":"1726","DOI":"10.1007\/s00198-006-0172-4","volume":"17","author":"O Johnell","year":"2006","unstructured":"Johnell O, Kanis JA (2006) An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int 17:1726\u20131733","journal-title":"Osteoporos Int"},{"key":"1493_CR4","doi-asserted-by":"publisher","first-page":"e003524","DOI":"10.1136\/rmdopen-2023-003524","volume":"9","author":"ER Christensen","year":"2023","unstructured":"Christensen ER, Clausen A, Petersen TG, Skj\u00f8dt MK, Abrahamsen B, M\u00f6ller S, Rubin KH (2023) Excess mortality following a first and subsequent osteoporotic fracture: a Danish nationwide register-based cohort study on the mediating effects of comorbidities. RMD Open 9:e003524","journal-title":"RMD Open"},{"key":"1493_CR5","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s00198-018-4704-5","volume":"30","author":"JA Kanis","year":"2019","unstructured":"Kanis JA, Cooper C, Rizzoli R, Reginster JY (2019) European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int 30:3\u201344","journal-title":"Osteoporos Int"},{"key":"1493_CR6","doi-asserted-by":"publisher","first-page":"1401","DOI":"10.1007\/s00198-010-1348-5","volume":"22","author":"KH Rubin","year":"2011","unstructured":"Rubin KH, Abrahamsen B, Hermann AP, Bech M, Gram J, Brixen K (2011) Prevalence of risk factors for fractures and use of DXA scanning in Danish women A regional population-based study. Osteoporos Int 22:1401\u20131409","journal-title":"Osteoporos Int"},{"key":"1493_CR7","doi-asserted-by":"publisher","first-page":"1507","DOI":"10.1007\/s00198-016-3894-y","volume":"28","author":"NC Harvey","year":"2017","unstructured":"Harvey NC, McCloskey EV, Mitchell PJ, Dawson-Hughes B, Pierroz DD, Reginster JY, Rizzoli R, Cooper C, Kanis JA (2017) Mind the (treatment) gap: a global perspective on current and future strategies for prevention of fragility fractures. Osteoporos Int 28:1507\u20131529","journal-title":"Osteoporos Int"},{"key":"1493_CR8","doi-asserted-by":"publisher","unstructured":"Wells GA, Cranney A, Peterson J, Boucher M, Shea B, Robinson V, Coyle D, Tugwell P (2008) Alendronate for the primary and secondary prevention of osteoporotic fractures in postmenopausal women. Cochrane Database Syst Rev\u00a023(1):Cd001155. https:\/\/doi.org\/10.1002\/14651858.CD001155.pub2","DOI":"10.1002\/14651858.CD001155.pub2"},{"key":"1493_CR9","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":"1493_CR10","doi-asserted-by":"publisher","first-page":"1759720x2210835","DOI":"10.1177\/1759720X221083523","volume":"14","author":"A Gupta","year":"2022","unstructured":"Gupta A, Maslen C, Vindlacheruvu M et al (2022) Digital health interventions for osteoporosis and post-fragility fracture care. Ther Adv Musculoskelet Dis 14:1759720x221083523","journal-title":"Ther Adv Musculoskelet Dis"},{"key":"1493_CR11","doi-asserted-by":"publisher","first-page":"e0223526","DOI":"10.1371\/journal.pone.0223526","volume":"14","author":"S Spitzer","year":"2019","unstructured":"Spitzer S, Weber D (2019) Reporting biases in self-assessed physical and cognitive health status of older Europeans. PLoS One 14:e0223526","journal-title":"PLoS One"},{"key":"1493_CR12","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s11657-020-00739-y","volume":"15","author":"F Baleanu","year":"2020","unstructured":"Baleanu F, Moreau M, Kinnard V, Iconaru L, Karmali R, Rozenberg S, Rubinstein M, Paesmans M, Bergmann P, Body JJ (2020) Underevaluation of fractures by self-report: an analysis from the FRISBEE cohort. Arch Osteoporos 15:61","journal-title":"Arch Osteoporos"},{"key":"1493_CR13","doi-asserted-by":"publisher","first-page":"1967","DOI":"10.1002\/jbmr.3528","volume":"33","author":"KH Rubin","year":"2018","unstructured":"Rubin KH, M\u00f6ller S, Holmberg T, Bliddal M, S\u00f8ndergaard J, Abrahamsen B (2018) A new fracture risk assessment tool (FREM) based on public health registries. J Bone Miner Res 33:1967\u20131979","journal-title":"J Bone Miner Res"},{"key":"1493_CR14","doi-asserted-by":"publisher","first-page":"115934","DOI":"10.1016\/j.bone.2021.115934","volume":"147","author":"MK Skj\u00f8dt","year":"2021","unstructured":"Skj\u00f8dt MK, M\u00f6ller S, Hyldig N, Clausen A, Bliddal M, S\u00f8ndergaard J, Abrahamsen B, Rubin KH (2021) Validation of the fracture risk evaluation model (FREM) in predicting major osteoporotic fractures and hip fractures using administrative health data. Bone 147:115934","journal-title":"Bone"},{"key":"1493_CR15","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/s00198-021-06165-1","volume":"33","author":"S M\u00f6ller","year":"2022","unstructured":"M\u00f6ller S, Skj\u00f8dt MK, Yan L et al (2022) Prediction of imminent fracture risk in Canadian women and men aged 45 years or older: external validation of the Fracture Risk Evaluation Model (FREM). Osteoporos Int 33:57\u201366","journal-title":"Osteoporos Int"},{"key":"1493_CR16","unstructured":"Dansk Knoglemedicinsk Selskab Vejledning til udredning og behandling af Osteoporose. https:\/\/www.danskknogleselskab.dk\/behandlingsvejledning-nbv\/osteoporose\/"},{"key":"1493_CR17","doi-asserted-by":"publisher","first-page":"2029","DOI":"10.2147\/TCRM.S138000","volume":"14","author":"F Pouresmaeili","year":"2018","unstructured":"Pouresmaeili F, Kamalidehghan B, Kamarehei M, Goh YM (2018) A comprehensive overview on osteoporosis and its risk factors. Ther Clin Risk Manag 14:2029\u20132049","journal-title":"Ther Clin Risk Manag"},{"key":"1493_CR18","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1007\/s00223-014-9950-8","volume":"96","author":"KH Rubin","year":"2015","unstructured":"Rubin KH, Holmberg T, Rothmann MJ et al (2015) The risk-stratified osteoporosis strategy evaluation study (ROSE): a randomized prospective population-based study. Design and baseline characteristics. Calcif Tissue Int 96:167\u2013179","journal-title":"Calcif Tissue Int"},{"key":"1493_CR19","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1177\/1403494810387965","volume":"39","author":"CB Pedersen","year":"2011","unstructured":"Pedersen CB (2011) The Danish civil registration system. Scand J Public Health 39:22\u201325","journal-title":"Scand J Public Health"},{"key":"1493_CR20","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1007\/s00198-017-4326-3","volume":"29","author":"KH Rubin","year":"2018","unstructured":"Rubin KH, Rothmann MJ, Holmberg T et al (2018) Effectiveness of a two-step population-based osteoporosis screening program using FRAX: the randomized Risk-stratified Osteoporosis Strategy Evaluation (ROSE) study. Osteoporos Int 29:567\u2013578","journal-title":"Osteoporos Int"},{"key":"1493_CR21","doi-asserted-by":"publisher","first-page":"563","DOI":"10.2147\/CLEP.S179083","volume":"11","author":"M Schmidt","year":"2019","unstructured":"Schmidt M, Schmidt SAJ, Adelborg K, Sundb\u00f8ll J, Laugesen K, Ehrenstein V, S\u00f8rensen HT (2019) The Danish health care system and epidemiological research: from health care contacts to database records. Clin Epidemiol 11:563\u2013591","journal-title":"Clin Epidemiol"},{"key":"1493_CR22","doi-asserted-by":"publisher","first-page":"449","DOI":"10.2147\/CLEP.S91125","volume":"7","author":"M Schmidt","year":"2015","unstructured":"Schmidt M, Schmidt SA, Sandegaard JL, Ehrenstein V, Pedersen L, S\u00f8rensen HT (2015) The Danish National Patient Registry: a review of content, data quality, and research potential. Clin Epidemiol 7:449\u2013490","journal-title":"Clin Epidemiol"},{"key":"1493_CR23","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1177\/1403494811401482","volume":"39","author":"E Lynge","year":"2011","unstructured":"Lynge E, Sandegaard JL, Rebolj M (2011) The Danish National Patient Register. Scand J Public Health 39:30\u201333","journal-title":"Scand J Public Health"},{"key":"1493_CR24","doi-asserted-by":"publisher","first-page":"1130","DOI":"10.1097\/01.mlr.0000182534.19832.83","volume":"43","author":"H Quan","year":"2005","unstructured":"Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA (2005) Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 43:1130\u20131139","journal-title":"Med Care"},{"key":"1493_CR25","doi-asserted-by":"publisher","first-page":"257","DOI":"10.2147\/CLEP.S444447","volume":"16","author":"A Clausen","year":"2024","unstructured":"Clausen A, M\u00f6ller S, Skj\u00f8dt MK, Lynggaard RB, Vinholt PJ, Lindberg-Larsen M, S\u00f8ndergaard J, Abrahamsen B, Rubin KH (2024) Validity of major osteoporotic fracture diagnoses in the Danish National Patient Registry. Clin Epidemiol 16:257\u2013266","journal-title":"Clin Epidemiol"},{"key":"1493_CR26","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1177\/1536867X1001000303","volume":"10","author":"RB Newson","year":"2010","unstructured":"Newson RB (2010) Comparing the predictive powers of survival models using Harrell\u2019s C or Somers\u2019 D. The Stata J: Promoting communications on statistics and Stata 10:339\u2013358","journal-title":"The Stata J: Promoting communications on statistics and Stata"},{"key":"1493_CR27","unstructured":"StataCorp (2023) Stata statistical software: release 18 College Station, TX: StataCorp LLC.\u00a0https:\/\/www.stata.com\/support\/faqs\/resources\/citing-software-documentation-faqs\/"},{"key":"1493_CR28","doi-asserted-by":"publisher","first-page":"3389","DOI":"10.1007\/s00198-017-4205-y","volume":"28","author":"MJ Rothmann","year":"2017","unstructured":"Rothmann MJ, M\u00f6ller S, Holmberg T et al (2017) Non-participation in systematic screening for osteoporosis-the ROSE trial. Osteoporos Int 28:3389\u20133399","journal-title":"Osteoporos Int"},{"key":"1493_CR29","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.bone.2018.02.002","volume":"110","author":"KC Reber","year":"2018","unstructured":"Reber KC, K\u00f6nig HH, Becker C, Rapp K, B\u00fcchele G, M\u00e4chler S, Lindlbauer I (2018) Development of a risk assessment tool for osteoporotic fracture prevention: a claims data approach. Bone 110:170\u2013176","journal-title":"Bone"},{"key":"1493_CR30","doi-asserted-by":"publisher","first-page":"2329","DOI":"10.1002\/jbmr.4438","volume":"36","author":"C Beaudoin","year":"2021","unstructured":"Beaudoin C, Jean S, Moore L, Gamache P, Bessette L, Ste-Marie LG, Brown JP (2021) Prediction of osteoporotic fractures in elderly individuals: a derivation and internal validation study using healthcare administrative data. J Bone Miner Res 36:2329\u20132342","journal-title":"J Bone Miner Res"},{"key":"1493_CR31","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1007\/s00198-018-4780-6","volume":"30","author":"S Yang","year":"2019","unstructured":"Yang S, Leslie WD, Morin SN, Lix LM (2019) Administrative healthcare data applied to fracture risk assessment. Osteoporos Int 30:565\u2013571","journal-title":"Osteoporos Int"},{"issue":"4","key":"1493_CR32","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1007\/s40520-022-02100-4","volume":"34","author":"MK Javaid","year":"2022","unstructured":"Javaid MK, Kanis JA, Kaufman JM, Lamy O, Matijevic R, Perez AD, Radermecker RP, Rosa MM, Thomas T, Thomasius F, Vlaskovska M, Rizzoli R, Cooper C (2022) Management of patients at very high risk of osteoporotic fractures through sequential treatments. Aging Clin Exp Res 34(4):695\u2013714. https:\/\/doi.org\/10.1007\/s40520-022-02100-4","journal-title":"Aging Clin Exp Res"},{"key":"1493_CR33","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/s11657-022-01117-6","volume":"17","author":"P Chotiyarnwong","year":"2022","unstructured":"Chotiyarnwong P, McCloskey EV, Harvey NC et al (2022) Is it time to consider population screening for fracture risk in postmenopausal women? A position paper from the International Osteoporosis Foundation Epidemiology\/Quality of Life Working Group. Arch Osteoporos 17:87","journal-title":"Arch Osteoporos"},{"key":"1493_CR34","unstructured":"Solutions for Public Health (2019) Screening for osteoporosis in postmenopausal women. External review against programme appraisal criteria for the UK National Screening Committee. https:\/\/view-health-screening-recommendations.service.gov.uk\/osteoporosis\/"},{"key":"1493_CR35","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1007\/s00198-019-05226-w","volume":"31","author":"T Merlijn","year":"2020","unstructured":"Merlijn T, Swart KMA, van der Horst HE, Netelenbos JC, Elders PJM (2020) Fracture prevention by screening for high fracture risk: a systematic review and meta-analysis. Osteoporos Int 31:251\u2013257","journal-title":"Osteoporos Int"},{"key":"1493_CR36","doi-asserted-by":"publisher","first-page":"102584","DOI":"10.1016\/j.eclinm.2024.102584","volume":"71","author":"TG Petersen","year":"2024","unstructured":"Petersen TG, Abrahamsen B, H\u00f8iberg M et al (2024) Ten-year follow-up of fracture risk in a systematic population-based screening program: the risk-stratified osteoporosis strategy evaluation (ROSE) randomised trial. EClinicalMedicine 71:102584","journal-title":"EClinicalMedicine"},{"key":"1493_CR37","unstructured":"National Osteoporosis Guideline Group (2021) Clinical guideline for the prevention and treatment of osteoporosis. https:\/\/www.nogg.org.uk\/full-guideline. Accessed July 15th 2024"},{"key":"1493_CR38","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1186\/s12889-015-2056-z","volume":"15","author":"A Beauchamp","year":"2015","unstructured":"Beauchamp A, Buchbinder R, Dodson S, Batterham RW, Elsworth GR, McPhee C, Sparkes L, Hawkins M, Osborne RH (2015) Distribution of health literacy strengths and weaknesses across socio-demographic groups: a cross-sectional survey using the Health Literacy Questionnaire (HLQ). BMC Public Health 15:678","journal-title":"BMC Public Health"},{"key":"1493_CR39","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1007\/s00198-019-04952-5","volume":"30","author":"YH Roh","year":"2019","unstructured":"Roh YH, Lee ES, Ahn J, Kim HS, Gong HS, Baek KH, Chung HY (2019) Factors affecting willingness to get assessed and treated for osteoporosis. Osteoporos Int 30:1395\u20131401","journal-title":"Osteoporos Int"},{"key":"1493_CR40","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1177\/1403494811402412","volume":"39","author":"KH Rubin","year":"2011","unstructured":"Rubin KH, Abrahamsen B, Hermann AP, Bech M, Gram J, Brixen K (2011) Fracture risk assessed by fracture risk assessment tool (FRAX) compared with fracture risk derived from population fracture rates. Scand J Public Health 39:312\u2013318","journal-title":"Scand J Public Health"},{"key":"1493_CR41","unstructured":"Statistics Denmark (2024) Immigrants and their descendants [Internet]. Statistics Denmark. https:\/\/www.dst.dk\/en\/Statistik\/emner\/borgere\/befolkning\/indvandrere-og-efterkommere# Accessed June 25th 2024"},{"key":"1493_CR42","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1534\/genetics.116.189241","volume":"204","author":"G Athanasiadis","year":"2016","unstructured":"Athanasiadis G, Cheng JY, Vilhj\u00e1lmsson BJ et al (2016) Nationwide genomic study in Denmark reveals remarkable population homogeneity. Genetics 204:711\u2013722","journal-title":"Genetics"}],"container-title":["Archives of Osteoporosis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11657-024-01493-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11657-024-01493-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11657-024-01493-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T21:18:03Z","timestamp":1766524683000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11657-024-01493-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,7]]},"references-count":42,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1493"],"URL":"https:\/\/doi.org\/10.1007\/s11657-024-01493-1","relation":{},"ISSN":["1862-3514"],"issn-type":[{"value":"1862-3514","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,7]]},"assertion":[{"value":"23 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"For this type of study, formal consent is not required. For the ROSE study (from which parts of the dataset included in the current study originates), all procedures performed involving human participants were in accordance with the ethical standards of the institutional and\/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The authors refer to previous publications of the ROSE study for further information [\n                      \n                      ].","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"According to Danish law, it is not required to obtain informed consent for register-based studies. Informed consent was obtained from all individual participants included in the original ROSE study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"ERC, KWL, FLP, TGP, SM, and KHR declare no conflicts of interest. BA reports personal speaker fees from Amgen and UCB, personal speaker fees from Gedeon Richter, and institutional research grants and personal consulting or speaker fees from UCB, Novartis, Pharmacosmos, and Kyowa-Kirin.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}],"article-number":"21"}}