{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T05:41:57Z","timestamp":1776058917176,"version":"3.50.1"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T00:00:00Z","timestamp":1776038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Using the FAERS database in conjunction with the WHO Vigibase, this study systematically evaluated the characteristics, high-risk drugs, and demographic factors associated with drug-induced osteoporosis, and analyzed the onset time patterns of adverse events for major implicated medications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Osteoporosis-related reports from FAERS between Q1\u20132014 and Q1\u20132025 were collected, and after deduplication, 55,895 cases were included. Disproportionality analyses (ROR, PRR, MGPS, BCPNN) and LASSO regression were applied to identify high-risk drugs. Multivariate regression was used to assess the independent effects of age, sex, and drug exposure. Onset time distribution analyses were conducted for the five drugs with the strongest signals, and external validation was performed using WHO Vigibase.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Reports of osteoporosis increased markedly after 2020, with females and individuals aged \u226560 years representing high-risk populations. Disproportionality analysis identified 18 associated drugs, with Tenofovir Disoproxil showing the highest number of reports and the strongest signal (ROR 367.06). LASSO regression further identified 17 strongly associated drugs, predominantly antineoplastic agents and immunosuppressants. Multivariate analysis indicated that age &amp;gt;60 years (OR\u00a0=\u00a03.7) and female sex (OR\u00a0=\u00a01.8) were significant risk factors, while Tenofovir Disoproxil (OR\u00a0=\u00a0210) and Adefovir (OR\u00a0=\u00a059) exhibited the strongest drug-related risk signals. Onset time analysis revealed distinct temporal patterns among the five drugs: Tenofovir Disoproxil and Medroxyprogesterone had the highest cumulative risk and the broadest time distribution, whereas Adefovir and Anastrozole were mainly associated with early-onset events. External validation in WHO Vigibase corroborated the high-risk signals of Tenofovir Disoproxil and Adefovir.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This comprehensive pharmacovigilance study identifies key medications associated with elevated osteoporosis risk and reveals marked differences in onset time patterns. These findings provide robust evidence to support targeted monitoring and inform individualized preventive strategies in clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1783284","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T04:43:52Z","timestamp":1776055432000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Real-world identification of high-risk medications for drug-induced osteoporosis: a multi-method pharmacovigilance study based on FAERS with WHO Vigibase validation"],"prefix":"10.3389","volume":"17","author":[{"given":"Wenbin","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Internal Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital","place":["Taiyuan, 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