{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T07:27:09Z","timestamp":1781854029418,"version":"3.54.5"},"reference-count":15,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmacoepidemiology and Drug"],"published-print":{"date-parts":[[2022,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Adverse drug reaction (ADR) reports in pharmacovigilance databases often contain coded information and large amounts of unstructured or semi\u2010structured information in plain text format. The unstructured format and sheer volume of these data often render them neglected. Structural topic modelling (STM) represents a potentially insightful way of harnessing these valuable data and to detect grouping or themes in spontaneous reports to aid signal detection.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>This was an explorative study of the potential for structural topic modelling to identify useful patterns in ADR reports involving opioid drugs in a pharmacovigilance database.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A dataset of ADR reports on opioid drugs reported to the Netherlands Pharmacovigilance Centre Lareb from 1991 to December 2020 was used, comprising a total of 3069 unique reports. Qualitative text analysis was combined with STM, an automated text analysis method, to examine these data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In reports submitted directly by patients and healthcare professionals, 11 meaningful topics were identified, whereby patient experience reports, particularly in relation to pain (relief), and the timing of intake and ADRs of tramadol and paracetamol, were the most common. Of the 12 topics identified in reports received via marketing authorization holders, patch and skin\u2010related side effects, addiction and constipation were the most prevalent.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The STM\u2010based analysis identified information that cannot always be captured by coding with the Medical Dictionary for Regulatory Activities (MedDRA\u00ae). The identified topics reflect findings in the literature on opioids.<\/jats:p><\/jats:sec>","DOI":"10.1002\/pds.5502","type":"journal-article","created":{"date-parts":[[2022,6,25]],"date-time":"2022-06-25T13:18:51Z","timestamp":1656163131000},"page":"1003-1006","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Using structural topic modelling to reveal patterns in reports on opioid drugs in a pharmacovigilance database"],"prefix":"10.1002","volume":"31","author":[{"given":"Lea","family":"L\u00f6sch","sequence":"first","affiliation":[{"name":"Athena Institute Vrije Universiteit Amsterdam  The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Brown","sequence":"additional","affiliation":[{"name":"AISSR University of Amsterdam  Amsterdam The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8965-3224","authenticated-orcid":false,"given":"Florence","family":"van Hunsel","sequence":"additional","affiliation":[{"name":"Netherlands Pharmacovigilance Centre Lareb  's\u2010Hertogenbosch The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,7,6]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/14740338.2016.1177509"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40264-018-0653-3"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2019.00046"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2009.05.019"},{"key":"e_1_2_8_6_1","unstructured":"The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human USE. 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Accessed 1 June 2017.https:\/\/www.whocc.no\/atc\/structure_and_principles\/"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.poetic.2013.08.004"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2133806.2133826"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1080\/14740338.2018.1458838"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2018.00541"},{"key":"e_1_2_8_16_1","doi-asserted-by":"crossref","unstructured":"EickhoffM WienekeR (Eds)Understanding topic models in context: A mixed\u2010methods approach to the meaningful analysis of large document collectionsAIS eLibrary;2018.","DOI":"10.24251\/HICSS.2018.113"}],"container-title":["Pharmacoepidemiology and Drug Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/pds.5502","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/pds.5502","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/pds.5502","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T07:29:32Z","timestamp":1692775772000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/pds.5502"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,6]]},"references-count":15,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["10.1002\/pds.5502"],"URL":"https:\/\/doi.org\/10.1002\/pds.5502","archive":["Portico"],"relation":{},"ISSN":["1053-8569","1099-1557"],"issn-type":[{"value":"1053-8569","type":"print"},{"value":"1099-1557","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,6]]},"assertion":[{"value":"2021-12-28","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-06-17","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-07-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}