An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium
Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site...
Gespeichert in:
Veröffentlicht in: | Therapeutic innovation & regulatory science 2024-07, Vol.58 (4), p.591-599 |
---|---|
Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 599 |
---|---|
container_issue | 4 |
container_start_page | 591 |
container_title | Therapeutic innovation & regulatory science |
container_volume | 58 |
creator | Koneswarakantha, Björn Adyanthaya, Ronojit Emerson, Jennifer Collin, Frederik Keller, Annett Mattheus, Michaela Spyroglou, Ioannis Donevska, Sandra Ménard, Timothé |
description | Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials. |
doi_str_mv | 10.1007/s43441-024-00631-8 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11169048</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3031134537</sourcerecordid><originalsourceid>FETCH-LOGICAL-c426t-f17f5a1315d93cb04580e8dff6319b425526f1adf8646edc12d2ac7964a35d853</originalsourceid><addsrcrecordid>eNp9ks9u1DAQxiMEolXpC3BAI3FpDwE7dhyHC4qWAitt1VVpuVpex9m6JHZqJyvtg_F-OE1b_hzwxR7Nz9_M2F-SvMboHUaoeB8ooRSnKKMpQozglD9LDjPMeEo5os8fz0WJDpLjEG5RXCXPi4y_TA4IzxnFBT9MflYWLnpt029u9ErDJayl-iG3Ghrn4ZMetBqMs-AaqOqd9kHD2U7bIcC1rbVPL3Xv_GDsFoyFRWusUbKFK29kGz7Asutb3UVc3otIW8N32Zp6Djd7GG40LM_X1aqCk6UdtAflztfS7uFurFZm2ENlZbsfjAqnsHA2TMXG7lXyookF9PHDfpRcfz67WnxNVxdflotqlSqasSFtcNHkEhOc1yVRG0RzjjSvmya-V7mhWZ5nrMGybjijTNcKZ3UmVVEyKkle85wcJR9n3X7cdBGIk3jZit6bTvq9cNKIvzPW3Iit2wmMMSsR5VHh5EHBu7tRh0F0JijdttJqNwZBEMGY0JwUEX37D3ob_ySOP1GsoJhlbKKymVLeheB189QNRmJyhpidIaIzxL0zxNTFmz_neLry6IMIkBkIMWW32v-u_R_ZX-bqxUo</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3067416267</pqid></control><display><type>article</type><title>An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium</title><source>MEDLINE</source><source>SpringerNature Journals</source><creator>Koneswarakantha, Björn ; Adyanthaya, Ronojit ; Emerson, Jennifer ; Collin, Frederik ; Keller, Annett ; Mattheus, Michaela ; Spyroglou, Ioannis ; Donevska, Sandra ; Ménard, Timothé</creator><creatorcontrib>Koneswarakantha, Björn ; Adyanthaya, Ronojit ; Emerson, Jennifer ; Collin, Frederik ; Keller, Annett ; Mattheus, Michaela ; Spyroglou, Ioannis ; Donevska, Sandra ; Ménard, Timothé ; IMPALA (Inter coMPany quALity Analytics) Consortium ; On behalf of the IMPALA (Inter coMPany quALity Analytics) Consortium</creatorcontrib><description>Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.</description><identifier>ISSN: 2168-4790</identifier><identifier>ISSN: 2168-4804</identifier><identifier>EISSN: 2168-4804</identifier><identifier>DOI: 10.1007/s43441-024-00631-8</identifier><identifier>PMID: 38564178</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Adverse Drug Reaction Reporting Systems - standards ; Adverse events ; Analytical Report ; Clinical trials ; Clinical Trials as Topic ; Consortia ; Drug Safety and Pharmacovigilance ; Drug-Related Side Effects and Adverse Reactions ; Heuristic methods ; Humans ; Impalas ; Medicine ; Pharmacotherapy ; Pharmacy ; Software</subject><ispartof>Therapeutic innovation & regulatory science, 2024-07, Vol.58 (4), p.591-599</ispartof><rights>The Author(s) 2024</rights><rights>2024. The Author(s).</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c426t-f17f5a1315d93cb04580e8dff6319b425526f1adf8646edc12d2ac7964a35d853</cites><orcidid>0000-0003-4545-6944 ; 0000-0003-4585-7799</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s43441-024-00631-8$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s43441-024-00631-8$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38564178$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Koneswarakantha, Björn</creatorcontrib><creatorcontrib>Adyanthaya, Ronojit</creatorcontrib><creatorcontrib>Emerson, Jennifer</creatorcontrib><creatorcontrib>Collin, Frederik</creatorcontrib><creatorcontrib>Keller, Annett</creatorcontrib><creatorcontrib>Mattheus, Michaela</creatorcontrib><creatorcontrib>Spyroglou, Ioannis</creatorcontrib><creatorcontrib>Donevska, Sandra</creatorcontrib><creatorcontrib>Ménard, Timothé</creatorcontrib><creatorcontrib>IMPALA (Inter coMPany quALity Analytics) Consortium</creatorcontrib><creatorcontrib>On behalf of the IMPALA (Inter coMPany quALity Analytics) Consortium</creatorcontrib><title>An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium</title><title>Therapeutic innovation & regulatory science</title><addtitle>Ther Innov Regul Sci</addtitle><addtitle>Ther Innov Regul Sci</addtitle><description>Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.</description><subject>Adverse Drug Reaction Reporting Systems - standards</subject><subject>Adverse events</subject><subject>Analytical Report</subject><subject>Clinical trials</subject><subject>Clinical Trials as Topic</subject><subject>Consortia</subject><subject>Drug Safety and Pharmacovigilance</subject><subject>Drug-Related Side Effects and Adverse Reactions</subject><subject>Heuristic methods</subject><subject>Humans</subject><subject>Impalas</subject><subject>Medicine</subject><subject>Pharmacotherapy</subject><subject>Pharmacy</subject><subject>Software</subject><issn>2168-4790</issn><issn>2168-4804</issn><issn>2168-4804</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><recordid>eNp9ks9u1DAQxiMEolXpC3BAI3FpDwE7dhyHC4qWAitt1VVpuVpex9m6JHZqJyvtg_F-OE1b_hzwxR7Nz9_M2F-SvMboHUaoeB8ooRSnKKMpQozglD9LDjPMeEo5os8fz0WJDpLjEG5RXCXPi4y_TA4IzxnFBT9MflYWLnpt029u9ErDJayl-iG3Ghrn4ZMetBqMs-AaqOqd9kHD2U7bIcC1rbVPL3Xv_GDsFoyFRWusUbKFK29kGz7Asutb3UVc3otIW8N32Zp6Djd7GG40LM_X1aqCk6UdtAflztfS7uFurFZm2ENlZbsfjAqnsHA2TMXG7lXyookF9PHDfpRcfz67WnxNVxdflotqlSqasSFtcNHkEhOc1yVRG0RzjjSvmya-V7mhWZ5nrMGybjijTNcKZ3UmVVEyKkle85wcJR9n3X7cdBGIk3jZit6bTvq9cNKIvzPW3Iit2wmMMSsR5VHh5EHBu7tRh0F0JijdttJqNwZBEMGY0JwUEX37D3ob_ySOP1GsoJhlbKKymVLeheB189QNRmJyhpidIaIzxL0zxNTFmz_neLry6IMIkBkIMWW32v-u_R_ZX-bqxUo</recordid><startdate>20240701</startdate><enddate>20240701</enddate><creator>Koneswarakantha, Björn</creator><creator>Adyanthaya, Ronojit</creator><creator>Emerson, Jennifer</creator><creator>Collin, Frederik</creator><creator>Keller, Annett</creator><creator>Mattheus, Michaela</creator><creator>Spyroglou, Ioannis</creator><creator>Donevska, Sandra</creator><creator>Ménard, Timothé</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U7</scope><scope>C1K</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4545-6944</orcidid><orcidid>https://orcid.org/0000-0003-4585-7799</orcidid></search><sort><creationdate>20240701</creationdate><title>An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium</title><author>Koneswarakantha, Björn ; Adyanthaya, Ronojit ; Emerson, Jennifer ; Collin, Frederik ; Keller, Annett ; Mattheus, Michaela ; Spyroglou, Ioannis ; Donevska, Sandra ; Ménard, Timothé</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c426t-f17f5a1315d93cb04580e8dff6319b425526f1adf8646edc12d2ac7964a35d853</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adverse Drug Reaction Reporting Systems - standards</topic><topic>Adverse events</topic><topic>Analytical Report</topic><topic>Clinical trials</topic><topic>Clinical Trials as Topic</topic><topic>Consortia</topic><topic>Drug Safety and Pharmacovigilance</topic><topic>Drug-Related Side Effects and Adverse Reactions</topic><topic>Heuristic methods</topic><topic>Humans</topic><topic>Impalas</topic><topic>Medicine</topic><topic>Pharmacotherapy</topic><topic>Pharmacy</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Koneswarakantha, Björn</creatorcontrib><creatorcontrib>Adyanthaya, Ronojit</creatorcontrib><creatorcontrib>Emerson, Jennifer</creatorcontrib><creatorcontrib>Collin, Frederik</creatorcontrib><creatorcontrib>Keller, Annett</creatorcontrib><creatorcontrib>Mattheus, Michaela</creatorcontrib><creatorcontrib>Spyroglou, Ioannis</creatorcontrib><creatorcontrib>Donevska, Sandra</creatorcontrib><creatorcontrib>Ménard, Timothé</creatorcontrib><creatorcontrib>IMPALA (Inter coMPany quALity Analytics) Consortium</creatorcontrib><creatorcontrib>On behalf of the IMPALA (Inter coMPany quALity Analytics) Consortium</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Therapeutic innovation & regulatory science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Koneswarakantha, Björn</au><au>Adyanthaya, Ronojit</au><au>Emerson, Jennifer</au><au>Collin, Frederik</au><au>Keller, Annett</au><au>Mattheus, Michaela</au><au>Spyroglou, Ioannis</au><au>Donevska, Sandra</au><au>Ménard, Timothé</au><aucorp>IMPALA (Inter coMPany quALity Analytics) Consortium</aucorp><aucorp>On behalf of the IMPALA (Inter coMPany quALity Analytics) Consortium</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium</atitle><jtitle>Therapeutic innovation & regulatory science</jtitle><stitle>Ther Innov Regul Sci</stitle><addtitle>Ther Innov Regul Sci</addtitle><date>2024-07-01</date><risdate>2024</risdate><volume>58</volume><issue>4</issue><spage>591</spage><epage>599</epage><pages>591-599</pages><issn>2168-4790</issn><issn>2168-4804</issn><eissn>2168-4804</eissn><abstract>Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>38564178</pmid><doi>10.1007/s43441-024-00631-8</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-4545-6944</orcidid><orcidid>https://orcid.org/0000-0003-4585-7799</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2168-4790 |
ispartof | Therapeutic innovation & regulatory science, 2024-07, Vol.58 (4), p.591-599 |
issn | 2168-4790 2168-4804 2168-4804 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11169048 |
source | MEDLINE; SpringerNature Journals |
subjects | Adverse Drug Reaction Reporting Systems - standards Adverse events Analytical Report Clinical trials Clinical Trials as Topic Consortia Drug Safety and Pharmacovigilance Drug-Related Side Effects and Adverse Reactions Heuristic methods Humans Impalas Medicine Pharmacotherapy Pharmacy Software |
title | An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T14%3A51%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Open-Source%20R%20Package%20for%20Detection%20of%20Adverse%20Events%20Under-Reporting%20in%20Clinical%20Trials:%20Implementation%20and%20Validation%20by%20the%20IMPALA%20(Inter%20coMPany%20quALity%20Analytics)%20Consortium&rft.jtitle=Therapeutic%20innovation%20&%20regulatory%20science&rft.au=Koneswarakantha,%20Bj%C3%B6rn&rft.aucorp=IMPALA%20(Inter%20coMPany%20quALity%20Analytics)%20Consortium&rft.date=2024-07-01&rft.volume=58&rft.issue=4&rft.spage=591&rft.epage=599&rft.pages=591-599&rft.issn=2168-4790&rft.eissn=2168-4804&rft_id=info:doi/10.1007/s43441-024-00631-8&rft_dat=%3Cproquest_pubme%3E3031134537%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3067416267&rft_id=info:pmid/38564178&rfr_iscdi=true |