Drug Safety最新文献

{"title":"Evaluation of Data Quality and Utility of the Japan Drug Information Institute in Pregnancy (JDIIP) Consultation Case Database for Pregnancy Pharmacovigilance.","authors":"Shinichi Matsuda, Naho Yakuwa, Mikako Goto, Manabu Akazawa, Kunihiko Takahashi, Tatsuhiko Anzai, Sachi Koinuma, Izumi Fujioka, Yoriko Miura, Mihoko Ota, Hiroaki Oka, Naoki Nitani, Tomiko Tawaragi, Atsuko Murashima","doi":"10.1007/s40264-025-01554-5","DOIUrl":"https://doi.org/10.1007/s40264-025-01554-5","url":null,"abstract":"<p><strong>Introduction: </strong>Ensuring medication safety during pregnancy is crucial for protecting maternal and fetal health. However, fragmented data sources and the lack of comprehensive databases present substantial barriers to effective pharmacovigilance. The Japan Drug Information Institute in Pregnancy (JDIIP) database, which contains data on drug treatment counseling for pregnant women, is expected to help address the lack of comprehensive databases for pregnancy pharmacovigilance (PregPV).</p><p><strong>Objective: </strong>We evaluated the quality and utility of the JDIIP database for PregPV activities, particularly its ability to consolidate and utilize drug-exposure data among pregnant women in Japan.</p><p><strong>Methods: </strong>To assess the quality and utility of the JDIIP database for PregPV, we examined its alignment with 48 core data elements (CDEs) considered critical for PregPV, as recently proposed by a European Union consortium through the ConcePTION Project. We performed a detailed mapping of each CDE definition-including maternal lifestyle factors, drug exposure, and pregnancy outcomes-against the corresponding data elements captured in the JDIIP database.</p><p><strong>Results: </strong>The JDIIP database either directly collected or could derive 38 of the 48 specific items (79%) recommended by the ConcePTION Project. At the category level, the JDIIP database aligned closely with the CDE requirements for database management details, pregnancy details, maternal medical history, pregnancy medication exposure, live/stillborn birth outcomes, and malformation details, achieving coverage of over 80% of the necessary variables in each category. Some categories, such as maternal medical conditions arising during pregnancy and infant complications within the first year of life, showed less alignment, with coverage rates below 50%. Although the JDIIP database provides comprehensive coverage of critical pharmacovigilance elements, data collection for specific variables and categories that better align with the CDE framework can be enhanced to improve alignment with the CDE framework and strengthen pharmacovigilance capabilities.</p><p><strong>Conclusions: </strong>Our findings highlight the potential of the JDIIP database as a valuable resource for advancing PregPV research. Although the collection of certain maternal and infant data elements could be improved, the substantial alignment of the database with established CDEs positions it as a promising tool for advancing PregPV initiatives in Japan.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144076679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incretin-Based Drugs and the Incidence of Endometrial Cancer Among People with Type 2 Diabetes: Active Comparator New-User Design.","authors":"Sonny M Rothman, Hui Yin, Oriana H Y Yu, Michael Pollak, Laurent Azoulay","doi":"10.1007/s40264-025-01551-8","DOIUrl":"https://doi.org/10.1007/s40264-025-01551-8","url":null,"abstract":"<p><strong>Introduction: </strong>The use of incretin-based drugs may be associated with a decreased risk of endometrial cancer among women with type 2 diabetes.</p><p><strong>Methods: </strong>Using data from the UK Clinical Practice Research Datalink and linked databases, two new-user active comparator cohorts of women with type 2 diabetes who initiated glucagon-like peptide 1 receptor agonists (GLP-1 RAs) or sulfonylureas (cohort 1) and DPP-4 inhibitors or sulfonylureas (cohort 2) were assembled. Propensity score fine stratification weighted Cox proportional hazards models were fitted to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident endometrial cancer.</p><p><strong>Results: </strong>Cohort 1 included 9239 new users of GLP-1 RAs and 80,086 new users of sulfonylureas. The GLP-1 RAs were not associated with a decreased risk of endometrial cancer when compared with sulfonylureas (HR: 1.11, 95% CI: 0.66-1.88). In a duration-response secondary analysis, use of GLP-1 RAs for more than two years was associated with an increased risk of endometrial cancer (HR: 2.47, 95% CI: 1.37-4.43) when compared to sulfonylureas When analysed by drug type, exenatide was associated with an elevated risk when compared to sulfonylureas (HR: 2.26, 95% CI:1.06-4.82). Cohort 2 included 42,486 new users of DPP-4 inhibitors and 79,353 new users of sulfonylureas. DPP-4 inhibitors were not associated with a decreased risk of endometrial cancer compared with sulfonylureas (HR: 1.00, 95% CI: 0.76-1.32). In a duration-response secondary analysis, use of DPP-4 inhibitors for more than two years was associated with an increased risk of endometrial cancer (HR: 1.63, 95% CI: 1.14-2.33) when compared to sulfonylureas.</p><p><strong>Conclusions: </strong>In this population-based study, the use of GLP-1 RAs and DPP-4 inhibitors was not associated with a decreased risk of endometrial cancer when compared with the use of sulfonylureas among women with type 2 diabetes.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143985755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drug Induced Liver Injury: Highlights and Controversies in the 2023 Literature.","authors":"Harjit Singh, Bryce F Kunkle, Angela R Troia, Advait M Suvarnakar, Ade C Waterman, Yadana Khin, Serena Y Korkmaz, Corinne E O'Connor, James H Lewis","doi":"10.1007/s40264-025-01514-z","DOIUrl":"10.1007/s40264-025-01514-z","url":null,"abstract":"<p><p>Drug-induced liver injury (DILI) remains an active field of clinical research and investigation with more than 4700 publications appearing in 2023 relating to hepatotoxicity of all causes and injury patterns. As in years past, we have attempted to identify and summarize highlights and controversies from the past year's literature. Several new and novel therapeutic agents were approved by the US Food and Drug Administration (FDA) in 2023, a number of which were associated with significant hepatotoxicity. Updates in the diagnosis and management of DILI using causality scores as well as newer artificial intelligence-based methods were published. Details of newly established hepatotoxins as well as updated information on previously documented hepatotoxic drugs is presented. Significant updates in treatment of DILI were also included as well as reports related to global DILI registries.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"455-488"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143373832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opinion Mining of Erowid's Experience Reports on LSD and Psilocybin-Containing Mushrooms.","authors":"Ahmed Al-Imam, Riccardo Lora, Marek A Motyka, Erica Marletta, Michele Vezzaro, Jerzy Moczko, Manal Younus, Michal Michalak","doi":"10.1007/s40264-025-01530-z","DOIUrl":"10.1007/s40264-025-01530-z","url":null,"abstract":"<p><strong>Background: </strong>Psychedelics are gaining attention for their therapeutic potential in modern and personalized medicine. Online forums such as Erowid provide valuable user insights, but analyses of these experiences using natural language processing (NLP) remain scarce.</p><p><strong>Objective: </strong>This study aims to utilize NLP, including sentiment and lexicon analysis, to examine user-generated experience reports on psilocybin-containing mushrooms and LSD from the Erowid forum.</p><p><strong>Methods: </strong>Data from 2188 Erowid users (1161 psilocybin mushrooms and 1027 LSD) was collected via automated web scraping with XPath, CSS selectors, and Selenium WebDriver. The dataset included report titles, substances, and demographics. Sentiment analysis utilized BERT, RoBERTa, and VADER models. Preprocessing involved tokenization, lemmatization, part-of-speech tagging, and stop-word filtering. Lexicon analysis identified themes through recurring n-grams, visualized using Python.</p><p><strong>Results: </strong>User demographics revealed comparable ages for psilocybin mushrooms (23.8 ± 0.9 years) and LSD users (20.0 ± 0.6 years), with a predominance of male users. The BERT model predominantly labeled experiences as negative (unfavorable), particularly for mushroom users (p = 0.001). VADER indicated more positive experiences for mushroom users (p < 0.001), while RoBERTa mainly classified experiences as negative or neutral. Significant gender differences were found only with VADER, where more male users expressed positive opinions about psilocybin mushrooms (74.09% versus 65.52%, p < 0.021). The VADER model yielded more polarized results, whereas RoBERTa's cautious classifications indicate its suitability for analyzing lengthy and complex psychedelic reports. Further, RoBERTa outperformed other transformer-based models, achieving the highest accuracy. Lexicon analysis revealed emotional, sensory, and temporal themes, with psilocybin reports emphasizing introspection and time dilation phenomenon, while LSD reports highlighted memory issues and cognitive disorientation.</p><p><strong>Conclusions: </strong>Sentiment analysis showed that VADER produced more polarized results, while RoBERTa offered cautious classifications with the highest accuracy. Lexicon analysis revealed shared themes, with mushroom reports focusing on introspection and time dilation perception, while those of LSD emphasized cognitive disturbances. This study highlights the value of these analyses in understanding psychedelic experiences, informing harm reduction, and guiding policy-making.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"559-575"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging Tools to Support DILI Assessment in Clinical Trials with Abnormal Baseline Serum Liver Tests or Pre-existing Liver Diseases.","authors":"Jasmine Amirzadegan, Bereket Tesfaldet, Y Veronica Pei, Eileen Navarro Almario, Mark I Avigan, Paul H Hayashi","doi":"10.1007/s40264-024-01511-8","DOIUrl":"10.1007/s40264-024-01511-8","url":null,"abstract":"<p><p>Based on the late Dr. Hyman Zimmerman's observation that hepatocellular drug-induced liver injury (DILI) leading to jaundice carries a ≥ 10% fatality risk (coined as Hy's law by others), evaluation of Drug-Induced Serious Hepatotoxicity (eDISH) continues to play a central role in the assessment of a study drug's liability for acute hepatocellular DILI. The eDISH identifies drugs in clinical trials with DILI fatality (death or transplant) risk that may be unacceptable in a post-market setting. As a two-dimensional graph that plots peak total bilirubin (TB) versus peak serum aminotransferase levels for each patient during study drug or comparator treatment, eDISH identifies potential cases of acute, modest, and serious hepatocellular DILI for in-depth analysis of liver tests (LT) and clinical course so that the likelihood of causal association with the study drug can be determined. Unfortunately, the generalizable utility of this tool only pertains to trials enrolling patients with normal or near normal (NNN) baseline (BL) serum LTs. The eDISH does not necessarily apply to trials of patients with abnormal baseline (ABN-BL) LTs that often coincide with underlying liver disorders. Because drug development programs being reviewed by the FDA increasingly target liver disorders, we are often challenged to evaluate DILI risk in trials of patients with ABN-BL LTs. Also, the high background prevalence of metabolic dysfunction associated steatotic liver disease (MASLD) means patients with LTs above NNN may need to be enrolled in trials treating non-liver disorders to reflect the target population. Such study populations create challenges for industry and regulators because eDISH may not reliably categorize or identify potential cases of DILI for further analysis, as it so efficiently does in NNN-BL trials. We describe the main functionalities of eDISH in NNN-BL trials to understand what should be emulated by new tools or eDISH modifications. We then discuss non-eDISH-based plots that may be useful in ABN-BL trials.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"443-453"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11982145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143390510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network Analysis and Machine Learning for Signal Detection and Prioritization Using Electronic Healthcare Records and Administrative Databases: A Proof of Concept in Drug-Induced Acute Myocardial Infarction.","authors":"Maria Antonietta Barbieri, Andrea Abate, Olivér M Balogh, Mátyás Pétervári, Péter Ferdinandy, Bence Ágg, Vera Battini, Marianna Cocco, Andrea Rossi, Carla Carnovale, Manuela Casula, Edoardo Spina, Maurizio Sessa","doi":"10.1007/s40264-025-01515-y","DOIUrl":"10.1007/s40264-025-01515-y","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Safety signals for potential drug-induced adverse events (AEs) typically emerge from multiple data sources, primarily spontaneous reporting systems, despite known limitations. Increasingly, real-world data from sources such as electronic health records (EHRs) and administrative databases are leveraged for signal detection. Although network analysis has shown promise in mapping relationships between clinical attributes for signal detection in spontaneous reporting system databases, its application in real-world data from EHRs and administrative databases remains limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to evaluate the performance of network analysis in detecting safety signals within Italian administrative databases, using drug-induced acute myocardial infarction (AMI) as a proof of concept.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We employed a case-crossover design to explore the association between drug exposure and AMI using the Healthcare Administrative Database of Mantova, Italy, from 2014 to 2018. Patients with their first AMI hospitalization were identified after a 365-day washout period to exclude prior hospitalizations. We constructed a network to analyse the relationships between prescribed drugs and diagnoses, represented as nodes, with undirected edges illustrating their interactions. For each patient with AMI, we identified all diagnoses and drugs recorded or redeemed within 365 days of the first AMI episode and generated various drug-diagnosis, drug-drug, and diagnosis-diagnosis pairs. We calculated the frequency of these pairs, and three types of edge weights quantified the strength of connections. We identified outlier drug-AMI pairs using a predictive score (F) based on frequency (C) and full edge weights (W&lt;sub&gt;F&lt;/sub&gt;), with validation for known AMI associations. We prioritized signals using the F score, C of AMI, and W&lt;sub&gt;F&lt;/sub&gt;, analysed through k-means clustering to identify patterns in the data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;From 2014 to 2018, a total of 3918 patients had an AMI, with 4686 AMI diagnoses. Of those, 2866 had prescriptions in the previous year, totalling 498,591 prescriptions. A network analysis identified 2968 unique nodes, revealing 529,935 diagnosis-diagnosis connections, 235,380 drug-diagnosis connections, and 102,831 drug-drug connections. The median number of connections (C) was 404 (Q1-Q3: 194-671) for drug nodes and 380 (Q1-Q3: 216-664) for diagnosis nodes. The median W&lt;sub&gt;F&lt;/sub&gt; was 11.8 (Q1-Q3: 9-14), and the median F score across pairs was 0.1 (Q1-Q3: 0.1-0.3). A total of 249 potential safety signals were detected, with 63.4% aligning with known AEs. Among the remaining signals, 80 were prioritized, and five emerged as the highest priority: terazosin, tamsulosin, allopurinol, esomeprazole, and omeprazole.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Overall, our novel method demonstrates that network analysis is a valuable tool for signal detection and prioriti","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"513-526"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11982071/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143364029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk of Fracture Associated with Pregabalin or Mirogabalin Use: A Case-Case-Time-Control Study Based on Japanese Health Insurance Claims Data.","authors":"Hinako Wakabayashi, Toshiki Fukasawa, Satomi Yoshida, Kairi Ri, Soichiro Masuda, Takayuki Anno, Koji Kawakami","doi":"10.1007/s40264-025-01516-x","DOIUrl":"10.1007/s40264-025-01516-x","url":null,"abstract":"<p><strong>Background: </strong>Pregabalin is widely used for neuropathic pain. Mirogabalin, a newer gabapentinoid, was recently introduced in several Asian countries. A previous case-crossover study showed an association between pregabalin and fall-related injuries, but the findings may have been affected by biases from individual- and population-level exposure time trends, and generalizability was limited due to a focus on a middle-aged population. Further, no findings have appeared on mirogabalin and its association with fall-related fractures.</p><p><strong>Objective: </strong>We conducted a case-case-time-control study to investigate the risk of fracture associated with pregabalin and mirogabalin in a population with broad demographic coverage.</p><p><strong>Methods: </strong>Incident fractures were identified from a Japanese claims database. For each case, hazard (days 1-30 before the fracture event) and control windows (days 61-90 before the event) were set. Each current case was matched by age and sex to a future case, defined as a patient who experienced a fracture 120-365 days later. Odds ratios (ORs) were estimated using conditional logistic regression models.</p><p><strong>Results: </strong>A total of 814,216 and 460,811 cases were included in the pregabalin and mirogabalin analyses, respectively. ORs were 1.35 (95% confidence interval 1.28-1.43) for pregabalin and 1.53 (1.35-1.72) for mirogabalin, indicating an increased risk of fracture with both drugs. These results remained consistent and robust across sensitivity and subgroup analyses, except in patients under 65 years of age.</p><p><strong>Conclusion: </strong>Given this observed risk and the fact that these medications are commonly prescribed to older populations, caution is warranted in clinical use.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"503-511"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143398782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequential Epidemiological Analyses of Real-World Data: A Tool for Prospective Drug Safety Surveillance from the Rofecoxib Example.","authors":"Saad Hanif Abbasi, Lars Christian Lund, Jesper Hallas, Anton Pottegård","doi":"10.1007/s40264-024-01512-7","DOIUrl":"10.1007/s40264-024-01512-7","url":null,"abstract":"<p><strong>Introduction: </strong>Large administrative healthcare databases can be used for near real-time sequential safety surveillance of drugs as an alternative approach to traditional reporting-based pharmacovigilance. The study aims to build and empirically test a prospective drug safety monitoring setup and perform a sequential safety monitoring of rofecoxib use and risk of cardiovascular outcomes.</p><p><strong>Methods: </strong>We used Danish population-based health registers and performed sequential analysis of rofecoxib use and cardiovascular outcomes using case-time-control and cohort study designs from January 2000 to September 2004. Each monitoring period added 6 months of data until the end of the study period. In the case-time-control study, incident cases of myocardial infarction (MI) and ischemic stroke were identified and matched with up to five time controls on age, sex, and calendar time. Exposure status on the date of diagnosis was assessed using a 60-day focal window, with reference windows 120, 180, and 240 days prior to the diagnoses. In the cohort study, incident users of rofecoxib were matched up to 1:4 with ibuprofen users (active comparators) using high-dimensional disease risk scores and were followed for 60 days.</p><p><strong>Results: </strong>The earliest association between rofecoxib use and the risk of MI was seen in study period 2 for case-time-control design (OR 1.42, 95% CI 1.04-1.93) and in study period 7 for the cohort study design (RR 1.22; 95% CI 1.02-1.47).</p><p><strong>Conclusions: </strong>Our prospective drug safety monitoring setup showed that the risk of MI could have been detected 3.5 years before the ultimate market withdrawal of rofecoxib. However, further research is needed to validate this approach.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"489-502"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11982122/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Longitudinal Post-authorization Safety Study of Golimumab in Treatment of Ulcerative Colitis: A Cohort Study in Denmark and Sweden, 2013-2021.","authors":"Annette Kjær Ersbøll, Zhiping Huang, Deanna D Hill, Simone Møller Hede, Vibeke Andersen, Kristian Bolin, Marie Skov Kristensen, Suzan Esslinger, Frida Richter Hansen, Erik Hertervig, Lila Kallio, Thora Majlund Kjærulff, Stine Kloster, Alexis Krumme, James D Lewis, Laila Mehkri, Niels Qvist, Lau Caspar Thygesen, Cindy Weinstein, Anders Green","doi":"10.1007/s40264-025-01519-8","DOIUrl":"10.1007/s40264-025-01519-8","url":null,"abstract":"<p><strong>Background: </strong>When golimumab (GLM) was approved for the treatment of moderate to severe ulcerative colitis (UC) in 2013, a post-authorization safety study was conducted.</p><p><strong>Objective: </strong>Our objective was to examine whether exposure to GLM was associated with an increased incidence of all-cause total colectomy, colorectal cancer, and hepatosplenic T-cell lymphoma in Denmark and Sweden.</p><p><strong>Methods: </strong>We conducted a new-user, active comparator cohort study of patients with UC in 2013-2021. Exposure to GLM, other anti-tumor necrosis factor (TNF) agents (infliximab and adalimumab) and thiopurines was a time-varying variable. Therapies were based on prescription redemptions and hospital-based administration of medications from national prescription and hospital registers. The association between exposure to study therapies and outcomes was evaluated using Poisson regression of incidence rates (IRs), presented as IR ratios (IRRs) and 95% confidence intervals (CIs).</p><p><strong>Results: </strong>A total of 5177 and 7469 patients were included in Denmark and Sweden, respectively. The IR of all-cause total colectomy per 1000 person-years was higher in Denmark (IR 42.6; 95% CI 38.9-46.2) than in Sweden (IR 16.1; 95% CI 14.2-18.0). No significant difference was observed in all-cause total colectomy between GLM and other anti-TNF agents (Denmark: adjusted IRR [aIRR] 1.28; 95% CI 0.98-1.66; Sweden: aIRR 1.17; 95% CI 0.72-1.90). A significant difference was observed between GLM and thiopurines (Denmark: aIRR 13.62; 95% CI 8.73-21.26; Sweden: aIRR 4.52; 2.75-7.41). Privacy regulations prevented analysis of a few colorectal cancer events. No hepatosplenic T-cell lymphoma events were identified.</p><p><strong>Conclusion: </strong>The IR of all-cause total colectomy with GLM was similar to that with other anti-TNF agents but was much higher than with thiopurines, probably related to confounding by indication.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"541-558"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11982097/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Stakeholder Call to Action for the Future of Vaccine Post-Marketing Monitoring: Proceedings from the First Beyond COVID-19 Monitoring Excellence (BeCOME) Conference.","authors":"Vincent Bauchau, Kaatje Bollaerts, Phil Bryan, Jim Buttery, Kourtney Davis, Robert T Chen, Daniel R Feikin, Antonella Fretta, Sarah Frise, Sonja Gandhi-Banga, Hector S Izurieta, Corinne Jouquelet-Royer, Alena Khromava, Lin Li, Raj Long, Sarah MacDonald, Lydie Marcelon, Robert Massouh, Wilhelmine Meeraus, Flor M Munoz, Karen Naim, Dale Nordenberg, Hanna Nohynek, Heather Rubino, Daniel A Salmon, Sarah Sellers, Laurence Serradell, Laurence Torcel-Pagnon, Jamie Wilkins","doi":"10.1007/s40264-024-01510-9","DOIUrl":"10.1007/s40264-024-01510-9","url":null,"abstract":"","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"577-585"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11982078/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142946472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}