BackgroundAttitudes of healthcare professionals regarding spontaneous reporting of adverse drug reactions (ADRs) in Japan are not well known, and Japan’s unique system of surveillance, called early post-marketing phase vigilance (EPPV), may affect these reporting attitudes. Our objectives were to describe potential effects of EPPV and to test whether ADR seriousness, prominence, and frequency are related to changes in reporting over time.MethodsA manufacturer’s database of spontaneous ADR reports was used to extract data from individual case safety reports for 5 drugs subject to EPPV. The trend of reporting and the time lag between ADR onset and reporting to the manufacturer were examined. The following indices for ADRs occurring with each drug were calculated and analyzed to assess reporting trends: Serious:Non-serious ratio, High prominence:Low prominence ratio, and High frequency:Low frequency ratio.ResultsFor all 5 drugs, the time lag between ADR onset and reporting to the manufacturer was shorter in the EPPV period than in the post-EPPV period. All drugs showed higher Serious:Non-serious ratios in the post-EPPV period. No specific patterns were observed for the High prominence:Low prominence ratio. The High frequency:Low frequency ratio for peginterferon alpha-2a and sevelamer hydrochloride decreased steadily throughout the study period.ConclusionsHealthcare professionals may be more likely to report serious ADRs than to report non-serious ADRs, but the effect of event prominence on reporting trends is still unclear. Factors associated with ADR reporting attitude in Japan might be different from those in other countries because of EPPV and the involvement of medical representatives in the spontaneous reporting process. Pharmacovigilance specialists should therefore be cautious when comparing data between different time periods or different countries. Further studies are needed to elucidate the underlying mechanism of spontaneous ADR reporting in Japan.
BackgroundAlthough several reports have suggested that patient-generated data from Internet sources could be used to improve drug safety and pharmacovigilance, few studies have identified such data sources in Japan. We introduce a unique Japanese data source: tōbyōki, which translates literally as “an account of a struggle with disease.”ObjectiveThe objective of this study was to evaluate the basic characteristics of the TOBYO database, a collection of tōbyōki blogs on the Internet, and discuss potential applications for pharmacovigilance.MethodsWe analyzed the overall gender and age distribution of the patient-generated TOBYO database and compared this with other external databases generated by health care professionals. For detailed analysis, we prepared separate datasets for blogs written by patients with depression and blogs written by patients with rheumatoid arthritis (RA), because these conditions were expected to entail subjective patient symptoms such as discomfort, insomnia, and pain. Frequently appearing medical terms were counted, and their variations were compared with those in an external adverse drug reaction (ADR) reporting database. Frequently appearing words regarding patients with depression and patients with RA were visualized using word clouds and word cooccurrence networks.ResultsAs of June 4, 2016, the TOBYO database comprised 54,010 blogs representing 1405 disorders. Overall, more entries were written by female bloggers (68.8%) than by male bloggers (30.8%). The most frequently observed disorders were breast cancer (4983 blogs), depression (3556), infertility (2430), RA (1118), and panic disorder (1090). Comparison of medical terms observed in tōbyōki blogs with those in an external ADR reporting database showed that subjective and symptomatic events and general terms tended to be frequently observed in tōbyōki blogs (eg, anxiety, headache, and pain), whereas events using more technical medical terms (eg, syndrome and abnormal laboratory test result) tended to be observed frequently in the ADR database. We also confirmed the feasibility of using visualization techniques to obtain insights from unstructured text-based tōbyōki blog data. Word clouds described the characteristics of each disorder, such as “sleeping” and “anxiety” in depression and “pain” and “painful” in RA.ConclusionsPharmacovigilance should maintain a strong focus on patients’ actual experiences, concerns, and outcomes, and this approach can be expected to uncover hidden adverse event signals earlier and to help us understand adverse events in a patient-centered way. Patient-generated tōbyōki blogs in the TOBYO database showed unique characteristics that were different from the data in existing sources generated by health care professionals. Analysis of tōbyōki blogs would add value to the assessment of disorders with a high prevalence in women, psychiatric disorders in which subjective symptoms have important clinical meaning, refractory disorders, and other chronic disorders.
EGFR inhibitor-associated rash:future directions for management and investigation outcomes from / the HER1/EGFR inhibitor rash management forum. Application of a Japanese insurance claims database to pharmacovigilance activities in pharmaceutical industry was discussed. Using a commercially available insurance claims database, incidences of several cancers, the number of patients who were administered anticancer agents, and possible adverse effects were studied. Cancer incidences obtained from the database were virtually equivalent to those from a traditional survey program. The number of cancer patients included in the database with one million beneficiaries, were a few thousands a year. Disorders in epithelial-derived tissue were observed more frequently in lung cancer patients after the initiation of EGF tyrosine kinase inhibitor therapy than after platinum-based therapy, suggesting possible candidates of adverse effects of the EGF tyrosine kinase. We concluded that an estimation of disease incidence and selecting candidates of adverse events with the claims database is theoretically possible. And the database is also applicable to pharmacovigilance fields. (Jpn J Pharmacoepidemiol 2012;17(2) :145-153)
A BSTRA CT BACKGROUND The development and expanding accessibility of large-scale medical databases support increasing use of these databases for clinical epidemiological studies in Japan. METHODS Members of the Database Utilization Committee of the Society of Clinical Epidemiology discussed the ways to enhance scientific rigor in the utilization of large-scale medical databases in Japan. The topics covered included what we need to know about the current research environment when conducting large-scale medical database studies, the key points to consider when conducting clinical research using these databases, and the use of realworld evidence in regulatory decision making. RESULTS In generating real-world evidence, several evaluation principles should be noted: the characteristics of data commonly used for clinical epidemiology in Japan; the need for reproducibility and transparency in database studies; the development of research questions for database studies; the need to assess the quality and validity of data; and legal and ethical considerations. We also introduce the discussions on real-world evidence for drug approval applications. CONCLUSION With rapid technological developments, the characteristics of medical databases and analytical methods will evolve over time. Keeping these principles in mind, we must continuously update the evaluation methods and strategies used to assess the data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.