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Matrix decomposition in meta-analysis for extraction of adverse event pattern and patient-level safety profile.

ABSTRACT: The purpose of assessing adverse events (AEs) in clinical studies is to evaluate what AE patterns are likely to occur during treatment. In contrast, it is difficult to specify which of these patterns occurs in each patient. To tackle this challenging issue, we constructed a new statistical model including nonnegative matrix factorization by incorporating background knowledge of AE-specific structures such as severity and drug mechanism of action. The model uses a meta-analysis framework for integrating data from multiple clinical studies because insufficient information is derived from a single trial. We demonstrated the proposed method by applying it to real data consisting of three Phase III studies, two mechanisms of action, five anticancer treatments, 3317 patients, 848 AE types, and 99,546 AEs. The extracted typical treatment-specific AE patterns coincided with medical knowledge. We also demonstrated patient-level safety profiles using the data of AEs that were observed by the end of the second cycle.

SUBMITTER: Matsuura K

PROVIDER: S-EPMC8359197 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Matrix decomposition in meta-analysis for extraction of adverse event pattern and patient-level safety profile.

Matsuura Kentaro K Tsuchida Jun J Ando Shuji S Sozu Takashi T

Pharmaceutical statistics 20210305 4

The purpose of assessing adverse events (AEs) in clinical studies is to evaluate what AE patterns are likely to occur during treatment. In contrast, it is difficult to specify which of these patterns occurs in each patient. To tackle this challenging issue, we constructed a new statistical model including nonnegative matrix factorization by incorporating background knowledge of AE-specific structures such as severity and drug mechanism of action. The model uses a meta-analysis framework for inte ...[more]

PMID: 33675157

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Project description:IntroductionVortioxetine, a multimodal serotonergic drug, is widely used as treatment for major depressive disorder. Although on the market since late 2013, the data of the relative safety of vortioxetine, especially compared to selective serotonin reuptake inhibitors, are still scarce.ObjectiveThe aim of this study was to explore the adverse event reporting pattern of vortioxetine through a cluster analysis. Furthermore, to compare the adverse event reporting pattern for vortioxetine with that of the selective serotonin reuptake inhibitors.MethodsIndividual case safety reports for vortioxetine in VigiBase up to 1 November, 2019 were subjected to consensus clustering, to identify and describe natural groupings of reports based on their reported adverse events. A vigiPoint exploratory analysis compared vortioxetine to the selective serotonin reuptake inhibitors in terms of relative frequencies for a wide range of covariates, including patient sex and age, reported drugs and adverse events, and reporting country. Important differences were identified using odds ratios with adaptive statistical shrinkage.ResultsThirty-six clusters containing at least five reports were identified and analysed. The two largest clusters included 48% of the vortioxetine reports and appeared to represent gastrointestinal adverse events and hypersensitivity adverse events. Other distinct clusters were related to, respectively, fatigue, aggression/suicidality, convulsion, medication errors, arthralgia/myalgia, increased weight, paraesthesia and anticholinergic effects. Some of these clusters are not labelled for vortioxetine, such as arthralgia/myalgia and paraesthesia, but are known adverse events for selective serotonin reuptake inhibitors. A vigiPoint analysis revealed a higher proportion of reports from consumers and non-health professionals for vortioxetine as well as higher relative reporting rates of gastrointestinal symptoms, pruritus and mood-related symptoms, consistent with the cluster analysis.ConclusionsA pattern of co-reported adverse events that is consistent with labelled adverse events for vortioxetine and the safety profile for selective serotonin reuptake inhibitors in general was revealed. Clusters of unlabelled adverse events were identified that reflect clinical entities that might represent signals of previously unknown adverse events. More extensive analyses of spontaneous reports may help to further understand the reporting pattern of adverse events.

Project description:Text mining for the life sciences aims to aid database curation, knowledge summarization and information retrieval through the automated processing of biomedical texts. To provide comprehensive coverage and enable full integration with existing biomolecular database records, it is crucial that text mining tools scale up to millions of articles and that their analyses can be unambiguously linked to information recorded in resources such as UniProt, KEGG, BioGRID and NCBI databases. In this study, we investigate how fully automated text mining of complex biomolecular events can be augmented with a normalization strategy that identifies biological concepts in text, mapping them to identifiers at varying levels of granularity, ranging from canonicalized symbols to unique gene and proteins and broad gene families. To this end, we have combined two state-of-the-art text mining components, previously evaluated on two community-wide challenges, and have extended and improved upon these methods by exploiting their complementary nature. Using these systems, we perform normalization and event extraction to create a large-scale resource that is publicly available, unique in semantic scope, and covers all 21.9 million PubMed abstracts and 460 thousand PubMed Central open access full-text articles. This dataset contains 40 million biomolecular events involving 76 million gene/protein mentions, linked to 122 thousand distinct genes from 5032 species across the full taxonomic tree. Detailed evaluations and analyses reveal promising results for application of this data in database and pathway curation efforts. The main software components used in this study are released under an open-source license. Further, the resulting dataset is freely accessible through a novel API, providing programmatic and customized access (http://www.evexdb.org/api/v001/). Finally, to allow for large-scale bioinformatic analyses, the entire resource is available for bulk download from http://evexdb.org/download/, under the Creative Commons - Attribution - Share Alike (CC BY-SA) license.

Project description:BackgroundOver the last decade attention has grown to give patients and next of kin (P/N) more substantial roles in adverse event investigations. Adverse event investigations occur after adverse events that resulted in death or severe injury. Few studies have focused on patient perspectives on their involvement in such investigations. The present study sets out to investigate how P/N and patient representatives (client councils and the Patient Federation Netherlands) view the involvement of P/N in adverse event investigations, particularly whether and why they want to involved, and how they want to shape their involvement.MethodsThe study features qualitative data on three levels: interviews with P/N (personal), focus groups with representatives of client councils (institutional), and an interview with the Patient Federation Netherlands (national). Researchers used inductive, thematic analysis and validated the results through data source triangulation.ResultsThe initiative taken by the hospitals in this study provided P/N with the space to feel heard and a position as legitimate stakeholder. P/N appreciated the opportunity to choose whether and how they wanted to be involved in the investigation as stakeholders. P/N emphasized the need for hospitals to learn from the investigations, but for them the investigation was also part of a more encompassing relationship. P/N's views showed the inextricable link between the first conversation with the health care professional and the investigation, and the ongoing care after the investigation was finalized. Hence, an adverse event investigation is part of a broader experience when understood from a patient perspective.ConclusionsAn adverse event investigation should be considered as part of an existing relationship between P/N and hospital that starts before the investigation and continues during follow up care. It is crucial for hospitals to take the initiative in the investigation and in the involvement of P/N. P/N motivations for involvement can be understood as driven by agency or communion. Agentic motivations include being an active participant by choice, while communion motivations include the need to be heard.

Dataset Information

Matrix decomposition in meta-analysis for extraction of adverse event pattern and patient-level safety profile.

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Matrix decomposition in meta-analysis for extraction of adverse event pattern and patient-level safety profile.

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