Purpose: Data mining has been introduced as one of the most useful methods for signal detection by spontaneous reports, but data mining is not always effective in detecting all safety issues. To investigate appropriate situations in which data mining is effective in routine signal detection activities, we analyzed the characteristics of signals that the US Food and Drug Administration (FDA) identified from the FDA Adverse Event Reporting System (FAERS).
Methods: Among the signals that the FDA identified from the FAERS between 2008 1Q and 2014 4Q, we selected 233 signals to evaluate in this study. We conducted a disproportionality analysis and classified these signals into two groups according to the presence or absence of statistical significance in the reporting odds ratio (ROR). Then, we compared the two groups based on the characteristics of the suspected drugs and adverse events (AEs).
Results: Safety signals were most frequently identified for new drugs that had been on the market for less than 5 years, but some signals were still identified for old drugs (≥20 years), and most of them were statistically significant. The proportion of the signals for "serious" events was significantly higher in the group of nonsignals by ROR (Fisher's exact test, P = 0.032).
Conclusions: Data mining was shown to be effective in the following situations: (1) early detection of safety issues for newly marketed drugs, (2) continuous monitoring of safety issues for old drugs, and (3) signal detection of nonserious AEs, to which little attention is usually given.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/pds.4672 | DOI Listing |
Front Artif Intell
January 2025
Language Intelligence and Information Retrieval (LIIR) Lab, Department of Computer Science, KU Leuven, Leuven, Belgium.
The digitization of healthcare records has revolutionized medical research and patient care, with electronic health records (EHRs) containing a wealth of structured and unstructured data. Extracting valuable information from unstructured clinical text presents a significant challenge, necessitating automated tools for efficient data mining. Natural language processing (NLP) methods have been pivotal in this endeavor, aiming to extract crucial clinical concepts embedded within free-form text.
View Article and Find Full Text PDFMicrolife
January 2025
Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, 45141 Essen, Germany.
Oil reservoirs are society's primary source of hydrocarbons. While microbial communities in industrially exploited oil reservoirs have been investigated in the past, pristine microbial communities in untapped oil reservoirs are little explored, as are distribution patterns of respective genetic signatures. Here, we show that a pristine oil sample contains a complex community consisting of bacteria and fungi for the degradation of hydrocarbons.
View Article and Find Full Text PDFExpert Opin Drug Saf
January 2025
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Background: Drug-induced thrombocytopenia (DITP) often occurs in patients during clinical treatment. However, clinicians usually fail to distinguish which drugs can be plausible culprits accurately. We aimed to develop a large comprehensive drug benchmark database with DITP toxicity using the recommended method by FDA.
View Article and Find Full Text PDFSci Total Environ
January 2025
College of Ecology and Environment, Joint Center for sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; Yale-NUIST Center on Atmospheric Environment, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China. Electronic address:
Methane (CH) emissions from the coal industry represent a substantial portion of anthropogenic CH emissions from energy-related activities. China ranks as the world's largest coal producer, where Shanxi Province is one of its major coal production regions and accounts for 20.7 % of the national total coal production.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Radiology, Yantaishan Hospital, Yantai, Shandong, China.
Diabetic retinopathy, a retinal disorder resulting from diabetes mellitus, is a prominent cause of visual degradation and loss among the global population. Therefore, the identification and classification of diabetic retinopathy are of utmost importance in the clinical diagnosis and therapy. Currently, these duties are extensively carried out by manual examination utilizing the human visual system.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!