Lester Reich

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PURPOSE To describe instances of inadvertent intrathecal injection of ionic contrast media and to consider treatment approaches, and diagnostic and medicolegal issues. METHODS Ten cases of inadvertent injection, of which nine were reported to the manufacturers/authors and one appeared in the literature, are related with emphasis on similarity of(More)
Several data mining algorithms (DMAs) are being studied in hopes of enhancing screening of large post-marketing safety databases for signals of novel adverse events (AEs). The objective of this study was to apply two DMAs to the United States FDA Adverse Event Reporting System (AERS) database to see whether signals of potentially fatal AEs with cancer drugs(More)
Data mining is receiving considerable attention as a tool for pharmacovigilance and is generating many perspectives on its uses. This paper presents four concepts that have appeared in various professional venues and represent potential sources of misunderstanding and/or entail extended discussions: (i) data mining algorithms are unvalidated; (ii) data(More)
In the adjuvant setting, the third-generation aromatase inhibitors (AIs) anastrozole, letrozole and exemestane are recommended at some point during treatment, either in the upfront, switch after tamoxifen or extended treatment setting after tamoxifen in postmenopausal patients with hormone receptor-positive early breast cancer. AIs have demonstrated(More)
Dear Sirs, A principal concern of pharmacovigilance is the timely identification of adverse drug reactions (ADRs) to medicines that are novel in terms of their clinical nature, severity, and/or frequency. This can involve identifying ‘‘signals’’ of previously unreported drugevent combinations (DECs). There appears to be considerable semantic imprecision(More)
Pharmacovigilance experts devote considerable effort to post-marketing surveillance of adverse drug reactions (ADRs). Although the prepared mind of the pharmacovigilance expert remains the cornerstone of this process [1], statistical algorithms, also known as data mining algorithms (DMAs), are being promoted as supplementary tools for safety reviewers.(More)
OBJECTIVE To apply two data mining algorithms (DMAs) to Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) reports that involved endotoxin-like reactions with intravenous gentamicin to determine whether a signal of disproportionate reporting of these events would have been generated concurrently with surveillance based on clinical(More)