Quantitative signal detection using spontaneous ADR reporting

By Andrew Bate, S. Evans. Pharmacoepidemiology and Drug Safety, 2009

847 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/df724ab567b36759a1aff801b75ad7fac9c2c334

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Citations in the corpus

Data-Driven Prediction of Drug Effects and Interactions (2012, methodology): “Indication bias is one of the most common examples of this and occurs when a drug is synthetically associated with an event that is more appropriately attributed to the underlying disease ( 4 ).”
Molecular Systems Biology Peer Review Process File Indi: a Computational Framework for Inferring Drug Interactions and Their Associated Recommendations Transaction Report (neutral): “…in the ADRs such as under-reporting, duplicate reports or change in reporting methodologies over time (Rawlins, 1988; van der Heijden et al, 2002; Bate and Evans, 2009), the necessity to pre-define drug classes, and the inability to handle novel and rarely used drugs for which no or limited…”
Pharmacological inhibition of cystine–glutamate exchange induces endoplasmic reticulum stress and ferroptosis (2014, background): “Using disproportionality analysis (Bate and Evans, 2009), we identified adverse drug effects for sorafenib and for a set of comparison kinase-targeted drugs for which sufficient data was available in our data (dasatinib, erlotinib, gefitinib, imatinib, lapatinib, and sunitinib), none of which (at…”
Dose-Specific Adverse Drug Reaction Identification in Electronic Patient Records: Temporal Data Mining in an Inpatient Psychiatric Population (2014, methodology): “The aim of these analyses is to generate hypotheses of causal relationships between drugs and AEs, referred to as signal detection [14].”
Portable Automatic Text Classification for Adverse Drug Reaction Detection via Multi-corpus Training (2014, background): “Such spontaneous reporting systems also suffer from a range of limitations including under-reporting (only approximately 10% of serious ADRs are reported [12] in AERS), over-reporting of known ADRs, incomplete data, duplicated reporting, unspecified causal links and so on [13, 14].”
Detection of drug‐drug interactions through data mining studies using clinical sources, scientific literature and social media (2018, neutral): “However, there are also some challenges in SRS as FAERS that limit their application, such as reporting bias or sampling variance [49, 141, 142].”