ArticleDrug safety2017
Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS.
Article in Drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Alemtuzumab and thrombotic thrombocytopenic purpura: Analysis of an international surveillance database and systematic literature review.Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis · 2025Pooled it
- Off-the-Shelf Large Language Models for Causality Assessment of Individual Case Safety Reports: A Proof-of-Concept with COVID-19 Vaccines.Drug safety · 2025Article
- Application of a Language Model Tool for COVID-19 Vaccine Adverse Event Monitoring Using Web and Social Media Content: Algorithm Development and Validation Study.JMIR infodemiology · 2024Article
- A New Method to Extract Health-Related Quality of Life Data From Social Media Testimonies: Algorithm Development and Validation.Journal of medical Internet research · 2022Article
- Article
- Hypothesis-free signal detection in healthcare databases: finding its value for pharmacovigilance.Therapeutic advances in drug safety · 2019Article
- Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis.Journal of medical Internet research · 2018Article
- Adverse Reactions Associated With Cannabis Consumption as Evident From Search Engine Queries.JMIR public health and surveillance · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPost-marketing drug surveillance is largely based on signals found in spontaneous reports from patients and healthcare providers. Rare adverse drug reactions and adverse events (AEs) that may develop after long-term exposure to a drug or from drug interactions may be missed. The US FDA and others have proposed that web-based data could be mined as a resource to detect latent signals associated with adverse drug reactions.
methodsRecently, a web-based search query method called a query log reaction score (QLRS) was developed to detect whether AEs associated with certain drugs could be found from search engine query data. In this study, we compare the performance of two other algorithms, the proportional query ratio (PQR) and the proportional query rate ratio (Q-PRR) against that of two reference signal-detection algorithms (SDAs) commonly used with the FDA AE Reporting System (FAERS) database.
resultsIn summary, the web query methods have moderate sensitivity (80%) in detecting signals in web query data compared with reference SDAs in FAERS when the web query data are filtered, but the query metrics generate many false-positives and have low specificity compared with reference SDAs in FAERS.
conclusionFuture research is needed to find better refinements of query data and/or the metrics to improve the specificity of these web query log algorithms.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.