ArticleClinical pharmacology and therapeutics2014
Use of internet search logs to evaluate potential drug adverse events.
Article in Clinical pharmacology and therapeutics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS.Drug safety · 2017Article
- Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts.Drug safety · 2017Article
- Social Media Listening for Routine Post-Marketing Safety Surveillance.Drug safety · 2016Article
- Big Data Transforms Discovery-Utilization Therapeutics Continuum.Clinical pharmacology and therapeutics · 2016Article
- The potential of translational bioinformatics approaches for pharmacology research.British journal of clinical pharmacology · 2015Article
- Analyzing search behavior of healthcare professionals for drug safety surveillance.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2015Article
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Internet search logs provide an abundant source of data that can be explored for purposes such as identifying drug exposure-adverse event relationships. The methodology to rigorously conduct such evaluations is not well characterized, and the utility of such analyses is not well defined. In this issue, White and colleagues propose an approach using Internet search logs for this purpose and compare it to parallel analyses conducted using the US Food and Drug Administration's spontaneous reporting database.
Indexed as
Identifiers
25056395What OpenQuestion holds
Registered trials
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.