ArticlePharmacoepidemiology and drug safety2014
A modular, prospective, semi-automated drug safety monitoring system for use in a distributed data environment.
Article in Pharmacoepidemiology and drug safety, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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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.
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.
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Who cites it
16 citing papers in PubMed, 27 citations in OpenAlex.
- Active surveillance of drug safety in healthcare data: Sequential monitoring of bacterial and serious urinary tract infection risk in sodium-glucose cotransporter 2 inhibitor users.British journal of clinical pharmacology · 2026Article
- Sequential Epidemiological Analyses of Real-World Data: A Tool for Prospective Drug Safety Surveillance from the Rofecoxib Example.Drug safety · 2025Article
- New Function for Safety Signal Monitoring in MID-NETClinical and translational science · 2025Article
- Prospective Monitoring of New Drugs in Older Adults with and without Frailty: Near-Real-Time Assessment of Effectiveness and Safety of Oral Anticoagulants in Medicare Data.Drugs & aging · 2024Article
- Assessing the Benefits and Harms of Pharmacotherapy in Older Adults with Frailty: Insights from Pharmacoepidemiologic Studies of Routine Health Care Data.Drugs & aging · 2024Review
- The State of Use and Utility of Negative Controls in Pharmacoepidemiologic Studies.American journal of epidemiology · 2024Review
- Surveillance of Antidepressant Safety (SADS): Active Signal Detection of Serious Medical Events Following SSRI and SNRI Initiation Using Big Healthcare Data.Drug safety · 2021Article
- Safety and Effectiveness of Direct Oral Anticoagulants Versus Vitamin K Antagonists: Pilot Implementation of a Near-Real-Time Monitoring Program in Italy.Journal of the American Heart Association · 2018Observational
- Automated data-adaptive analytics for electronic healthcare data to study causal treatment effects.Clinical epidemiology · 2018Review
- Development and application of two semi-automated tools for targeted medical product surveillance in a distributed data network.Current epidemiology reports · 2017Article
- Continuous Post-Market Sequential Safety Surveillance with Minimum Events to Signal.Revstat statistical journal · 2017Article
- The Potential Return on Public Investment in Detecting Adverse Drug Effects.Medical care · 2017Article
- Leveraging Food and Drug Administration Adverse Event Reports for the Automated Monitoring of Electronic Health Records in a Pediatric Hospital.Biomedical informatics insights · 2017Article
- Successful Comparison of US Food and Drug Administration Sentinel Analysis Tools to Traditional Approaches in Quantifying a Known Drug-Adverse Event Association.Clinical pharmacology and therapeutics · 2016Article
- Transparency and Reproducibility of Observational Cohort Studies Using Large Healthcare Databases.Clinical pharmacology and therapeutics · 2016Article
- Product-Specific Regulatory Pathways to Approve Generic Drugs: The Need for Follow-up Studies to Ensure Safety and Effectiveness.Drug safety · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
purposeThe aim of this study was to develop and test a semi-automated process for conducting routine active safety monitoring for new drugs in a network of electronic healthcare databases.
methodsWe built a modular program that semi-automatically performs cohort identification, confounding adjustment, diagnostic checks, aggregation and effect estimation across multiple databases, and application of a sequential alerting algorithm. During beta-testing, we applied the system to five databases to evaluate nine examples emulating prospective monitoring with retrospective data (five pairs for which we expected signals, two negative controls, and two examples for which it was uncertain whether a signal would be expected): cerivastatin versus atorvastatin and rhabdomyolysis; paroxetine versus tricyclic antidepressants and gastrointestinal bleed; lisinopril versus angiotensin receptor blockers and angioedema; ciprofloxacin versus macrolide antibiotics and Achilles tendon rupture; rofecoxib versus non-selective non-steroidal anti-inflammatory drugs (ns-NSAIDs) and myocardial infarction; telithromycin versus azithromycin and hepatotoxicity; rosuvastatin versus atorvastatin and diabetes and rhabdomyolysis; and celecoxib versus ns-NSAIDs and myocardial infarction.
resultsWe describe the program, the necessary inputs, and the assumed data environment. In beta-testing, the system generated four alerts, all among positive control examples (i.e., lisinopril and angioedema; rofecoxib and myocardial infarction; ciprofloxacin and tendon rupture; and cerivastatin and rhabdomyolysis). Sequential effect estimates for each example were consistent in direction and magnitude with existing literature.
conclusionsBeta-testing across nine drug-outcome examples demonstrated the feasibility of the proposed semi-automated prospective monitoring approach. In retrospective assessments, the system identified an increased risk of myocardial infarction with rofecoxib and an increased risk of rhabdomyolysis with cerivastatin years before these drugs were withdrawn from the market.
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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.