A Comparison Study of Algorithms to Detect Drug–Adverse Event Associations: Frequentist, Bayesian, and Machine-Learning Approaches
- MedicineDrug Safety
Methods popular in the pharmacovigilance literature did not perform well and will need modification before their properties can be used in the drug–adverse event association problem, and the Bayesian confidence propagation neural network had the highest AUC overall.
Review of Statistical Methodologies for Detecting Drug–Drug Interactions Using Spontaneous Reporting Systems
- MedicineFront. Pharmacol.
This article reviews the studies on the latest statistical methodologies from classical methodologies for signal detection of DDIs using spontaneous reporting system, and describes how to calculate for each detection method and the major findings from the published literatures about DDIs.
Signal Detection of Adverse Drug Reaction using the Adverse Event Reporting System: Literature Review and Novel Methods
- Computer Science
This paper presents a meta-analyses of the literature on Bayesian Confidence Propagation Neural Network and its applications to Testing and Comparison, which shows clear trends in what works and what does not work.
Comparison of Signal Detection Algorithms Based on Frequency Statistical Model for Drug-Drug Interaction Using Spontaneous Reporting Systems
- MedicinePharmaceutical Research
Among the five models, the Ω shrinkage measure model showed the most conservative signal detection tendency, and will contribute to the selection of appropriate statistical models to detect signals of potential DDIs.
Detection algorithms and attentive points of safety signal using spontaneous reporting systems as a clinical data source.
- MedicineBriefings in bioinformatics
Signal detection using data mining is described, considering traditional methods and the latest knowledge, and their limitations, including methods that consider the patient background and those that identify drug-drug interactions.
Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology
- Medicine, BiologyEBioMedicine
Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach
- Computer ScienceJMIR public health and surveillance
This study proposes a causality measure that can detect an adverse reaction that is caused by a drug rather than merely being a correlated signal, and obtains an ADR detection accuracy of 74% on a large-scale manually annotated dataset of tweets.
Learning Causality Patterns for Detecting Adverse Drug Reactions from Social Media
- Computer Science
This paper proposes a causality measure that can detect an adverse reaction that is caused by a drug rather than merely being a correlated signal, and is the first causality-sensitive approach for detecting ADRs from social media.
Logistic Regression Likelihood Ratio Test Analysis for Detecting Signals of Adverse Events in Post-market Safety Surveillance
- Computer ScienceJournal of biopharmaceutical statistics
This article proposes a more flexible logistic regression approach which allows for covariates of all types rather than relying solely on stratification, and outlines a procedure for signal detection that accounts for multiple comparisons and controls the overall Type 1 error rate.
SHOWING 1-10 OF 15 REFERENCES
Are all quantitative postmarketing signal detection methods equal? Performance characteristics of logistic regression and Multi‐item Gamma Poisson Shrinker
- Computer SciencePharmacoepidemiology and drug safety
Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application that uses two algorithms for routine analyses: empirical Bayes Multi‐item Gamma Poisson Shrinker and logistic regression (LR).
Novel Data‐Mining Methodologies for Adverse Drug Event Discovery and Analysis
- Computer Science, MedicineClinical pharmacology and therapeutics
An overview of recent methodological innovations and data sources used to support ADE discovery and analysis is provided.
Advancing the Science for Active Surveillance: Rationale and Design for the Observational Medical Outcomes Partnership
- MedicineAnnals of Internal Medicine
The governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated, are described.
Large-scale regression-based pattern discovery: The example of screening the WHO global drug safety database
- Political Science
The results show that regression-based pattern discovery does offer practical advantages, and shrinkage regression should be used in parallel to existing measures of interestingness in ADR surveillance and other large-scale pattern discovery applications.
Quantitative signal detection using spontaneous ADR reporting
- Environmental SciencePharmacoepidemiology and drug safety
The role of Bayesian shrinkage in screening spontaneous reports, the importance of changes over time in screening the properties of the measures and some suggestions as to where emerging research is likely to lead are given.
Antipsychotics, glycemic disorders, and life-threatening diabetic events: a Bayesian data-mining analysis of the FDA adverse event reporting system (1968-2004).
- Medicine, PsychologyAnnals of clinical psychiatry : official journal of the American Academy of Clinical Psychiatrists
There are consistent and substantial differences between atypical antipsychotic drugs in the disproportionality reporting ratios relating to glycemic effects, especially life-threatening events, in the AERS database, and these results do not support a "class effect" hypothesis.
Data mining for signals in spontaneous reporting databases: proceed with caution
- MedicinePharmacoepidemiology and drug safety
To provide commentary and points of caution to consider before incorporating data mining as a routine component of any Pharmacovigilance program, and to stimulate further research aimed at better…
Novel Statistical Tools for Monitoring the Safety of Marketed Drugs
- BiologyClinical pharmacology and therapeutics
The statistical concepts behind these methods, as well as their practical application to monitoring the safety of pharmaceutical products using spontaneous AE reports are described and examples of how these tools can be used to identify novel drug interactions and demographic risk factors for adverse drug reactions are provided.
Contrast Media and Nephropathy: Findings From Systematic Analysis and Food and Drug Administration Reports of Adverse Effects
- MedicineInvestigative radiology
Context:Recent studies suggest differences in the incidence of contrast-induced nephropathy (CIN) among contrast media (CM). Objective:To determine whether there are significant differences among…
Drug-Induced Diseases: Prevention, Detection, and Management
In its second edition, this essential and comprehensive resource provides a detailed analysis of how to identify, prevent, and manage drug-induced diseases.