ArticleBMC medical research methodology2014
Estimating time-to-onset of adverse drug reactions from spontaneous reporting databases.
Article in BMC medical research methodology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- The Value of Time-to-Onset for Signal Validation: Experience from the Reporting of COVID-19 Vaccines and Glomerular Diseases in VigiBase.Drug safety · 2026Article
- Theoretical Framework and Key Considerations for Time-to-Onset Analysis in Spontaneous Reporting Systems.Drug safety · 2026Review
- Antihypertensive treatment and adverse psychiatric reactions in primary health care.Journal of human hypertension · 2026Article
- Comparative disproportionality signals for methotrexate monotherapy versus methotrexate combined with hydroxychloroquine, leflunomide, or sulfasalazine in rheumatoid arthritis: newly highlighted signals evaluated using drug information safety profiles.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Pharmacovigilance analysis of infliximab in inflammatory bowel disease: novel safety signals and sex-specific adverse event profiles from the FAERS database (2004-2024).Frontiers in immunology · 2026Article
- Real-world pharmacovigilance of drug-related bone metabolism disorders: integrating FAERS and VigiAccess with a Bradford Hill-based causal plausibility assessment.Frontiers in pharmacology · 2026Article
- Age-stratified adverse-event reporting signals of seven ALK/ROS1 tyrosine kinase inhibitors in FAERS: a disproportionality and time to onset study.Frontiers in pharmacology · 2026Article
- Real-world pharmacovigilance assessment of meropenem-associated adverse events: age stratification and time-to-onset analysis using FAERS.Frontiers in medicine · 2026Article
- The refinement of repeated exact time-to-event modeling: methodological refinements and implementation in NONMEMFrontiers in pharmacology · 2026Article
- Safety profile of entrectinib in NSCLC: Multi-source pharmacovigilance analysis using FAERS and JADER.PloS one · 2026Article
- Pharmacovigilance assessment of drug-induced aplastic anemia: analysis of the FDA adverse event reporting system.International journal of clinical pharmacy · 2025Article
- Article
- Safety profile of lanreotide: a retrospective post-marketing pharmacovigilance study based on the real-world data from FAERS database.Endocrine · 2025Article
- Postmarketing safety evaluation of pemetrexed using FAERS and JADER databases.Scientific reports · 2025Article
- Post-Marketing Safety Concerns with Efgartigimod alfa: A Pharmacovigilance Analysis Based on the Food and Drug Administration Adverse Event Reporting System Database.Clinical epidemiology · 2025Article
- Safety assessment of sodium zirconium cyclosilicate: A FAERS-based disproportionality analysis.PloS one · 2025Article
- Disproportionality analysis of biliary adverse events associated with fibrates using the JADER and FAERS databases.Frontiers in pharmacology · 2025Article
- Signal mining and analysis of adverse events of Brentuximab Vedotin base on FAERS and JADER databases.PloS one · 2025Article
- Unveiling the hidden risk of caspofungin: insights from three adverse event reporting systems and network pharmacology integration.Frontiers in pharmacology · 2025Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalyzing time-to-onset of adverse drug reactions from treatment exposure contributes to meeting pharmacovigilance objectives, i.e. identification and prevention. Post-marketing data are available from reporting systems. Times-to-onset from such databases are right-truncated because some patients who were exposed to the drug and who will eventually develop the adverse drug reaction may do it after the time of analysis and thus are not included in the data. Acknowledgment of the developments adapted to right-truncated data is not widespread and these methods have never been used in pharmacovigilance. We assess the use of appropriate methods as well as the consequences of not taking right truncation into account (naive approach) on parametric maximum likelihood estimation of time-to-onset distribution.
methodsBoth approaches, naive or taking right truncation into account, were compared with a simulation study. We used twelve scenarios for the exponential distribution and twenty-four for the Weibull and log-logistic distributions. These scenarios are defined by a set of parameters: the parameters of the time-to-onset distribution, the probability of this distribution falling within an observable values interval and the sample size. An application to reported lymphoma after anti TNF- α treatment from the French pharmacovigilance is presented.
resultsThe simulation study shows that the bias and the mean squared error might in some instances be unacceptably large when right truncation is not considered while the truncation-based estimator shows always better and often satisfactory performances and the gap may be large. For the real dataset, the estimated expected time-to-onset leads to a minimum difference of 58 weeks between both approaches, which is not negligible. This difference is obtained for the Weibull model, under which the estimated probability of this distribution falling within an observable values interval is not far from 1.
conclusionsIt is necessary to take right truncation into account for estimating time-to-onset of adverse drug reactions from spontaneous reporting databases.
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