ArticleBiometrics2015
Continuous versus group sequential analysis for post-market drug and vaccine safety surveillance.
Article in Biometrics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Near real-time vaccine safety surveillance using electronic health records-a systematic review of the application of statistical methods.Pharmacoepidemiology and drug safety · 2016Pooled it
- Robust Alpha Spending for Unstable Data.Statistics in medicine · 2026Article
- Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.Statistics in medicine · 2026Article
- Active Surveillance for COVID-19 Vaccine Safety Using Sequential Analysis in Korea: Population-Based Retrospective Observational Study.JMIR public health and surveillance · 2026Observational
- Sequential Safety Surveillance of RSVpreF Vaccination During Pregnancy Early in the Postapproval Period.JAMA network open · 2026Article
- Sequential analysis for post-marketing drug safety surveillance using routinely collected electronic healthcare data: a scoping review.Therapeutic advances in drug safety · 2026Article
- A lesson in embracing uncertainty in early safety signals from the Tsepamo study.AIDS (London, England) · 2025Article
- Article
- Exact sequential test for clinical trials and post-market drug and vaccine safety surveillance with Poisson and binary data.Statistics in medicine · 2021Article
- Innovative trial designs and analyses for vaccine clinical development.Contemporary clinical trials · 2021Article
- A Bayesian approach to sequential analysis in post-licensure vaccine safety surveillance.Pharmaceutical statistics · 2020Article
- Alpha spending for historical versus surveillance Poisson data with CMaxSPRT.Statistics in medicine · 2019Article
- Exact conditional maximized sequential probability ratio test adjusted for covariates.Sequential analysis · 2019Article
- Use of routinely collected electronic healthcare data for postlicensure vaccine safety signal detection: a systematic review.BMJ global health · 2019Article
- Conditional power as an aid in making interim decisions in observational studies.European journal of epidemiology · 2018Article
- Type I Error Probability Spending for Post-Market Drug and Vaccine Safety Surveillance With Poisson Data.Methodology and computing in applied probability · 2018Article
- Sources of Safety Data and Statistical Strategies for Design and Analysis: Postmarket Surveillance.Therapeutic innovation & regulatory science · 2018Review
- Type I error probability spending for post-market drug and vaccine safety surveillance with binomial data.Statistics in medicine · 2018Article
- Active Monitoring of Adverse Drug Reactions with Neural Network Technology.Chinese medical journal · 2017Article
- A Synthesis of Current Surveillance Planning Methods for the Sequential Monitoring of Drug and Vaccine Adverse Effects Using Electronic Health Care Data.EGEMS (Washington, DC) · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The use of sequential statistical analysis for post-market drug safety surveillance is quickly emerging. Both continuous and group sequential analysis have been used, but consensus is lacking as to when to use which approach. We compare the statistical performance of continuous and group sequential analysis in terms of type I error probability; statistical power; expected time to signal when the null hypothesis is rejected; and the sample size required to end surveillance without rejecting the null. We present a mathematical proposition to show that for any group sequential design there always exists a continuous sequential design that is uniformly better. As a consequence, it is shown that more frequent testing is always better. Additionally, for a Poisson based probability model and a flat rejection boundary in terms of the log likelihood ratio, we compare the performance of various continuous and group sequential designs. Using exact calculations, we found that, for the parameter settings used, there is always a continuous design with shorter expected time to signal than the best group design. The two key conclusions from this article are (i) that any post-market safety surveillance system should attempt to obtain data as frequently as possible, and (ii) that sequential testing should always be performed when new data arrives without deliberately waiting for additional data.
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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.