ArticlePharmaceutical statistics2018
Response-adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?
Article in Pharmaceutical statistics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Trial
- Bayesian Response-Adaptive Randomization for Cluster Randomized Controlled Trials.Statistics in medicine · 2026Article
- Optimal allocation strategies in platform trials with continuous endpoints.Statistical methods in medical research · 2024Article
- Response-adaptive randomization in clinical trials: from myths to practical considerations.Statistical science : a review journal of the Institute of Mathematical Statistics · 2023Article
- Inference in response-adaptive clinical trials when the enrolled population varies over time.Biometrics · 2023Article
- A novel statistical test for treatment differences in clinical trials using a response-adaptive forward-looking Gittins Index Rule.Biometrics · 2023Article
- Generalisations of a Bayesian decision-theoretic randomisation procedure and the impact of delayed responses.Computational statistics & data analysis · 2022Article
- Should RECOVERY have used response adaptive randomisation? Evidence from a simulation study.BMC medical research methodology · 2022Article
- The Temptation of Overgeneralizing Response-adaptive Randomization.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Reply to Villar et al.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Age-based targeting of biannual azithromycin distribution for child survival in Niger: an adaptive cluster-randomized trial protocol (AVENIR).BMC public health · 2021Article
- Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.BMC medicine · 2020Article
- Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19.Statistics in biopharmaceutical research · 2020Article
- Including non-concurrent control patients in the analysis of platform trials: is it worth it?BMC medical research methodology · 2020Article
- Time-trend impact on treatment estimation in two-arm clinical trials with a binary outcome and Bayesian response adaptive randomization.Journal of biopharmaceutical statistics · 2020Article
- To add or not to add a new treatment arm to a multiarm study: A decision-theoretic framework.Statistics in medicine · 2019Article
- Response-adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?Pharmaceutical statistics · 2018Article
- Design Considerations for a Phase II Platform Trial in Major Depressive Disorder.Pharmaceutical statisticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Response-adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients-referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2-armed and the multi-armed case. We further propose a RAR design for multi-armed clinical trials, which is computationally efficient and robust to several time trends considered.
Indexed as
Identifiers
What 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.