ArticleJournal of biopharmaceutical statistics2020
Time-trend impact on treatment estimation in two-arm clinical trials with a binary outcome and Bayesian response adaptive randomization.
Article in Journal of biopharmaceutical statistics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- 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
- Evaluating Bayesian adaptive randomization procedures with adaptive clip methods for multi-arm trials.Statistical methods in medical research · 2021Article
- Statistical consideration when adding new arms to ongoing clinical trials: the potentials and the caveats.Trials · 2021Article
- Including non-concurrent control patients in the analysis of platform trials: is it worth it?BMC medical research methodology · 2020Article
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
Clinical trial design and analysis often assume study population homogeneity, although patient baseline profile and standard of care may evolve over time, especially in trials with long recruitment periods. The time-trend phenomenon can affect the treatment estimation and the operating characteristics of trials with Bayesian response adaptive randomization (BRAR). The mechanism of time-trend impact on BRAR is increasingly being studied but some aspects remain unclear. The goal of this research is to quantify the bias in treatment effect estimation due to the use of BRAR in the presence of time-trend. In addition, simulations are conducted to compare the performance of three commonly used BRAR algorithms under different time-trend patterns with and without early stopping rules. The results demonstrate that using these BRAR methods in a two-arm trial with time-trend may cause type I error inflation and treatment effect estimation bias. The magnitude and direction of the bias are affected by the parameters of the BRAR algorithm and the time-trend pattern.
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Registered trials
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