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相关论文: Deep Historical Borrowing Framework to Prospective…

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Bayesian dynamic borrowing methods incorporate historical control data into current clinical trial analyses while allowing the degree of borrowing to depend on the compatibility between historical and current data. Although many methods…

统计方法学 · 统计学 2026-05-27 Tomohiro Ohigashi , Wataru Murasaki , Masahiko Gosho

Use of historical control data to augment a small internal control arm in a randomized control trial (RCT) can lead to significant improvement of the efficiency of the trial. It introduces the risk of potential bias, since the historical…

统计方法学 · 统计学 2022-10-05 Jixian Wang , Hongtao Zhang , Ram Tiwari

Bayesian dynamic borrowing has become an increasingly important tool for evaluating the consistency of regional treatment effects which is a key requirement for local regulatory approval of a new drug. It helps increase the precision of…

统计方法学 · 统计学 2026-01-06 Xin Zhang , Hui Zhang , Satrajit Roychoudhury

Meta-analytic-predictive (MAP) priors have been proposed as a generic approach to deriving informative prior distributions, where external empirical data are processed to learn about certain parameter distributions. The use of MAP priors is…

统计方法学 · 统计学 2025-11-11 Christian Röver , Tim Friede

Information borrowing from historical data is gaining attention in clinical trials of rare and pediatric diseases, where statistical power may be insufficient for confirmation of efficacy if the sample size is small. Although Bayesian…

统计方法学 · 统计学 2023-05-25 Masahiro Kojima

When incorporating historical control data into the analysis of current randomized controlled trial data, it is critical to account for differences between the datasets. When the cause of the difference is an unmeasured factor and…

统计方法学 · 统计学 2025-09-10 Tomohiro Ohigashi , Kazushi Maruo , Takashi Sozu , Masahiko Gosho

Use of historical data in clinical trial design and analysis has shown various advantages such as reduction of within-study placebo-treated number of subjects and increase of study power. The meta-analytic-predictive (MAP) approach accounts…

应用统计 · 统计学 2019-12-12 Sebastian Weber , Yue Li , John Seaman , Tomoyuki Kakizume , Heinz Schmidli

In pre- and non-clinical toxicology, the reduction of animal use is highly desireable. Although approaches for possible sample size reduction in the concurrent control group were suggested previously under the virtual control groups…

统计方法学 · 统计学 2026-03-13 Max Menssen , Carsten Kneuer , Gyamfi Akyianu , Christian Röver , Tim Friede , Frank Schaarschmidt

Bayesian clinical trials can benefit of available historical information through the elicitation of informative prior distributions. Concerns are however often raised about the potential for prior-data conflict and the impact of Bayes test…

统计方法学 · 统计学 2022-12-01 Silvia Calderazzo , Annette Kopp-Schneider

There is currently a focus on statistical methods which can use historical trial information to help accelerate the discovery, development and delivery of medicine. Bayesian methods can be constructed so that the borrowing is "dynamic" in…

统计方法学 · 统计学 2024-09-13 Darren A. V. Scott , Alex Lewin

In pharmaceutical and toxicological research, historical control data are increasingly used to validate concurrent control groups, typically via the construction of historical control limits. While methods have been described for continuous…

统计方法学 · 统计学 2026-03-24 Sören Budig , Frank Schaarschmidt , Max Menssen

Basket trials have emerged as a new class of efficient approaches in oncology to evaluate a new treatment in several patient subgroups simultaneously. In this paper, we extend the key ideas to disease areas outside of oncology, developing a…

统计方法学 · 统计学 2020-06-01 Haiyan Zheng , James M. S. Wason

Incorporating historical information into the design and analysis of a new clinical trial has been the subject of much recent discussion. For example, in the context of clinical trials of antibiotics for drug resistant infections, where…

统计方法学 · 统计学 2018-06-08 Isaac Gravestock , Leonhard Held

External controls from historical trials or observational data can augment randomized controlled trials when large-scale randomization is impractical or unethical, such as in drug evaluation for rare diseases. However, non-randomized…

统计方法学 · 统计学 2025-05-08 Ke Zhu , Shu Yang , Xiaofei Wang

Historical data from previous clinical trials, observational studies and health records may be utilized in analysis of clinical trials data to strengthen inference. Under the Bayesian framework incorporation of information obtained from any…

应用统计 · 统计学 2021-03-23 Shirin Golchi

Randomized controlled trials (RCTs) are the gold standard for causal inference, yet practical constraints often limit the size of the concurrent control arm. Borrowing control data from previous trials offers a potential efficiency gain,…

统计方法学 · 统计学 2026-03-17 Linying Yang , Xing Liu , Robin J. Evans

The power prior is a popular class of informative priors for incorporating information from historical data. It involves raising the likelihood for the historical data to a power, which acts as a discounting parameter. When the discounting…

统计方法学 · 统计学 2025-05-26 Yueqi Shen , Matthew A. Psioda , Luiz M. Carvalho , Joseph G. Ibrahim

Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is how to effectively borrow information from historical data while maintaining a reasonable type I…

统计方法学 · 统计学 2020-12-15 Liyun Jiang , Lei Nie , Ying Yuan

In clinical trials, there often exist multiple historical studies for the same or related treatment investigated in the current trial. Incorporating historical data in the analysis of the current study is of great importance, as it can help…

统计方法学 · 统计学 2021-02-02 Huaqing Jin , Guosheng Yin

In early phase drug development of combination therapy, the primary objective is to preliminarily assess whether there is additive activity from a novel agent when combined with an established monotherapy. Due to potential feasibility…

统计方法学 · 统计学 2025-02-24 Zhaohua Lu , John Toso , Girma Ayele , Philip He
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