Bayesian modeling and prediction of accrual in multi-regional clinical trials.

Bayesian modeling and prediction of accrual in multi-regional clinical trials.
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DOI:
10.1177/0962280214557581
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发表时间:
2017-04
影响因子:
2.3
通讯作者:
Long Q
Long Q
中科院分区:
医学3区
文献类型:
--
作者:
Deng Y;Zhang X;Long Q

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在多地区试验中,潜在的总体和地区特定的应计率通常不会随着时间的推移而保持恒定,不同地区可能有不同的启动时间,这与每个地区内应计率的初始跳跃相结合,通常会导致总体应计率不连续,与多地区试验相关的这些问题尚未得到充分研究。在本文中,我们澄清了多区域性质的影响,在临床试验中的应计建模和预测,并探讨了贝叶斯方法的应计建模和预测,该模型使用非齐次泊松过程(NHPP)的区域特定的应计,并允许在每个地区的潜在泊松率随时间而变化。所提出的方法可以适应不同地区/中心的交错启动时间和不同的初始应计率。我们的数值研究表明,所提出的方法提高了准确性和精度的应计预测相比,现有的方法,包括NHPP模型,不模拟特定区域的应计。
In multi-regional trials, the underlying overall and region-specific accrual rates often do not hold constant over time and different regions could have different start-up times, which combined with initial jump in accrual within each region often leads to a discontinuous overall accrual rate, and these issues associated with multi-regional trials have not been adequately investigated. In this paper, we clarify the implication of the multi-regional nature on modeling and prediction of accrual in clinical trials and investigate a Bayesian approach for accrual modeling and prediction, which models region-specific accrual using a nonhomogeneous Poisson process (NHPP) and allows the underlying Poisson rate in each region to vary over time. The proposed approach can accommodate staggered start-up times and different initial accrual rates across regions/centers. Our numerical studies show that the proposed method improves accuracy and precision of accrual prediction compared to existing methods including the NHPP model that does not model region-specific accrual.
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