Adaptive design and timeline prediction for cardiovascular event trials for a non-inferiority/superiority claim

Quan, Hui; Mao, Xuezhou; Wu, Yujun; Cho, Meehyung; Zhao, Peng-Liang; Zhang, Ji; Bauer, Déborah

doi:10.1080/23737484.2015.1088419

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Timeline Prediction1

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2018

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“…wherẽandS are the density and survival function of the event time; and S c is the survival function of the censoring time, without conditioning on the treatment indicator. A timeline prediction method based on blinded data can be found in the work of Quan et al 21 Our approach generalizes their method by allowing arbitrary number of pieces in the piecewise exponential distributions and treatment crossover.…”

Section: Timeline Predictionmentioning

confidence: 99%

Design and monitoring of survival trials in complex scenarios

Luo

Mao

Chen

et al. 2018

Statistics in Medicine

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This paper proposes an approach to design and monitor survival trials accounting for complex scenarios such as delayed treatment effect, treatment dilution, and treatment crossover. These scenarios often lead to non‐proportional hazards, making study design and monitoring more difficult. We demonstrate that, with event times following piecewise exponential distributions, the log‐rank statistic as well as its variance‐covariance structure can be easily computed, which greatly simplifies study design and monitoring. As the number of pieces in the exponential distributions can be arbitrary, this approach can handle a wide range of scenarios. Three hypothetical examples are used to demonstrate its potential use.

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Section: Timeline Predictionmentioning

confidence: 99%