Sample Size Re-estimation with the Com-Nougue Method to Evaluate Treatment Effect

Jin Wang ()
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Jin Wang: Biometrics, Abbott Vascular

Statistics in Biosciences, 2022, vol. 14, issue 1, No 6, 90-103

Abstract: Abstract The binary endpoint and the time-to-event (TTE) endpoint are the main staple for clinical evaluation. The TTE endpoint is typically utilized when the follow-up is long, and the attrition rate is substantial. In the latter case, if the constant hazard ratio condition is approximately accurate, typically the Cox regression is applied to all available information by accommodating early terminations. However, if the treatment effect is fluctuating over time to such a degree that the proportional hazard ratio assumption is seriously violated, alternative approaches need to be considered, including in the setting of adaptive trial design. Due to the lack of literature focusing on application of the Com-Nougue method in the adaptive trial design, this paper is to highlight the unique features of sample size re-estimation under the Com-Nougue approach in contrast to some typical statistical techniques, with some representative simulations. In most scenarios of the simulations, including both superiority and non-inferiority (NI) tests, constant and piecewise hazard ratio under the exponential distribution, the Com-Nougue method performs well with the adaptive design. Cox regression excels in the proportional hazard ratio setting due to the use of all available data. This paper illustrates the utility of the Com-Nougue method in adaptive clinical trial design. It also provides a simple and convenient approach to calculate the conditional power and sample size under arbitrary underlying true parameter assumptions.

Keywords: Adaptive design; Com-Nougue; Promising zone; Conditional power; Piecewise (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s12561-021-09316-4

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