Related Experiment Video
Updated: Jun 13, 2025
A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
Power and sample size calculation for non-inferiority trials with treatment switching in intention-to-treat analysis
Austin Shih1, Chih-Yuan Hsu2,3, Yu Shyr4,5
1Department of Mathematics, Vanderbilt University, Nashville, TN, 37240, USA.
Background:
Difference in Restricted Mean Survival Time (DRMST) has attracted attention and is increasingly used in non-inferiority (NI) trials because of its superior power in detecting treatment effects compared to hazard ratio. However, when treatment switching (also known as crossover) occurs, the widely used intention-to-treat (ITT) analysis can underpower or overpower NI trials.
Methods:
We propose a simulation-based approach, named nifts, to calculate powers and determine the necessary sample size to achieve a desired power for non-inferiority trials that allow treatment switching, in ITT analysis using DRMST.
Results:
The nifts approach offers three options for a non-inferiority margin, assumes three entry patterns and generalized gamma distributions for event time, incorporates two distributions for dropout censoring, and provides five distribution options for switching. Real-world and simulated examples are used to illustrate the proposed method and examine how switching probability, switching time, the relative effectiveness of treatments, allocation ratio, entry patterns, and event time distribution influence powers and sample sizes. nifts adjusts the non-inferiority margins intended for NI trials without treatment switching to accommodate the presence of treatment switching in the designs. With the adjusted margins, the type I errors are well-controlled. The ratios of sample sizes with treatment switching to those without switching are close to 1, indicating no significant change in power at sample sizes without switching when using adjusted margins. The performance on power and sample sizes is not sensitive to the choice of switch time distributions.
Conclusions:
This simulation-based approach provides power and sample size calculation in NI trials with treatment switching, when comparing the RMSTs of two treatment groups in ITT analysis. With its comprehensive parameter settings, nifts will be useful for designing NI trials that allow for treatment switching. nifts is freely available at https://github.com/cyhsuTN/nifts .
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
Related Concept Videos
01:09Comparing Experimental Results: Student's t-Test
01:09Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
01:17Sign Test for Matched Pairs
To conduct the sign test, we first calculate the differences in...
01:23McNemar's Test
01:25Choosing Between z and t Distribution
01:21Testing a Claim about Mean: Unknown Population SD
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...