Might be useful in cases where the experimental treatment is expected to be effective in the overall population.

1. As these designs comprise two sequential stages, it follows that the sample size calculation should also be staged.
2. At the first stage, the standard formula for a traditional randomized trial can be used for the biomarker-positive subgroup using the significance level α to estimate the treatment effect in that subgroup.
3. The formula used in the enrichment designs for the required total number of events or the required number of patients can be used at the first stage of these designs.
4. At the second stage, the sample size must be adjusted in order to yield appropriate power for the entire population.

• At the first stage, the standard formula for a traditional randomized trial which is the same as the formula proposed for enrichment designs can be applied for the biomarker-positive subgroup.
• At the second stage, the sample size formula proposed for marker stratified designs aiming to yield appropriate power for the entire population could be considered.

Advantages

• Can control the overall type I error α.
• Can require smaller sample size as compared to the subgroup-specific designs, especially when we assume that the novel treatment equally benefits both biomarker-defined subgroups.

Limitations

• Can be problematic for determining whether the treatment is beneficial in the biomarker-negative subgroup.
• Cannot control the probability of rejecting the null hypothesis of no treatment effect in the biomarker-negative subgroup when the treatment benefit is restricted to biomarker-positive patients. Consequently, there is a high risk of inappropriately recommending the novel treatment for biomarker-negative patients due to the large treatment effect in the biomarker-positive subgroup.

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