Optimal Two-Stage Randomized Multinomial Designs for Phase II Oncology Trials

Abstract

A new two-stage design is proposed that is suitable for early detection of the anticancer activity of experimental therapies in Phase II oncology trials. The endpoints of interest are response rate and early progression rate. The anticancer activity is defined by a positive signal in one endpoint and a non-negative signal in the other endpoint. The two endpoints are modeled by the multinomial distribution. The design is optimal in that it minimizes the patient exposure when the experimental therapies are inactive. The design parameters are found by a grid searching algorithm under type I and type II error rate constraints. Examples of the design are also presented in this paper.

Key Words:

• Multinomial
• Oncology trials
• Progression
• Randomized
• Response

Notes

^† n ₁ and n ₂ are the sample sizes at each stage per arm. N _max is the total sample size for both arms. ^‡The optimal designs minimize the expected sample size. The minimax designs minimize the maximum sample size.

^† n ₁ and n ₂ are the sample sizes at each stage per arm. N _max is the total sample size for both arms. ^‡The optimal designs minimize the expected sample size. The minimax designs minimize the maximum sample size.

^† n ₁ and n ₂ are the sample sizes at each stage per arm. N _max is the total sample size for both arms. ^‡The optimal designs minimize the expected sample size. The minimax designs minimize the maximum sample size.