Phase II trial design with growth modulation index as the primary endpoint

Area of Science:

• Oncology
• Biostatistics
• Clinical Trial Design

Background:

• Advanced cancer treatments increasingly utilize molecularly targeted therapies, genomic-driven approaches, and immunotherapies.
• The growth modulation index (GMI) is a key metric for assessing treatment efficacy in relapse or refractory cancer patients.
• Limited literature exists on clinical trial designs specifically using GMI as a primary endpoint.

Purpose of the Study:

• To derive a sample size formula for score tests within a log-linear model for GMI.
• To provide statistically sound methods for phase II clinical trial designs with GMI as the primary endpoint.

Main Methods:

• Derivation of a sample size formula for the score test under a log-linear model of GMI.
• Illustration of study designs using the derived formula, incorporating bivariate exponential and Weibull frailty models.
• Application to generalized treatment effect size for robust statistical analysis.

Main Results:

• A novel sample size formula for GMI-based primary endpoint analysis in clinical trials has been developed.
• The derived formula is applicable across various statistical models, including bivariate exponential and Weibull frailty models.
• The proposed methods offer a statistically rigorous framework for single-arm phase II trials.

Conclusions:

• The derived sample size formula provides a robust statistical foundation for designing phase II clinical trials where GMI is the primary endpoint.
• This work addresses a gap in the literature by offering practical guidance for GMI-focused trial design.
• The proposed statistical methods support the advancement of precision medicine in oncology by enabling better evaluation of novel cancer therapies.