The efficiency of clinical trial designs for predictive biomarker validation.

BACKGROUND: The rapid advance of molecular genetic technology and of molecular diagnostics companies have set the stage for a new era in personalized treatments. Biomarkers such as gene expressions may be integrated into the anatomically based tumor-node-metastasis staging system to provide information for risk stratification and treatment selection. With the assumption that preliminary results show evidence that a biomarker has predictive value, the marker-based designs are geared to assess the purported predictive value in a clinical trial.
PURPOSE: In this article, we compared the efficiency of the traditional design, which does not involve a biomarker, to several alternative designs in terms of the sample size required in each trial.
METHODS: We first derived the variance formulas for the two-sample t-tests under the various designs when the biomarker assay is imperfect, and then conducted numerical and simulation studies to evaluate the performance of the various designs.
RESULTS: Based on numerical and simulation studies, we conclude that the marker-based strategy designs are less efficient than the traditional design in general. Since the biomarker assay is imperfect in a realistic setting, the estimated sample size for each alternative design is influenced by the sensitivity and specificity of the assay and the prevalence of the biomarker in the population of interest as well as the parameters involved in a standard sample size calculation. LIMITATIONS: Due to limitations of a simulation study, it is not clear whether our results can be generalized to other parameter settings that are different from the ones used in the simulation study.
CONCLUSIONS: The marker-based strategy designs are less efficient than the traditional design in general. If there is no treatment effect among marker-negative patients, it is still feasible to use the marker-based strategy design I if the assay sensitivity is high. If the treatment effect among marker-negative patients is half of the effect among marker-positive patients, the marker prevalence must be relatively high and the sensitivity of the assay must be very high for the marker-based strategy design I to approximate the efficiency of the traditional design. The efficiency of the marker-based strategy design II relative to the traditional design is low in all scenarios considered under the current study.