Frequentist analysis of basket trials with one-sample Mantel-Haenszel procedures

TL;DR

This paper introduces a simple, purely frequentist method for basket trials using Mantel-Haenszel procedures, enabling efficient and interpretable analysis under common treatment effect assumptions, with potential for confirmatory trial design.

Contribution

It develops a novel frequentist approach for basket trials based on Mantel-Haenszel procedures, offering simplicity, consistency, and interpretability over existing Bayesian methods.

Findings

Proposed estimator is consistent under large strata and sparse data models.

Introduces dually consistent variance estimators for reliable inference.

Provides a method for identifying effective basket subclasses.

Abstract

Recent substantial advances of molecular targeted oncology drug development is requiring new paradigms for early-phase clinical trial methodologies to enable us to evaluate efficacy of several subtypes simultaneously and efficiently. The concept of the basket trial is getting of much attention to realize this requirement borrowing information across subtypes, which are called baskets. Bayesian approach is a natural approach to this end and indeed the majority of the existing proposals relies on it. On the other hand, it required complicated modeling and may not necessarily control the type 1 error probabilities at the nominal level. In this paper, we develop a purely frequentist approach for basket trials based on one-sample Mantel-Haenszel procedure relying on a very simple idea for borrowing information under the common treatment effect assumption over baskets. We show that the proposed estimator is consistent under two limiting models of the large strata and sparse data limiting models (dually consistent) and propose dually consistent variance estimators. The proposed Mantel-Haenszel estimators are interpretable even if the common treatment assumptions are violated. Then, we can design basket trials in a confirmatory matter. We also propose an information criterion approach to identify effective subclass of baskets.