Estimands for Randomized Discontinuation Designs in Oncology

TL;DR

This paper proposes an estimand framework tailored for randomized discontinuation designs in oncology trials, aiming to clarify objectives and improve regulatory decision-making.

Contribution

It introduces a specific estimand framework for RDDs in oncology, addressing current ambiguities and aligning trial objectives with statistical analysis.

Findings

Application to JAVELIN Gastric 100 trial illustrates framework utility.

Comparison highlights differences between RDDs and traditional RCTs.

Framework supports clearer interpretation and regulatory decisions.

Abstract

Randomized discontinuation design (RDD) is an enrichment strategy commonly used to address limitations of traditional placebo-controlled trials, particularly the ethical concern of prolonged placebo exposure. RDD consists of two phases: an initial open-label phase in which all eligible patients receive the investigational medicinal product (IMP), followed by a double-blind phase in which responders are randomized to continue with the IMP or switch to placebo. This design tests whether the IMP provides benefit beyond the placebo effect. The estimand framework introduced in ICH E9(R1) strengthens the dialogue among clinical research stakeholders by clarifying trial objectives and aligning them with appropriate statistical analyses. However, its application in oncology trials using RDD remains unclear. This manuscript uses the phase III JAVELIN Gastric 100 trial and the phase II trial of sorafenib (BAY 43-9006) as case studies to propose an estimand framework tailored for oncology trials employing RDD in phase III and phase II settings, respectively. We highlight some similarities and differences between RDDs and traditional randomized controlled trials in the context of ICH E9(R1). This approach aims to support more efficient regulatory decision-making.