Estimands for Randomized Discontinuation Designs in Oncology

The Randomized Discontinuation Design (RDD) is a two-stage adaptive enrichment design that is uniquely suited to answer causal questions about the benefit of continuing treatment in patients who have already demonstrated response to an induction therapy. The estimand framework from the International Council for Harmonisation (ICH) E9(R1) addendum provides the necessary language to precisely define this scientific question. A major challenge in formulating estimands for RDD oncology trials is that the target population for the primary scientific question is itself defined by a post-treatment biological outcome in Stage 1, which makes it difficult to separate the process of selecting eligible participants from the causal inference problem in Stage 2. In this paper, we address this challenge using the Phase III JAVELIN Gastric 100 trial as an example. We argue that the "conventional" estimand can be formulated as an estimand targeting the response-defined subgroup of participants with evidence of response to the induction therapy in Stage 1, and we clarify the precise sense in which this subgroup is, and is not, related to the concept of a principal stratum. We also formulate a "full-path" estimand-capturing the patients' entire two-stage treatment journey-and connect it to the dynamic treatment regime literature. We also provide Directed Acyclic Graphs (DAGs) for the two estimands to clarify their respective causal structures. This paper aims to strengthen the dialogue among clinical research stakeholders tasked with the design and analysis of RDD trials and support more efficient regulatory decision-making. Trial Registration: ClinicalTrials.gov identifier: NCT02625610.