# Integrating Phase 2 into Phase 3 based on an Intermediate Endpoint While Accounting for a Cure Proportion -- with an Application to the Design of a Clinical Trial in Acute Myeloid Leukemia

## TL;DR

This paper introduces a novel statistical approach for integrating Phase 2 and Phase 3 clinical trial stages using an intermediate endpoint, especially for treatments with potential curative effects, demonstrated through an AML trial case study.

## Contribution

It proposes a new method combining cure proportion models with interim analysis strategies to optimize trial design and decision-making in oncology studies.

## Key findings

- Simulation-based planning improves trial efficiency.
- Intermediate endpoints can inform futility decisions.
- Application to AML trial demonstrates practical utility.

## Abstract

For a trial with primary endpoint overall survival for a molecule with curative potential, statistical methods that rely on the proportional hazards assumption may underestimate the power and the time to final analysis. We show how a cure proportion model can be used to get the necessary number of events and appropriate timing via simulation. If Phase 1 results for the new drug are exceptional and/or the medical need in the target population is high, a Phase 3 trial might be initiated after Phase 1. Building in a futility interim analysis into such a pivotal trial may mitigate the uncertainty of moving directly to Phase 3. However, if cure is possible, overall survival might not be mature enough at the interim to support a futility decision. We propose to base this decision on an intermediate endpoint that is sufficiently associated with survival. Planning for such an interim can be interpreted as making a randomized Phase 2 trial a part of the pivotal trial: if stopped at the interim, the trial data would be analyzed and a decision on a subsequent Phase 3 trial would be made. If the trial continues at the interim then the Phase 3 trial is already underway. To select a futility boundary, a mechanistic simulation model that connects the intermediate endpoint and survival is proposed. We illustrate how this approach was used to design a pivotal randomized trial in acute myeloid leukemia, discuss historical data that informed the simulation model, and operational challenges when implementing it.