# Great Wall: A Generalized Dose Optimization Design for Drug Combination Trials Maximizing Survival Benefit

**Authors:** Yan Han, Yingjie Qiu, Yi Zhao, Isabella Wan, Lang Li, Suyu Liu, Yong Zang

PMC · DOI: 10.1002/pst.70049 · Pharmaceutical Statistics · 2025-11-12

## TL;DR

The Great Wall design is a new method for drug combination trials that aims to maximize long-term survival benefits by optimizing dose combinations based on toxicity and early efficacy.

## Contribution

The Great Wall design introduces a modular dose optimization approach that addresses partial order toxicity and balances early efficacy with long-term survival outcomes.

## Key findings

- The Great Wall design uses a divide-and-conquer algorithm to handle partial order toxicity and eliminate suboptimal dose combinations.
- Simulation studies show the design has desirable operating characteristics across various clinical settings.
- The design is modular and practical for trials where long-term survival outcomes are assessed.

## Abstract

Most phase I–II drug‐combination trial designs assume that selecting the optimal dose combination based on early outcomes will also lead to maximum long‐term survival benefits. However, this assumption is often violated in many clinical studies, generally due to high rates of relapse following the initial response. To address this problem, we propose the Great Wall design, a general dose optimization design for drug‐combination trials. The Great Wall design employs a “divide‐and‐conquer” algorithm to address the issue of partial order of toxicity and uses early outcomes to eliminate dose combinations that are excessively toxic or less efficacious. It utilizes a dose randomization approach to construct a candidate set of the promising dose combinations balancing the toxicity and early efficacy outcomes. The patients assigned to the candidate set are followed to collect the survival outcomes and the final optimal dose combination is then selected to maximize the survival benefit. The simulation studies confirm the desirable operating characteristics of the Great Wall design under various clinical settings. R codes are also provided to facilitate the application. The Great Wall design is modular and practically useful in settings where investigators plan to follow patients long enough to assess survival outcomes.

## Full-text entities

- **Diseases:** toxic (MESH:D064420)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

31 references — full list in the complete paper: https://tomesphere.com/paper/PMC12606548/full.md

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Source: https://tomesphere.com/paper/PMC12606548