Drug Efficacy Estimation for Follow‐on Companion Diagnostic Devices Through External Studies
A therapeutic product is usually not suitable for all patients but for only a subpopulation. The safe and effective use of such a therapeutic product requires the co-approval of a companion diagnostic device which can be used to identify suitable patients. While the first-of-a-kind companion diagnostic device is often developed in conjunction with its intended therapeutic product and simultaneously validated through a randomized clinical trial, there remains room for the innovation of new and improved follow-on companion diagnostic devices designed for the same therapeutic product. However, conducting a new randomized trial or a bridging study for the follow on companion devices may be unethical, expensive or unpractical. Hence, there arises a need for an external study to evaluate the concordance between the FDA-approved comparator companion diagnostic device (CCD) and the subsequent follow-on companion diagnostic devices (FCD), indirectly validating the latter. In this article, we introduce a novel external study design, referred to as the targeted treatment design, as an extension of the existing concordance design. Additionally, we present corresponding statistical analysis methods. Our approach combines the CCD randomized trial data and the FCD external study data, enabling the estimation of drug efficacy within the FCD+ and FCD- subpopulations-the parameters crucial for the validation of the FCD. Theoretical results and simulation studies validate the proposed methods and we further illustrate the proposed methods through an application in a real example of non-small-cell lung cancer.
Authors
- Xiao‐Hua Zhou (ORCID: https://orcid.org/0000-0001-7935-1222)
- Jiarui Sun (ORCID: https://orcid.org/0000-0002-3150-5269)
- Wenjie Hu (ORCID: https://orcid.org/0000-0002-8772-2705)
Institutions
- Peking University (CN)
- Peking University People's Hospital (CN)
- Peking University International Hospital (CN)
Publication Details
- Journal
- Statistics in Medicine
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1002/sim.10231
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Novo Nordisk