Each week, we will be publishing layman’s abstracts of new articles from our prestigious portfolio of journals in statistics. The aim is to highlight the latest research to a broader audience in an accessible format.
A pragmatic adaptive enrichment design for selecting the right target population for cancer immunotherapies. Pharmaceutical Statistics. 2020; 1– 10. https://doi.org/10.1002/pst.2066, , , .
The scientific understanding of disease biology and corresponding treatment options is evolving during the course of drug development. This article presents a case-study of a clinical trial in cancer immunotherapy which was originally designed to demonstrate the benefit of an investigational drug in all subjects with the disease. However, while the trial was ongoing, insights from data external to the trial emerged which suggested that the drug may only benefit a subset of subjects which can be identified by a biomarker. This uncertainty regarding the appropriate target population was incorporated in the ongoing trial by amending its design to an adaptive enrichment design (AED). An AED proceeds in two stages. In the first stage, all subjects with the disease are included. A mid-trial analysis of the first stage data is then conducted to decide whether the information is already sufficient to demonstrate a benefit of the novel group in all subjects or in the biomarker subgroup or whether stage 2 of the trial needs to be initiated. Moreover, the design allows for a population selection after stage 1, i.e. depending on stage 1 results, all subjects with the disease or only biomarker positive subjects, respectively, will be included in stage 2. Importantly, as described by the authors, a properly planned and conducted AED allows for such mid-trial decision making without compromising the scientific integrity and validity of the trial.
This work demonstrates that AEDs are an efficient way to circumvent emerging uncertainties about the target population for cancer immunotherapy. To date AEDs are still relatively rare in clinical development. This paper serves to promote the use of AEDs and increase the confidence that such designs are feasible in practice. AEDs can support personalized health care such that one can identify the right patients, those who benefit most from a treatment. At the same time, AEDs can make drug development more efficient through reliable mid-trial decision making to concentrate resources on the most promising therapies.