Estimating Treatment Effects with a Single Arm Clinical Trial and Data Summaries from an External Control Group: is it Possible?

Abstract

Randomized controlled trials are crucial for assessing new treatments, but they are often infeasible due to ethical or practical constraints. In these cases, single-arm trials combined with external control data constitute an alternative approach for estimating treatment effects. However, individual patient-level data on external controls are frequently inaccessible due to privacy and economic concerns. Therefore, investigators rely on data summaries published by previous studies of the control therapy. We propose a method for inference on the treatment effect of an experimental therapy using patient-level data from a single-arm trial and a few published data summaries from an external control group. We introduce and study the Interval of Potential Effects (IPE), described as the range of plausible levels of the treatment effect that are compatible with the patient-level data from the experimental treatment and the available summaries on the control group. The width of the IPE quantifies the uncertainty on the treatment effect attributable to the lack of individual patient data from the control group. We demonstrate, through simulations and a case study, how the IPE indicates whether the available summaries are sufficient for accurate estimation of the treatment effect. We also illustrate that IPEs can support decision-making in the early phases of development of new treatments.