Improving efficiency of inference in clinical trials with external control data

TL;DR

This paper introduces a method to improve the efficiency of estimating treatment effects in clinical trials by leveraging external control data, especially when the trial has limited sample size, using a doubly robust and locally efficient estimator.

Contribution

It proposes a novel approach that combines trial data with external controls under an exchangeability assumption, reducing the semiparametric efficiency bound and allowing for relaxed overlap conditions.

Findings

Efficiency gains are significant with large external datasets.

The method performs well in finite samples as shown by simulations.

Application suggests potential efficacy advantages of the combination treatment.

Abstract

Suppose we are interested in the effect of a treatment in a clinical trial. The efficiency of inference may be limited due to small sample size. However, external control data are often available from historical studies. Motivated by an application to Helicobacter pylori infection, we show how to borrow strength from such data to improve efficiency of inference in the clinical trial. Under an exchangeability assumption about the potential outcome mean, we show that the semiparametric efficiency bound for estimating the average treatment effect can be reduced by incorporating both the clinical trial data and external controls. We then derive a doubly robust and locally efficient estimator. The improvement in efficiency is prominent especially when the external control dataset has a large sample size and small variability. Our method allows for a relaxed overlap assumption, and we illustrate with the case where the clinical trial only contains a treated group. We also develop doubly robust and locally efficient approaches that extrapolate the causal effect in the clinical trial to the external population and the overall population. Our results also offer a meaningful implication for trial design and data collection. We evaluate the finite-sample performance of the proposed estimators via simulation. In the Helicobacter pylori infection application, our approach shows that the combination treatment has potential efficacy advantages over the triple therapy.