Are adaptive randomised trials or non-randomised studies the best way to address the Ebola outbreak in west Africa?

Abstract

The Ebola outbreak that has devastated parts of west Africa represents an unprecedented challenge for research and ethics. Estimates from the past three decades emphasise that the present effort to contain the epidemic in the three most affected countries (Guinea, Liberia, and Sierra Leone) has been insufficient, with more than 24,900 cases and about 10,300 deaths, as of March 25, 2015. Faced with such an exceptional event and the urgent response it demands, the use of randomised controlled trials (RCT) for Ebola-related research might be both unethical and infeasible and that potential interventions should be assessed in non-randomised studies on the basis of compassionate use. However, non-randomised studies might not yield valid conclusions, leading to large residual uncertainty about how to interpret the results, and can also waste scarce intervention-related resources, making them profoundly unethical. Scientifically sound and rigorous study designs, such as adaptive RCTs, could provide the best way to reduce the time needed to develop new interventions and to obtain valid results on their efficacy and safety while preserving the application of ethical precepts. We present an overview of clinical studies registered at present at the four main international trial registries and provide a simulation on how adaptive RCTs can behave in this context, when mortality varies simultaneously in either the control or the experimental group.

Figure 1

Flowchart for selection of clinical trials enrolling patients with acute Ebola virus disease to assess efficacy or safety, or both, of new interventions Records or trial to be selected (green boxes); excluded records or trials (orange boxes); analysed trials (blue boxes). EUDRA=European Union Drug Regulatory Authorities. PACTR=Pan African Clinical Trial Registry. ICTRP=International Clinical Trials Registry Platform (WHO).

Figure 2

Trial simulation to estimate probability of early stopping (A) Early stopping estimate at the first interim analysis (overall sample size=70). (B) Early stopping estimate at the second interim analysis (overall sample size=140). *Punctual estimate for early stopping if reported mortality in control group is equal to 10% (ie, extraordinary unexpected efficacy). †Punctual estimate for early stopping if reported mortality is equal to the a priori assumptions.