Critical concepts in adaptive clinical trials

Abstract

Adaptive clinical trials are an innovative trial design aimed at reducing resources, decreasing time to completion and number of patients exposed to inferior interventions, and improving the likelihood of detecting treatment effects. The last decade has seen an increasing use of adaptive designs, particularly in drug development. They frequently differ importantly from conventional clinical trials as they allow modifications to key trial design components during the trial, as data is being collected, using preplanned decision rules. Adaptive designs have increased likelihood of complexity and also potential bias, so it is important to understand the common types of adaptive designs. Many clinicians and investigators may be unfamiliar with the design considerations for adaptive designs. Given their complexities, adaptive trials require an understanding of design features and sources of bias. Herein, we introduce some common adaptive design elements and biases and specifically address response adaptive randomization, sample size reassessment, Bayesian methods for adaptive trials, seamless trials, and adaptive enrichment using real examples.

Keywords: Bayesian adaptive trials; adaptive designs; adaptive enrichment; response adaptive randomization; sample size reassessment; seamless trials.

Figure 1

Response adaptive randomization. Notes: The first interim analysis shows serious toxicity for the high-dose arm and promising results for the medium dose. The RAR design allows the allocation ratio to be changed to zero for the high-dose arm after the first interim analysis, so that patients will no longer be enrolled to this treatment. The allocation ratio for the medium dose, on the other hand, can be increased allowing more patients to be enrolled to this arm. Then, the trial stops after the medium dose demonstrates superiority over the low-dose arm. This example shows how an RAR design can potentially allow for a larger number of patients to be allocated to the superior treatment. Abbreviation: RAR, response adaptive randomization.

Figure 2

Sample size reassessment. Notes: If the first interim analysis shows worse results than expected, an SSR can be performed using the interim results. SSR is not permitted in a traditional nonadaptive trial, so even when the original planned sample size is reached, the trial may be underpowered (Option 1). If SSR is permitted, the enrolment target could be increased to ensure that the trial is adequately powered (Option 2). Abbreviation: SSR, sample size reassessment.

Figure 3

Seamless trials. Notes: After first interim analysis, the high-dose arm showing serious toxicity could be discontinued from the trial. Thereafter, the trial transitions seamlessly from the feasibility into the pivotal phase with standard therapy arm being introduced into the trial.

Figure 4

Trial with adaptive enrichment design with SSR. Notes: In this example, the first interim analysis shows the experimental intervention has more promising results on one subgroup of patients (illustrated in gray), but it is not shown to be effective for other patients. The study eligibility criteria could then be modified to investigate the efficacy of the intervention in the gray subgroup (i.e., an adaptive enrichment design) with an SSR ensuring a sufficient sample size for this subgroup. Abbreviation: SSR, sample size reassessment.