Cross-validated risk scores adaptive enrichment (CADEN) design

TL;DR

CADEN is a new adaptive trial design that enriches the population with patients likely to benefit, improving statistical power and reducing sample size compared to traditional methods.

Contribution

The paper introduces CADEN, an adaptive enrichment design using risk scores for patient selection, with an early stopping rule, demonstrated through simulations and real trials.

Findings

CADEN outperforms non-enrichment designs in power.

CADEN reduces expected sample size.

The method is implemented in an R package.

Abstract

We propose a Cross-validated ADaptive ENrichment design (CADEN) in which a trial population is enriched with a subpopulation of patients who are predicted to benefit from the treatment more than an average patient (the sensitive group). This subpopulation is found using a risk score constructed from the baseline (potentially high-dimensional) information about patients. The design incorporates an early stopping rule for futility. Simulation studies are used to assess the properties of CADEN against the original (non-enrichment) cross-validated risk scores (CVRS) design that constructs a risk score at the end of the trial. We show that when there exists a sensitive group of patients, CADEN achieves a higher power and a reduction in the expected sample size, in comparison to the CVRS design. We illustrate the application of the design in two real clinical trials. We conclude that the new design offers improved statistical efficiency in comparison to the existing non-enrichment method, as well as increased benefit to patients. The method has been implemented in an R package caden.