  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 a
real clinical trial. 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.

Methodology