  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.
