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Table 2 Description of the simulated scenarios when K=3 biomarker subsets (k=A,B,C)

From: Enrichment Bayesian design for randomized clinical trials using categorical biomarkers and a binary outcome

Scenarios

Subset A

Subset B

Subset C

Theoretical Values

Outcomes

p1A

p0A

p1B

p0B

p1C

p0C

θA

θB

θC

RR

Scenario 1

0.40

0.40

0.40

0.40

0.40

0.40

1.000

1.000

1.000

1.000

Scenario 2

0.32

0.40

0.32

0.40

0.32

0.40

0.800

0.800

0.800

0.800

Scenario 3

0.40

0.40

0.40

0.40

0.20

0.50

1.000

1.000

0.400

0.769

Scenario 4

0.40

0.40

0.24

0.40

0.24

0.40

1.000

0.600

0.600

0.733

Scenario 5

0.40

0.40

0.24

0.40

0.20

0.50

1.000

0.600

0.400

0.646

Scenario 6

0.40

0.40

0.24

0.40

0.50

0.40

1.000

0.600

1.250

0.925

Scenario 7

0.40

0.40

0.20

0.50

0.50

0.40

1.000

0.400

1.250

0.846

  1. Here, pjk denotes the probability of death in the arm j in the subset k, and θk denotes the relative risk of death in the experimental versus the control arm in subset k. RR refers to the overall treatment effect.