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Table 5 Virtual re-execution of shortlisted designs using bootstrapped ANZ 9311 data

From: Improving clinical trials using Bayesian adaptive designs: a breast cancer example

Design

Duration (months), mean (SD)

Sample size, mean (SD)

Probability of success (%)

Probability of inconclusive (%)

Hazard ratio, median (IQR)

Fixed

76.7 (3.93)

233 (0.0)

0.13

1.16 (1.06, 1.28)

Small sample size

  Posterior

55.2 (32.3)

164 (51.3)

0.10

15.7

1.27 (1.15, 1.43)

  PPS

36.9 (13.1)

134 (51.8)

0.13

0.05

1.32 (1.10, 1.62)

  CPS

42.3 (9.7)

154 (28.9)

0.07

0.09

1.15 (1.03, 1.36)

  Goldilocks

36.9 (13.1)

134 (51.8)

0.14

0.05

1.32 (1.10, 1.62)

  PPBS

41.0 (5.6)

152 (26.6)

0.12

0.00

1.15 (1.02, 1.36)

High power

  Posterior

88.1 (35.4)

214 (32.5)

0.10

48.5

1.22 (1.07, 1.43)

  PPS

53.6 (9.2)

218 (14.6)

0.06

0.10

1.17 (1.07, 1.33)

  CPS

52.0 (8.1)

213 (15.1)

0.05

0.09

1.17 (1.03, 1.33)

  Goldilocks

53.5 (9.2)

218 (14.6)

0.06

0.09

1.17 (1.07, 1.33)

  PPBS

50.9 (4.5)

214 (15.1)

0.18

0.00

1.17 (1.03, 1.33)

  1. PPS Predictive probability of success, CPS Conditional probability of success, PPBS Predictive probability of Bayesian success. The median and interquartile range (IQR) of the distribution of 100,000 bootstrapped hazard ratios are shown, unadjusted for any adaptations, for illustrative purposes only