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Table 4 Virtual re-execution of shortlisted designs using real-world ANZ 9311 data

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

Design

Trial conclusion

Duration (months)

Sample size

Hazard ratio (95% CI)

Original trial

H0 not rejected

53.0 recruitment + 91.2 follow-up

235

1.17 (0.90, 1.52)

Small sample size

  Posterior

Early futility

69.9

233

1.14 (0.85, 1.52)

  PPS

Early futility

50.6

214

1.03 (0.71, 1.48)

  CPS

Early futility

43.2

164

1.00 (0.66, 1.52)

  Goldilocks

Early futility

50.6

214

1.03 (0.71, 1.48)

  PPBS

Early futility

42.3

158

0.98 (0.64, 1.50)

High power

  Posterior

Inconclusive

120.5

233

1.17 (0.90, 1.53)

  PPS

Early futility

52.4

228

1.10 (0.77, 1.58)

  CPS

Early futility

47.8

189

1.00 (0.68, 1.47)

  Goldilocks

Early futility

52.4

228

1.10 (0.77, 1.58)

  PPBS

Early futility

47.8

189

1.00 (0.68, 1.47)

  1. PPS Predictive probability of success, CPS Conditional probability of success, PPBS Predictive probability of Bayesian success. The hazard ratios and 95% confidence intervals (CI) are the estimates from the Cox proportional-hazards model, unadjusted for any adaptations, for illustrative purposes only