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. 2022 Aug 2;27(10):834–843. doi: 10.1111/resp.14337

TABLE 3.

Operating characteristics for the Bayesian adaptive design case study

Scenario Proportion of simulations CPAP declared superior to control Proportion of simulations NIPPV declared superior to control Proportion of simulations where at least one intervention is declared superior to control a Proportion of simulations stopped early for success Proportion of simulations stopped early for futility Average total sample size (SD) Average allocations, number of patients (SD)
Control CPAP NIPPV
(1) Null 0.0133 0.0144 0.0258 0.0155 0.3925 1356 (202) 515 (92) 421 (123) 421 (123)
(2) One intervention superior 0.0108 0.8897 0.8901 0.7470 0.0018 1126 (273) 458 (126) 211 (59) 458 (127)
(3) Both interventions superior 0.6710 0.6745 0.9260 0.8193 0.0004 1064 (269) 391 (106) 336 (105) 337 (106)
(4) NIPPV > CPAP > Control 0.1700 0.8274 0.8604 0.7166 0.0019 1140 (278) 436 (115) 285 (102) 421 (115)
(5) Both interventions have small improvement 0.2559 0.2519 0.4314 0.2821 0.0267 1370 (221) 517 (93) 427 (122) 427 (123)
(6) Harm 0.0005 0.0017 0.0021 0.0012 0.7319 1197 (242) 451 (107) 373 (117) 374 (117)

Note: These results are based on 10,000 simulated trials for each scenario. We assume a mean recruitment rate of 6.5 patients/week and that it took 6 months to reach that rate. It was assumed there would be no dropouts.

Abbreviations: CPAP, continuous positive‐pressure ventilation; NIPPV, non‐invasive intermittent positive‐pressure ventilation.

a

Proportion of simulated trials that declared the trial to be ‘successful’, that is, at least one arm superior to the control at the final analysis (includes trials that stopped early and those that recruited to the maximum sample size). The simulated type I error is italicized.