Background/aims: Fibrinolytic therapy with tenecteplase has been proposed for patients with pulmonary embolism but the optimal dose is unknown. Higher-than-necessary dosing is likely to cause excess bleeding. We designed an adaptive clinical trial to identify the minimum and assumed safest dose of tenecteplase that maintains efficacy.
Methods: We propose a Bayesian adaptive, placebo-controlled, group-sequential dose-finding trial using response-adaptive randomization to preferentially allocate subjects to the most promising doses, dual analyses strategies (continuous and dichotomized) using a gatekeeping approach to maximize clinical impact, and interim stopping rules to efficiently address competing trial objectives. The operating characteristics of the proposed design were evaluated using Monte Carlo simulation across multiple hypothetical efficacy scenarios.
Results: Simulation demonstrated response-adaptive randomization can preferentially allocate subjects to doses which appear to be performing well based on interim data. Interim decision-making, including the interim evaluation of both analysis strategies with gatekeeping, allows the trial to continue enrollment when success with the dichotomized analysis strategy appears sufficiently likely and to stop enrollment and declare superiority based on the continuous analysis strategy when there is little chance of ultimately declaring superiority with the dichotomized analysis.
Conclusion: The proposed design allows evaluation of a greater number of dose levels than would be possible with a non-adaptive design and avoids the need to choose either the continuous or the dichotomized analysis strategy for the primary endpoint.
Keywords: Bayes theorem; Pulmonary embolism; adaptive clinical trial; dose selection; statistical methods; thrombolysis.