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. 2020 Nov 10;4(21):5433-5441.
doi: 10.1182/bloodadvances.2020002789.

The design of a Bayesian platform trial to prevent and eradicate inhibitors in patients with hemophilia

Marnie Bertolet  1   2 , Maria M Brooks  1   2 , Margaret V Ragni  3   4
Affiliations

The design of a Bayesian platform trial to prevent and eradicate inhibitors in patients with hemophilia

Marnie Bertolet et al. Blood Adv. .

Abstract

Among individuals with the rare congenital bleeding disorder hemophilia A, the major challenge is inhibitor formation, which is associated with significant morbidity and cost. Yet, as the optimal approach to prevent and eradicate inhibitors is not known, we are at equipoise. Because classic trial design is not practical in a rare disease setting, we designed 2 48-week randomized trials comparing ELOCTATE and emicizumab to prevent and eradicate inhibitors. To achieve statistical efficiency, we incorporated historic data (Bayesian priors) on inhibitor formation to allow preferential randomization to emicizumab, piecewise exponential survival models to determine mean and 95% confidence interval for inhibitor formation in each arm, and simulations to determine the best model design to optimize power. To achieve administrative efficiency, the trials will be performed with the same sites, staff, visit frequency, blood sampling, laboratories, and laboratory assays, with streamlined enrollment so patients developing inhibitors in the first trial may be enrolled on the second trial. The primary end point is the probability of inhibitor formation or inhibitor eradication, respectively. The design indicates early stopping rules for overwhelming evidence of superiority of the emicizumab arms. Simulations indicate that, with 66 subjects, the Prevention Trial will have 84% power to detect noninferiority of emicizumab to ELOCTATE with a margin of 10% if emicizumab is truly 10% superior to ELOCTATE; with 90 subjects, the Eradication Trial will have 80% power to detect 15% superiority of ELOCTATE immune tolerance induction with vs without emicizumab. Thus, a platform design provides statistical and administrative efficiency to conduct INHIBIT trials.

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Conflict of interest statement

Conflict-of-interest disclosure: M.M.B. is a member of a Data and Safety Monitoring Board for Cerus Corporation. M.V.R. has received research funding from Alnylam Pharmaceuticals, BioMarin, Bioverativ, Sangamo Therapeutics, Spark Therapeutics, and Takeda Pharmaceutical and has served on advisory boards for Alnylam Pharmaceuticals, BioMarin, Bioverativ, and Spark Therapeutics. M.B. declares no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
INHIBIT trials Bayesian platform design. Proposed schema for the INHIBIT Trials Platform, which links 2 phase 3 randomized trials to prevent and eradicate inhibitors in individuals with hemophilia: the Inhibitor Prevention Trial and the Inhibitor Eradication Trial. BU, Bethesda units; HA, hemophilia A; HA-I, hemophilia A with inhibitors; HTC, hemophilia treatment center; PTP, previously treated patient.
Figure 2.
Figure 2.
Clinical trial 1: Inhibitor Prevention Trial schema. Schema for the Inhibitor Prevention Trial, in which ELOCTATE prophylaxis is compared with emicizumab prophylaxis to reduce inhibitor formation in PUPs with severe hemophilia A. The sample size indicates 1:3 preferential randomization of ELOCTATE/emicizumab, as a result of the incorporation of subjects on the ELOCTATE arm, borrowed from the Bayesian prior (supplemental Methods).
Figure 3.
Figure 3.
Clinical Trial 2: Inhibitor Eradication Trial schema. Schema for the Inhibitor Eradication Trial, in which ELOCTATE ITI combined with emicizumab prophylaxis is compared with ELOCTATE ITI alone to eradicate inhibitor in PTPs with severe hemophilia A and an inhibitor.
Figure 4.
Figure 4.
Inhibitor Prevention Trial: power for noninferiority across all design and hypothesis scenarios. The power for a test of noninferiority, assuming various randomization allocation ratios and degrees of “borrowing” for the prior (design scenarios) to determine the power associated with various effect sizes.
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References

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