A biomarker-guided Bayesian response-adaptive phase II trial for metastatic melanoma: The Personalized Immunotherapy Platform (PIP) trial design.

Abstract

TPS9599 Background: Anti-PD1-based immunotherapies have been approved for many cancer types and are now a standard therapy for advanced melanoma. Despite this, ̃50% of advanced melanoma patients (pts) fail to respond or eventually progress after response. It is therefore critical to identify pts with a low likelihood of response to anti-PD1-based therapy and efficiently assess activity of rationally-selected alternative novel immunotherapies. Methods: We designed this investigator-initiated phase II PIP-Trial to evaluate two consecutive biomarker testing platforms, followed by the activity of rationally selected 5 novel agents in pts with advanced melanoma. Two separate pt populations are included: Part-A) treatment-naïve pts predicted to be resistant to either anti-PD-1 alone or combined with ipilimumab using Biomarker Test-1); and Part-B) pts who had progressed on 1 prior line of PD1-based therapy. Part-A) is a Bayesian adaptive multi-arm multi-stage design using response adaptive randomisation after a burn-in period where pts are randomised to the existing arms with equal probability. From then on, regular interim analyses will be carried out with the objective to either drop poorly performing arms or continue. Part-B) is an open platform without control that combined a selection and an expansion phase to identify best novel agent(s) as second-line therapy. Expansion phase decisions will be based on enrichment for biomarker Test-2. Dropping an arm occurs when the posterior probability of observing a clinically significant effect on the primary outcome (i.e. 6-month RECIST objective response rate (ORR)) is low. The operational characteristics of the design were investigated through simulations considering 4 plausible scenarios with 40% ORR in the control arm (anti-PD1 + Anti-CTLA4). Simulations were based on the upcoming R package BATS. Part-A has at least 85% power to detect a 30% absolute improvement in ORR with respect to the control arm (with a max N = 216 – Table below). Part-B will be able to select two promising treatments in the expansion phase and formally test their efficacy against a minimum ORR of 25% at 80% power (max N = 150). [Table: see text]