AML-142 Patients at High Risk of Relapse Post-Transplant: A Phase 1 Study Design With a Novel Treatment Strategy Using the Estimand Framework

Context: The risk of disease relapse in patients allografted for acute myeloid leukemia (AML) is high and remains the main cause of transplant failure. A potent graft-versus-leukemia (GvL) effect is exerted post–stem cell transplantation (SCT); strategies that may augment a GvL effect have the potential to reduce relapse risk post SCT. Siremadlin/HDM201 is a novel investigational MDM2 inhibitor with single-agent (SA) anti-AML activity. MDM2 inhibitors possess potent immunomodulatory effects (IME) in murine solid tumor and AML models. The post–allogeneic SCT setting is ideal for investigating IME of MDM2 inhibition on the GvL effect. Objective: To present a study design assessing the safety and preliminary efficacy of treatment with monotherapy siremadlin and in combination with donor lymphocyte infusions (DLIs) for AML post SCT using the estimand framework (ICH E9 [R1] addendum). Design: Phase Ib/II proof-of-concept. Patients: AML patients in CR post SCT at high risk for relapse based on pre-SCT risk factors. Interventions: The estimand framework mandates definition of experimental intervention according to the clinical question. Due to the risk of GvHD with DLI early post SCT, siremadlin will first be given to eligible patients as priming monotherapy to prevent early relapse; patients who tolerate siremadlin with no evidence of GvHD are eligible to start siremadlin/DLI. Post combination, patients may continue maintenance SA siremadlin, which intends to prolong/enhance the GvL reaction to eradicate residual leukemic blasts. According to their treatment journey, patients may receive only part of the intervention's sequence (e.g., siremadlin priming monotherapy patients not eligible for DLI combination will continue priming). Main Outcome Measures: To determine 1) the siremadlin recommended dose (RD) across all parts of the treatment strategy and 2) preliminary efficacy regardless of the treatment parts received. Siremadlin RD will be determined using a Bayesian logistic regression model to guide dose finding of siremadlin during priming/Cycle 1 and a Bayesian time-to-DLT model to assess the siremadlin combination dose. Efficacy will be assessed by the proportion of patients remaining in CR ≥6 months. Summary: The estimand framework guided the design of an AML clinical study post SCT to conceptualize the assessment of safety and efficacy of the treatment strategy, accounting for different patient journeys.