Abstract 1372: Model based approach to evaluate Isatuximab (Isa) monthly dosing regimen in relapsed/refractory multiple myeloma (RRMM)

Introduction: Isa is a CD38 monoclonal antibody with multiple modes of action for killing tumor cells. Isa, in combination with pomalidomide and dexamethasone (Pd), is approved for the treatment of adult pts with RRMM who have received ≥2 prior therapies including lenalidomide and a proteasome inhibitor. This study characterized the relationship between serum M-protein kinetics and progression free survival (PFS) in RRMM pts from the Phase 3 ICARIA-MM study, and simulated expected PFS outcomes when switching to a hypothetical monthly Isa dosing regimen after 6 months.

Methods: A joint model of serum M-protein dynamics and PFS was developed using data from 256 pts. Pts received Isa intravenously, 10 mg/kg once weekly (QW) for 4 weeks (wks), then every other wk (Q2W) for 28-day cycles plus standard Pd (Isa-Pd) or Pd alone (control). A tumor growth inhibition model described serum M-protein kinetics under treatment effects of Isa-Pd or Pd alone; Isa exposure was predicted using individual PK parameters from the population PK analysis (Fau, PAGE Congress, 2019) and Pd exposure was predicted from K-PD model using dosing history. Trial simulations were performed using individual PK/PD parameters of ICARIA-MM pts.

Results: The joint model identified instantaneous changes (slope) in serum M-protein as the best on-treatment predictor for PFS and identified baseline pt characteristics impacting serum M-protein kinetics (serum albumin and serum β2 microglobulin on the baseline serum M-protein levels and the non-IgG type on the serum M-protein growth rate, the serum M-protein slope) and PFS (presence of plasmacytomas). Non-IgG MM pts have similar behavior on serum M-protein kinetics for the first 60 wks even with higher exposure and similar PFS vs IgG MM pts supporting non-dose adjustment based on IgG status. Clinical trial simulation of the Isa-Pd regimen showed that switching pts on treatment at 6 months to a monthly Isa regimen would shorten the median time to progression (TTP) by 4.1 wks and median PFS by 2.3 wks (14.03 to 13.45 months). Based on TTP criteria, pts with no risk of earlier progression while switching to a monthly Isa regimen (57.7%) tend to have lower baseline tumor burden (lower serum M-protein and lower percent of bone marrow plasma cell) and better prognostic factors (higher glomerular filtration rate, higher albumin, lower β2 microglobulin). At 6 months, 85% of these pts had predicted stable ≥VGPR status.

Conclusions: Trial simulations support the approved Isa 10 mg/kg QW/Q2W regimen and show that switching to a monthly Isa regimen after 6 months may reduce clinical benefit in the overall population. However, some pts with good prognosis (low tumor burden, low ISS stage, good renal function) and obtaining stable ≥VGPR status by 6 months may switch to a monthly regimen after 6 months without compromising disease progression risk; this hypothesis will be tested in a prospective clinical trial.

Citation Format: Hoai-Thu Thai, Nadia Gaudel-Dedieu, Marc Cerou, Bernard Sebastien, Helgi van de Velde, Dorothee Semiond, Christine Veyrat-Follet. Model based approach to evaluate Isatuximab (Isa) monthly dosing regimen in relapsed/refractory multiple myeloma (RRMM) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1372.

Matching-adjusted indirect comparisons: Application to time-to-event data

The Matching-Adjusted Indirect Comparison method (MAIC) is a recent methodology that allows to perform indirect comparisons between two drugs assessed in two different studies, where individual patients data are available in only one of the two studies, the data of the other one being available in an aggregate format only. In this work, we have assessed the properties of the MAIC method and compared, through simulations, several ways of practical implementation of the method. We conclude that it is more efficient to match the treatment arms separately (match the two drugs to compare on one hand, and the control arms on the other hand) and use the Lasso technique to select the covariates for the matching step is better than matching a maximal set of covariates.