First-Line Use of Daratumumab, Lenalidomide, and Dexamethasone Confers Survival Benefit Compared with Second-Line Use of Daratumumab-Based Regimens in Transplant-Ineligible Patients with Multiple Myeloma: Analysis of Different Clinical Scenarios
Authors: Fonseca Rafael , Facon Thierry , Hashim Mahmoud , Nair Sandhya , He Jianming , Ammann Eric M. , Lam Annette , Wildgust Mark , Kumar Shaji 
Published: November 2021

Abstract
Introduction: Despite recent treatment (tx) advances that have improved overall survival (OS), multiple myeloma (MM) remains a mostly incurable malignancy. Txs become less effective with each successive line of therapy (LOT). The rapidly evolving tx landscape has raised questions about the optimal tx sequence; recent trial data may be useful to develop and test hypotheses about tx sequencing. However, real-world (RW) data have shown that while most patients (pts) with newly diagnosed MM (NDMM) receive first-line (1L) tx, attrition rates are high in later LOT, with up to 50% of transplant ineligible (TIE) pts receiving no tx beyond 1L. As many pts will not have an opportunity to be salvaged with later LOT, achieving the longest possible progression-free survival (PFS) upfront is critical. In the MAIA trial, daratumumab (DARA), lenalidomide, and dexamethasone (D-Rd) demonstrated significant PFS (hazard ratio [HR]=0.53, P&lt;0.0001) and OS (HR=0.68, P=0.0013) benefit vs Rd. In a subgroup of pts ≥65 years old in the SWOG S0777 study, bortezomib, lenalidomide, and dexamethasone (VRd) had no significant OS benefit vs Rd. In the absence of head-to-head studies comparing different tx sequences, clinical trial data can be used to explore different scenarios. Published models suggest that delaying DARA until later LOT is a viable tx strategy. Limitations of these models include basing conclusions on tx sequences other than those recommended in clinical guidelines, not accounting for the attrition rates from 1L to subsequent LOT and relying on inappropriate clinical inputs for second-line (2L) tx and beyond. While addressing those limitations, we examined different clinical scenarios to explore the clinical value of using DARA first vs saving it until a later LOT.
Methods: We examined 3 potential clinical tx sequences using a lifetime three-health state clinical simulation to estimate survival outcomes in pts with TIE NDMM. The 3 health states were: 1L (time on tx + any subsequent tx-free interval), 2L (time on 2L + any subsequent LOT), and death. Tx sequences were reflective of clinical guidelines: D-Rd in 1L followed by pomalidomide (POM)- or carfilzomib (CAR)-based regimens in 2L and VRd or Rd in 1L followed by DARA-based regimens in 2L (Figure). Pt characteristics were assumed to be similar to those of pts in MAIA. Time spent in the 1L health state with D-Rd and Rd was based on time to next tx or death (TTNT) curves derived from MAIA; TTNT curves with VRd were derived by applying PFS HRs estimated in the PEGASUS study. The attrition rate for the base case analysis (58.8%) was based on MAIA data. Although similar to published studies, it includes pts who were lost to follow-up and may be an overestimate. A sensitivity analysis evaluated a more conservative estimate (27.2%) excluding censored pts. Attrition rates were assumed to be the same across tx arms. Time spent in the 2L health state with DARA-based and POM- or CAR-based regimens was based on RW OS curves derived from the nationwide EHR-derived deidentified Flatiron Health database. RW data were used as pts in published 2L trials are younger than in MAIA and many have had prior ASCT. We evaluated median OS and 5- and 10-year survival rates.
Results: Using D-Rd in 1L improved median OS by 2.5 or 3.5 years compared with delaying DARA-based regimens until 2L after VRd or Rd, respectively (Table). The probability of being alive at 5 and 10 years was higher with D-Rd than with VRd or Rd as initial therapy (Table). Changes in attrition rates impacted the expected median OS, but the absolute difference in median OS was maintained, with an incremental OS benefit consistently &gt;2 years.
Conclusions: Unlike previous attempts to examine outcomes with different tx sequences, we incorporated clinically representative sequences for pts with NDMM, included attrition rates, and explored their impact on OS with different tx sequences. Our approach shows that achieving the longest possible PFS in 1L drives OS outcomes. Saving agents until later LOT does not take into account that many pts do not reach 2L, as evidenced by published data on attrition rates in MM. Our findings show that in pts with TIE NDMM, starting with D-Rd may provide up to 3.5 years of additional OS gain with the currently available 2L tx. This gain could increase with new 2L agents currently in development, reinforcing the importance of using the best agents first, to increase the probability of pts benefitting from tx currently in development.
Figure 1 Figure 1.

Disclosures
Fonseca: Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy; Janssen: Consultancy; GSK: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aduro: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; AbbVie: Consultancy; Mayo Clinic in Arizona: Current Employment; BMS: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Bayer: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Juno: Consultancy; Takeda: Consultancy; Merck: Consultancy. Hashim: Johnson and Johnson: Current Employment. Nair: Janssen Research & Development: Current Employment. He: Janssen: Current Employment, Current equity holder in publicly-traded company. Ammann: Janssen: Current Employment, Current equity holder in publicly-traded company. Lam: Janssen: Current Employment, Current equity holder in publicly-traded company. Wildgust: Janssen: Current Employment, Current equity holder in publicly-traded company. Kumar: Beigene: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Amgen: Consultancy, Research Funding; Antengene: Consultancy, Honoraria; Roche-Genentech: Consultancy, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Bluebird Bio: Consultancy; BMS: Consultancy, Research Funding; Carsgen: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.