He, Jianming

Abstract Background Because patients with newly diagnosed multiple myeloma (NDMM) do not always receive any treatment beyond first-line (1L) therapy, it is imperative that patients receive the best treatment in the 1L setting. However, the optimal initial treatment remains to be identified. We performed a clinical simulation to assess potential outcomes with different treatment sequences. Patients and Methods We used a partitioned survival model to compare overall survival (OS) with (1) daratumumab, lenalidomide, and dexamethasone (D-Rd) in 1L followed by a pomalidomide- or carfilzomib-based regimen in second line (2L) versus (2) bortezomib, lenalidomide, and dexamethasone (VRd) in 1L followed by a daratumumab-based regimen in 2L versus (3) lenalidomide and dexamethasone (Rd) in 1L followed by a daratumumab-based regimen in 2L. Probabilities of transition between health states (1L, 2L+, and death) were based on published clinical data and real-world data from the Flatiron Health database. The proportion of patients discontinuing treatment after 1L (attrition rates) in the base case was estimated with a binomial logistic model using data from the MAIA trial. Results Using D-Rd in 1L conferred a longer median OS compared with delaying daratumumab-based regimens until 2L after VRd or Rd, respectively (8.9 [95% CrI 7.58-10.42] vs. 6.92 [5.92-8.33] or 5.75 [4.50-7.25] years). Results of scenario analyses were consistent with the base case. Conclusion Our simulation, which incorporates clinically representative treatments and attrition rates, supports the use of D-Rd as initial therapy, rather than delaying the use of daratumumab until later lines of therapy, in patients with transplant-ineligible NDMM.

Abstract Background Patients with high-risk, newly diagnosed multiple myeloma (HR-NDMM) who are ineligible for autologous stem cell transplant (ASCT) have limited first-line treatment options. Recent meta-analyses evaluating the impact of incorporating daratumumab in the backbone regimen on progression-free survival (PFS) have found mixed results in these patients. Materials and Methods A pooled analysis of patient-level data for ASCT-ineligible patients with HR-NDMM [ie, del(17p), t(4;14), t(14;16)] from the MAIA and ALCYONE trials; stratified by study identifier and adjusting for cytogenetic abnormality subtype, baseline performance status, International Staging System stage, myeloma type, and renal impairment; was conducted. Impact of daratumumab on PFS and rates of complete response or better (≥CR), minimal residual disease (MRD)-negative CR, very good partial response or better (≥VGPR), and overall response (ORR) was compared to control. Results Among 101 patients in the daratumumab and 89 patients in the control cohort, median follow-up was 43.7 months. Daratumumab reduced the risk of progression or death by 41% (adjusted hazard ratio for PFS [95% confidence interval (CI)] = 0.59 [0.41-0.85]) versus control. At 36 months, the estimated proportion of patients who did not progress and were still alive was 41.3% in the daratumumab and 19.9% in the control cohort. Rates of ≥CR (41.6% vs. 22.5%), MRD-negative CR (24.8% vs. 5.6%), ≥VGPR (75.2% vs. 46.1%), and ORR (92.1% vs. 74.2%) were higher for daratumumab versus control. Conclusion These findings demonstrate that incorporation of daratumumab in frontline treatment regimens reduced the risk of progression or death and improved response rates among ASCT-ineligible HR-NDMM patients.

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<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 >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.

PURPOSE To evaluate the effects of daratumumab, lenalidomide, and dexamethasone (D-Rd) versus lenalidomide and dexamethasone (Rd) on patient-reported outcomes (PROs) in the phase III MAIA study. PATIENTS AND METHODS PROs were assessed on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30-item and the EuroQol 5-dimensional descriptive system at baseline and every 3 months during treatment. By mixed-effects model, changes from baseline are presented as least squares means with 95% CIs. RESULTS A total of 737 transplant-ineligible (TIE) patients with newly diagnosed multiple myeloma were randomly assigned to D-Rd (n = 368) or Rd (n = 369). Compliance with PRO assessments was high at baseline (> 90%) through month 12 (> 78%) for both groups. European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30-item global health status scores improved from baseline in both groups and were consistently greater with D-Rd at all time points. A global health status benefit was achieved with D-Rd, regardless of age (< 75 and ≥ 75 years), baseline Eastern Cooperative Oncology Group (ECOG) performance status score, or depth of response. D-Rd treatment resulted in significantly greater reduction in pain scores as early as cycle 3 ( P = .0007 v Rd); the magnitude of change was sustained through cycle 12. Reductions in pain with D-Rd were clinically meaningful in patients regardless of age, ECOG status, or depth of response. Similarly, PRO improvements were observed with D-Rd and Rd on the EuroQol 5-dimensional descriptive system visual analog scale score. CONCLUSION D-Rd compared with Rd was associated with faster and sustained clinically meaningful improvements in PROs, including pain, in transplant-ineligible patients with newly diagnosed multiple myeloma regardless of age, baseline ECOG status, or depth of treatment response.

Introduction : Daratumumab (DARA) is a human CD38 antibody approved in combination with standard-of-care (SoC) regimens in pts with NDMM who are TIE. DARA-based treatments showed significantly improved progression-free survival (PFS) in pts with TIE NDMM in ongoing phase 3 studies ALCYONE (DARA + bortezomib/melphalan/prednisone [D-VMP] vs VMP) and MAIA (DARA + lenalidomide/dexamethasone [D-Rd] vs Rd continuous). An NMA allows estimation of the relative efficacy of regimens not compared in head-to-head trials. A previous NMA examined D-VMP and D-Rd vs comparators (Facon T et al., EHA 2019), excluding the SWOG S0777 study (bortezomib/lenalidomide/dexamethasone [VRd]; Durie BG, et al. Lancet 2017) as it enrolled both transplant-eligible (TE) and TIE pts, and data for pts who are TIE only (~50% [aged ≥65 y and frail]) were unavailable. In this NMA, D-Rd and D-VMP had the highest probabilities of being more effective than reference treatment Rd continuous in terms of PFS. Recently, VRd received EMA approval for treatment of TIE NDMM based on SWOG S0777, but results specific to TIE pts are still unavailable. Recent NMAs of TIE pts (Blommestein HM et al., Haematologica, 2019; Weisel et al., EHA 2019; Cao Y et al., Clin Lymphoma Myeloma Leuk, 2019) have included data from the the intent-to-treat (ITT) population of SWOG S0777, though its inclusion violates the similarity assumption. Here, we present a sensitivity analysis of the previously-conducted NMA including all pts who received VRd in SWOG S0777 for a comprehensive view of the comparative effectiveness of DARA-based treatments in TIE NDMM. Methods: VRd was included as part of a sensitivity analysis of the previous NMA based on the ITT population, reporting PFS and overall survival (OS). The Guyot method was used to estimate OS hazard ratios (HRs) for pts aged ≥65 y (proxy for TIE) from SWOG S0777 (Durie BG et al., ASH 2018). Median follow-up in ALCYONE and MAIA was 27.8 months and 28.0 months, respectively. Based on a systematic literature review conducted through January 2019, both PFS and OS were extracted and synthesized in Bayesian NMAs. Choice of fixed- or random-effects (FE or RE) model was based on lowest deviance information criterion (DIC) and/or presence of heterogeneity in the network. Rd continuous was selected as reference, as it was commonly included in guidelines across regions. For PFS and OS, HR <1 indicates the comparison is not in favor of Rd continuous. In addition to the previous NMA, we also report an NMA sensitivity analysis including only comparators approved by the EMA that are relevant for the European, Middle East and/or Africa (EMEA) region (EMEA NMA). Results: Global NMA: RE model was used for both PFS and OS. Compared with Rd continuous, the PFS HR for VRd in the sensitivity analysis was 0.74 (95% credible interval [CrI], 0.42-1.30), which was similar to SWOG S0777 (0.71; [96% Wald confidence interval [CI], 0.56-0.91]) and higher than HRs for D-Rd (0.55; 95% CrI, 0.31-0.97) and D-VMP (0.58; 95% CrI, 0.20-1.62; Table). For OS, the SWOG S0777 HR estimated by Guyot algorithm for pts aged ≥65 y was 0.80 (95% CI, 0.56-1.16). Compared with Rd continuous, the OS HR for VRd in the sensitivity analysis was 0.80 (95% CrI, 0.51-1.26), which was similar to SWOG S0777 and higher than D-Rd (0.78; 95% CrI, 0.51-1.18). EMEA NMA: FE model was used for both PFS and OS. Compared with Rd continuous, the PFS HR for VRd in the sensitivity analysis was 0.74 (95% CrI, 0.60-0.92), which was higher than HRs of D-Rd (0.55; 95% CrI, 0.43-0.71) and D-VMP (0.64; 95% CrI, 0.41-1.02). Compared with Rd continuous, the OS HR for VRd in the sensitivity analysis was 0.80 (95% CrI, 0.55-1.17), which was higher than for D-Rd (0.78; 95% CrI, 0.56-1.09). These results are consistent with the Global NMA, but differ slightly as the EMEA NMA has fewer evidence-loops (only EMEA SoC regimens were included). Conclusions: This study demonstrated favorable efficacy outcomes for DARA-based regimens vs other relevant frontline options, such as VRd, for pts with NDMM who are TIE. Limitations of the sensitivity analysis include lack of comparative trial data and demographic differences between pts from SWOG S0777 and trials of frontline MM treatments for pts who are TIE included in our network. The majority of SWOG S0777 pts are TE (<65 y), who often have better prognoses than TIE pts (≥65 y), and thus violates the similarity assumption of NMAs. However, DARA-based regimens still showed a comparative clinical advantage. Disclosures Facon: Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Usmani:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, SkylineDX, Takeda: Other: Consultant/Advisor; Amgen Array Biopharma, Bristol-Myers Squibb, Celgene, Janssen, Merck, Pharmacyclics, Sanofi, Takeda: Other: Research Grant; Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau. Dimopoulos:Sanofi Oncology: Research Funding. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. Mateos:Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees. Cavo:Janssen, Celgene, Amgen, Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, Janssen, Amgen, BMS, Abbvie, Takeda: Honoraria; Janssen, Celgene: Other: Travel Accommodations; Janssen, Celgene: Speakers Bureau. Heeg:Ingress-Health: Employment. Van Beekhuizen:Ingress-health: Consultancy. Pisini:Janssen: Employment, Equity Ownership. Nair:Janssen: Employment, Equity Ownership. Lam:Janssen: Employment, Equity Ownership. Slavcev:Janssen: Employment, Equity Ownership. He:Janssen: Employment, Equity Ownership.