Nair, Sandhya

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 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.

Background: Light chain (AL) amyloidosis is a rare disease in which deposits of insoluble amyloid derived from immunoglobulin light chains accumulate and cause dysfunction of organs including the heart and kidneys. In order to reverse organ damage and improve overall survival, treatment must provide rapid, deep, and sustained hematologic responses. Although therapies approved for the treatment of multiple myeloma have demonstrated some efficacy, there are currently no health authority-approved treatments for AL amyloidosis. A retrospective observational study was undertaken to characterize patients and describe treatment patterns in patients with AL amyloidosis from real-world data in the US. Methods: Data were extracted from Optum Electronic Health Records (EHR) and Optum Clinformatics Data Mart (claims) databases. Eligible patients had (1) a diagnosis of AL amyloidosis (ICD-10 code E85.81) on or after January 1, 2008 or (2) a diagnosis of amyloidosis (ICD-9 codes 277.30, 277.39; ICD-10 codes E85.89, E85.9) on or after January 1, 2008 and at least one line of therapy (LOT) comprising one or more of the following treatments: bendamustine bortezomib, carfilzomib, cyclophosphamide, daratumumab, dexamethasone, doxorubicin, elotuzumab, etoposide, interferon alfa-2a, interferon alfa-2b, ixazomib, lenalidomide, melphalan, panobinostat, pomalidomide, prednisone/prednisolone, thalidomide, vincristine, or autologous stem cell transplant. Patients were required to have continuous medical enrollment during the 365 days prior to the index amyloidosis diagnosis date (claims data) or have first active date at least 365 days prior to index amyloidosis date (EHR data), must not have had prior cancer in the 365-day period prior to the index amyloidosis diagnosis date, and must have been age ≥18 years at time of amyloidosis diagnosis. Patients treated with dexamethasone only or dexamethasone and prednisolone only for ≤90 days and those treated with prednisone/prednisolone only irrespective of duration were excluded. LOTs were defined by a start date, an end date, and a distinct regimen made up of ≥1 drugs. Patients may have multiple sequential LOTs during the available follow-up period. Comorbidities were scored according to the Charlson Comorbidity Index (CCI). A score of 0 reflects no comorbidities; higher scores reflect increased mortality risk and the maximum score is 24. Descriptive statistics are provided for patient characteristics at index diagnosis date for patients who had ≥1 LOT, distribution of regimens in each LOT, treatment attrition, and duration of treatment in each line of therapy and by regimen. Results: Data from 1688 patients (Optum claims, n=624; Optum EHR, n=1064) were included in the analysis (Figure). Median age at diagnosis was 67 years and 55.7% of patients were male. Almost 70% of patients had an index diagnosis date between 2013 and 2019. The median CCI score at index diagnosis date (based on comorbidities in the 365-day pre-index diagnosis period) was 1 and 10.9% of patients had a stem cell transplant on or after the index diagnosis date. The three most common comorbidities were hypertension (50.8%), renal failure (26.2%), and congestive heart failure (24.6%). Median follow-up period was 28 months. Treatment information for regimens used by ≥5% of patients for LOT1 is summarized in the Table. The most common treatment regimen for LOT1 was a proteasome inhibitor (PI), an alkylating agent, and a steroid (n=392, 23.2%); this combination was used for an average of 111 days. Of patients treated with this combination, the most common regimen was bortezomib, cyclophosphamide, and dexamethasone (VCd), used by 358 patients. Steroid only (dexamethasone for ≥90 days) regimens accounted for 16.4% and a PI ± steroid for 13.2% of LOT1. A limitation of the study is that assumptions were used to classify AL amyloidosis vs other types of amyloidosis. Conclusions: VCd is the most commonly used regimen in patients with newly-diagnosed AL amyloidosis. This is consistent with clinical guidelines and real world data from Europe (Palladini et al, EHA 2020), supporting this regimen as the current standard of care for treatment of patients with newly-diagnosed AL amyloidosis. Disclosures Dispenzieri: Celgene: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Intellia: Research Funding; Janssen: Research Funding; Takeda: Research Funding. Zonder:Intellia, Amgen, Takeda, Janssen, Regeneron, Alnylam, Caelum, Oncopeptides: Consultancy; BMS, Celgene: Research Funding. Hoffman:Loxo: Current equity holder in publicly-traded company; Celgene: Honoraria, Speakers Bureau. Wong:Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Fortis: Research Funding; Roche: Research Funding; GSK: Research Funding; Amgen: Consultancy; Bristol Myers Squibb: Research Funding. Liedtke:Adaptive: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria. Abonour:BMS: Consultancy, Research Funding; Takeda: Consultancy; Janssen: Honoraria, Research Funding; Celgene: Consultancy. D'Souza:Amgen, Merck, TenoBio: Research Funding; Akcea, Imbrium, Janssen, Pfizer: Consultancy. Lee:Janssen: Current Employment. Nair:Janssen: Current Employment. Potluri:SmartAnalyst Inc.: Current Employment. Weiss:Janssen: Current Employment, Current equity holder in publicly-traded company. Vermeulen:Janssen: Current Employment, Current equity holder in publicly-traded company. Lam:Janssen: Current Employment. Mehra:Janssen: Current Employment.

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.