Qazilbash, Muzaffar H.

Abstract Background: CD34+ hematopoietic stem and progenitor cell (HSPC) dose during hematopoietic cell transplantation (HCT) remains one of the most reliable clinical parameters to predict quality of engraftment. A minimum HSPC dose of 2-2.5x10 6 CD34+ cells/kg is considered necessary for reliable engraftment, while optimal doses of 5-6x10 6 CD34+ cells/kg are associated with faster engraftment, as well as fewer transfusions, infections, and antibiotic days. CXCR4 inhibition significantly improves the number (#) of CD34+ HSPCs mobilized for HCT, when added to G-CSF (G). Motixafortide (M), a novel CXCR4 antagonist, is a potent mobilizer of HSPCs recently evaluated in the phase 3, double blind, placebo controlled, multicenter GENESIS Trial as a mobilizing agent prior to autologous HCT (ASCT) in multiple myeloma (MM). Methods: Patients received G (10 mcg/kg) on days 1-5 (and days 6-8, if needed). On day 4 (and day 6, if needed), patients received either M (1.25 mg/kg) or placebo (P). Apheresis began day 5, with up to 4 days of apheresis if needed. The primary and secondary endpoints were collection of ³6x10 6 CD34+ cells/kg in up to 2 days of apheresis or 1 day, respectively. The # of CD34+ cells/kg infused was determined independently by each investigator according to local practice, but a minimum of ³2x10 6 CD34+ cells/kg was required. A post-hoc analysis was performed pooling data from both arms to evaluate time to platelet engraftment (TPE) (≥20x10 9/L without transfusions x7 days) and neutrophil engraftment (TNE) (ANC ≥0.5x10 9/L x3 days) based on total # of CD34+ cells/kg and # of specific CD34+ HSPC subsets infused. CD34+ HSPC immunophenotyping was performed via multicolor fluorescence-activated cell sorting (FACS). TPE/TNE was analyzed using Kaplan-Meier curves and Cox proportional hazards model. Results: 114 MM patients underwent apheresis, ASCT and were evaluable (M+G N=77; P+G N=37). M+G mobilization yielded a median of 10.8x10 6 CD34+ cells/kg collected in 1 apheresis vs 2.3x10 6 CD34+ cells/kg with P+G (p<0.0001). M+G also resulted in mobilization of higher #s of relevant CD34+ HSPC subsets vs P+G, including 5.6 fold more HSCs (CD45RA-CD123loCD38+CD90+CD49f+) (p<0.0001), 3.5 fold more multipotent progenitors (MPPs) and common myeloid progenitors (CMPs) (CD45RA-CD123loCD38+CD90-CD49f+) (p=0.0004) and 5.6 fold more granulocyte and macrophage progenitors (GMPs) (CD45RA+CD123loCD38+/-CD10-) (<0.0001). The median # of infused HSPCs in both arms was <6x10 6 CD34+ cells/kg (Table 1), with similar TPE of 17-18 days (HR 0.89, 95% CI 0.59-1.34, p=0.57) and TNE of 12 days (HR 0.94, 95% CI 0.62-1.41, p=0.75). However, pooled analysis of all patients (N=114) revealed infusion of ³6x10 6 CD34+ cells/kg was associated with faster median TPE of 16 days vs 18 days with <6x10 6 CD34+ cells/kg (HR 0.63, 95% CI 0.41-0.96, p=0.03) (Figure 1A). Further analysis demonstrated an inverse correlation between increasing CD34+ cells/kg infused and TPE (Pearson r=-0.2789, p=0.0027). In addition, pooled analysis of 36 patients (M+G N=24; P+G N=12) using extended multicolor FACS revealed infusion of higher #s (>75 th percentile) of combined CD34+ HSC, MPP, CMP and GMP subsets was associated with faster TPE of 12 days vs 19 days with lower #s of these subsets (p=0.003) (Figure 2A). Furthermore, higher #s (>75 th percentile) of GMPs was individually associated with faster TPE of 13 days vs 19 days with lower GMP cell doses (p=0.0116) (Figure 2C). TNE was not impacted by increasing doses of total CD34+ HSPCs or any specific CD34+ HSPC subset (all p>0.05) (Figures 1B, 2B and 2D). Conclusions: M+G mobilization enabled significantly more CD34+ cells to be collected in 1 apheresis (median 10.8x10 6 CD34+ cells/kg) vs P+G (2.3x10 6 CD34+ cells/kg), as well as 3.5-5.6 fold higher #s of HSCs, MPPs, CMPs and GMPs (all p-values <0.0004). This high # of CD34+ cells/kg mobilized with M+G enables the potential infusion of ≥6x10 6 CD34+ cells/kg and cryopreservation of cells for later use. A dose response was observed with significant correlation between faster TPE and infusion of higher #s of total CD34+ HSPC doses (³6x10 6 CD34+ cells/kg) and combined HSC, MPP, CMP and GMP subsets. Additionally, infusion of higher #s of CD34+ GMP subsets was independently associated with faster TPE, suggesting these more committed progenitors may play a critical role in early engraftment. Figure 1 Figure 1. Disclosures Crees: BioLineRx Ltd.: Research Funding. Retting: BioLineRx Ltd.: Research Funding. Larson: TORL biotherapeutics: Current holder of individual stocks in a privately-held company; Abbvie, Bioline, BMS, Celgene, GSK, Janssen, Juno, Novartis, Pfizer, Takeda: Research Funding. Illes: Novartis, Janssen, Pfizer, Roche: Other: Travel, Accommodations, Expenses; Takeda, Seattle Genetics: Research Funding; Janssen, Celgene, Novartis, Pfizer, Takeda, Roche: Consultancy. Stiff: CRISPR: Consultancy; Gamida-Cell, Atara, Amgen, Incyte, Takeda, Macrogenetics, Eisai: Research Funding. Sborov: SkylineDx: Consultancy; GlaxoSmithKline: Consultancy; Sanofi: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees. Pereira: Jazz Pharmaceutical: Membership on an entity's Board of Directors or advisory committees. Mikala: Abbvie: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Krka: Consultancy; Novartis: Consultancy; Takeda: Consultancy. Holtick: Sanofi: Honoraria; Celgene: Honoraria. Qazilbash: Janssen: Research Funding; Oncopeptides: Other: Advisory Board; Biolline: Research Funding; Bristol-Myers Squibb: Other: Advisory Board; NexImmune: Research Funding; Amgen: Research Funding; Angiocrine: Research Funding. Hardy: Kite/Gilead: Membership on an entity's Board of Directors or advisory committees; American Gene Technologies, International: Membership on an entity's Board of Directors or advisory committees; InCyte: Membership on an entity's Board of Directors or advisory committees. Sorani: BioLineRx LTD: Current Employment. Shemesh-Darvish: BioLineRx LTD: Current Employment. Vainstein: BioLineRx LTD: Current Employment; Enlivex: Consultancy. Kadosh: StatExcellence: Current holder of individual stocks in a privately-held company; BioLineRx: Honoraria.

Abstract Waldenström macroglobulinemia (WM) is a rare B‐cell lymphoproliferative malignancy. Autologous hematopoietic cell transplantation (auto‐HCT) is considered in a subset of WM patients with relapsed disease. While registry data has shown a benefit for auto‐HCT in relapsed WM, there is a paucity of data on outcomes of patients relapsing after auto‐HCT. Eligibility criteria included adult patients with relapsed/refractory WM who underwent auto‐HCT between 2007 and 2017. The primary endpoint was post‐relapse overall survival (PR‐OS). Secondary endpoints were to identify factors prognostic of PR‐OS. Of the 48 patients with WM who underwent auto‐HCT, 22 (46%) experienced relapse following auto‐HCT. Median PR‐OS of relapsed WM patients after auto‐HCT ( n = 22) was not reached (NR) (95% confidence interval [CI]: 17.5 months‐NR). Among patients who relapsed <1 year versus ≥1 year from auto‐HCT, the median PR‐OS was 18.4 months (95%CI: 0.8‐NR) months and NR (95%CI: 17.5‐NR), respectively ( p = 0.06). Of note, disease status at the time of transplant, CR/VGPR versus partial remission did not appear to impact PR‐OS. The median PR‐OS was significantly longer in patients who received ibrutinib in the post‐transplant setting compared to those who did not (NR vs. 18.4 months, 95%CI: 9.1‐NR, p = 0.02). On univariable analysis, the presence of complex karyotype (RR = 4.87, 95% CI = 1.22–19.53) and a higher number of prior lines of therapy (RR = 1.81, 95% CI = 1.23–2.67) were associated with a significantly higher risk of relapse. This is the only study to date that evaluated outcomes of WM patients who relapsed following auto‐HCT and provides a benchmark for future trials evaluating survival following auto‐HCT relapse.

BackgroundConsolidative autologous hematopoietic stem cell transplantation (AHCT) is commonly used for patients with multiple myeloma (MM). We studied AHCT use and outcomes in patients with MM ≥75 years old.MethodsPatients with MM ≥75 years old receiving AHCT between 2013 and 2017 in the United States were identified using the Center for International Blood and Marrow Transplant Research database. Relapse and/or progression (REL), progression‐free survival (PFS), and overall survival (OS) were modeled using Cox proportional hazards models. Covariates used were age, sex, Karnofsky performance score (KPS), HCT‐comorbidity index (HCT‐CI), International Staging System and/or Durie‐Salmon stage, high‐risk cytogenetics, melphalan dose, and disease status at and 1 year after transplant. AHCT utilization rate using the Surveillance, Epidemiology, and End Results database was used to estimate specific incidence among ≥75 years old by race and gender.ResultsOf 360 patients, 63% were male, 84% were White, 56% had KPS <90, and 57% had HCT‐CI ≥3. The 100‐day transplant‐related mortality was 1% (0%‐2%) with a 2‐year REL rate of 27% (95% confidence interval [CI], 22%‐33%), PFS of 66% (95% CI, 60%‐72%), and OS of 83% (95% CI, 78%‐87%). On multivariate analysis, only high‐risk cytogenetics was associated with REL risk and decreased PFS. In White males, transplant utilization rate was 5.2%‐5.8% compared to 3.5%‐4.0% in African American males (P = .02). There was 3.37‐3.79% transplant utilization in White females compared to 1.88‐2.12% in African American females (P < .01).ConclusionsThe use of AHCT was associated with excellent 2‐year outcomes in this selected MM population ≥75 years old. Transplant utilization for patients ≥75 years old remains low with significant racial and gender disparities.

8022 Background: Maintenance therapy in multiple myeloma (MM) after first autologous hematopoietic cell transplantation (AHCT1) is considered standard of care. Data regarding maintenance therapy after a salvage AHCT (AHCT2) in the setting of relapsed MM are scarce. Therefore, we used data from the Center for International Blood and Marrow Transplant Research (CIBMTR) registry to examine the use of maintenance therapy after AHCT2 in MM patients and its effect on post-transplant patient outcomes. Methods: We included US adult MM patients who underwent AHCT2 after melphalan conditioning regimen from 2010-2018, and excluded patients who underwent tandem transplants. Outcomes of interest included non-relapse mortality (NRM), relapse/progression (REL), progression-free and overall survival (PFS, OS). Cox proportional hazards models were developed to study the main effect (maintenance use) with other covariates of interest including age, sex, race, performance status, HCT-comorbidity index, MM subtype, stage, creatinine, cytogenetic, conditioning melphalan dose, disease status at transplant, and time from AHCT1 to AHCT2. Results: Of 522 patients, 342 received maintenance therapy and 180 did not after AHCT2. Baseline characteristics were similar between the two groups. Median follow up was 58 months in the maintenance group and 61.5 months in the no-maintenance group. Common maintenance regimens included immunomodulatory drugs (IMID)-lenalidomide (N = 145, 42%) or pomalidomide (N = 46, 13%) and proteasome inhibitor, bortezomib (N = 45, 13%). Univariate analysis showed superior outcomes at 5 years in maintenance compared to the no-maintenance group: NRM 2 (0.7-3.9)% vs 9.9 (5.9-14.9)%, p < 0.001, REL 70.2 (64.4-75.8)% vs 80.3 (73.6-86.3)%, p 0.003, PFS 27.8% (22.4-33.5) vs. 9.8% (5.5-15.2), p < 0.001, and OS 54% (47.5-60.5) vs 30.9% (23.2-39.2) p < 0.001, respectively. IMID-containing maintenance regimens were associated with an improved 5-year PFS and OS compared to other maintenance regimens. Use of maintenance therapy retained its association with improved outcomes in multivariate analysis, including NRM: hazard ratio (HR) 0.19 (0.08-0.44), p 0.0001, REL: HR 0.58 (0.47-0.72), p < 0.0001, PFS HR 0.52 (0.43-0.64), p < 0.0001, and OS HR 0.46 (0.36-0.60), p < 0.0001. We conducted additional analyses to investigate a possible selection bias in the maintenance group including landmark analysis at 100-days and 6-months post-AHCT2 as well as a subgroup analysis of patients who received melphalan 200mg/m2 as conditioning for AHCT2 (as a surrogate for fitness)- all these analyses also showed improved outcomes in the maintenance group. Second cancers were reported in 17 (5%) patients in the maintenance group and 6 (3%) patients and no-maintenance group (p 0.39). Conclusions: Maintenance therapy after AHCT2 is associated with superior outcomes in MM patients.

8009 Background: Measuring response among patients with multiple myeloma is essential for the care of patients. Deeper responses have been associated with better progression free survival (PFS) and overall survival (OS). Serum (SIFE) and urine immunofixation are the currently used markers for biochemical documentation of CR after which marrow is tested for plasma cell clearance. Next generation flow cytometry and sequencing are used to document the presence of minimal residual disease (MRD). Mass spectrometry of blood by MALDI (Mass-Fix) is a new simple, inexpensive, sensitive, and specific means of detecting monoclonal immunoglobulins. To better test the hypothesis that Mass-Fix is superior to existing methodologies to predict for survival outcomes—especially SIFE-- samples from the STAMINA trial (NCT01109004), a trial comparing 3 transplant approaches among patients who have already received induction, were employed. Methods: Five-hundred and seventy-five patients were included. Samples from enrollment post-induction (post-I) and 1-year post enrollment (1YR) were tested when available. Four response parameters were assessed univariately: Mass-Fix, SIFE, complete response, and MRD by next generation flow cytometry. Mass spectrometry spectra were evaluated in a blinded fashion. Complete response was according to the 2006 International Myeloma Working Group criteria. Multivariate Cox proportional hazard models using stepwise regression were developed to explore the independent effect of the different response parameters on PFS and OS and interactions with other risk factors. Results: Of the 4 response measures, only MRD and Mass-Fix predicted for PFS and OS at multiple testing points on multivariate analyses (Table). Of the 4 post-I measurements, only MRD predicted for PFS; however, Mass-Fix was the only post-I measurement to predict for OS. Of all the 1-year measures, both 1YR Mass-Fix and 1YR MRD positivity predicted for inferior PFS and OS. In models including MRD and Mass-Fix, SIFE and CR were not prognostic for PFS or OS. Conclusions: Mass-Fix is a powerful means to track monoclonal proteins. The full utility of Mass-Fix was not exploited given the absence of a diagnostic sample and the fact that only serum (and not urine) was tested. Despite these limitations, it performed well at pre-induction and at 1 year. Mass-Fix provides a convenient and non-invasive means of predicting for myeloma outcomes. Clinical trial information: NCT01109004. [Table: see text]

Introduction: VRD (bortezomib, lenalidomide, dexamethasone) and VCD (bortezomib, cyclophosphamide, dexamethasone) are the two most commonly used triplet induction regimens in transplant eligible patients with multiple myeloma (MM). VCD is commonly used in patients with renal dysfunction at diagnosis. Given the variable results seen in head to head comparison of these (or similar) regimens to date, no definitive conclusion can be made on whether they are equivalent. This large CIBMTR registry study compares the outcomes with VRD vs. VCD induction therapy in patients undergoing upfront autologous stem cell transplant (ASCT). Methods: Patients were included if they underwent upfront ASCT for MM from January 2013 to December 2018 within 6 months of diagnosis, received VRD or VCD induction therapy and achieved at least a partial response pre-transplant. Of 1,135 patients, 914 patients received VRD and 221 received VCD therapy. Cox proportional hazards models were created for progression-free survival (PFS) and overall survival (OS). The following covariates were adjusted in the models: induction regimen (main effect), age, sex, race, performance score, hematopoietic cell transplant-comorbidity index (HCT-CI), estimated glomerular filtration rate (eGFR) at diagnosis, immunoglobulin subtype, cytogenetics, ISS stage, response status at transplant, melphalan dose, and maintenance therapy. Results: As shown in Table 1, patients in the VRD and VCD cohorts had similar age at transplant, adjusted HCT-CI scores, and distribution of high-risk cytogenetics. Patients in the VCD group were more likely to have renal impairment and ISS stage III disease. An eGFR (mL/min/1.73m2) at diagnosis &lt; 60 was seen in 26% of VRD patients vs. 48% of VCD patients. ISS stage III was seen in 17% vs. 34% of patients, respectively. Treatment and Response: Pre-transplant response in the VRD cohort was: complete response (CR)- 17%, very good partial response (VGPR)- 48% and partial response (PR)- 35%. Response in the VCD cohort was: CR- 17%, VGPR- 42% and PR- 41%. Conditioning dose was melphalan 200 mg/m2 in 80% of patients receiving VRD vs. 69% in the VCD group. Post-transplant response was at least VGPR in 74% vs. 75% of patients, respectively. Maintenance in the VRD group was: lenalidomide based (+/- bortezomib)- 80%, bortezomib based- 5%, other-3% and none- 12% of patients. In the VCD group, maintenance was: lenalidomide based- 63%, bortezomib based- 11%, other- 1% and none- 24%. Survival: Patients receiving VRD induction had superior outcomes compared to VCD induction with median PFS from transplant of 44.6 (38.0-55.8) months vs 34.1 (25.8-44.7) months, p 0.004 respectively. Median OS was not reached for either group, with 5-year OS 79 (74-83)% for VRD and 60 (50-69)% for VCD, p &lt;0.001. Univariate PFS and OS outcomes by induction regimen and eGFR at diagnosis are shown in Table 2 and Figure 1. Multivariate analysis is shown in Table 3. After adjusting for prognostic factors, there was no statistically significant difference between the two induction regimens, with hazard ratio (HR) for PFS in the VCD vs VRD group being 1.22 (95% CI: 0.96-1.55, p=0.10). ISS stage, cytogenetics, disease status prior to transplant, and maintenance were independent prognostic factors for PFS. Similarly, on multivariate analysis for OS, there was no statistically significant difference in the two groups, with HR for OS in VCD vs VRD group being 1.33 (95% CI: 0.93-1.92, p=0.12). ISS stage, cytogenetics, disease status prior to transplant, and maintenance were independent prognostic factors for OS. Conclusions: In patients with MM undergoing upfront transplant after VRD or VCD induction, no difference in outcomes was seen based on the induction therapy received after adjusting for other prognostic factors. As several MM patients with renal dysfunction are started on VCD, it is reassuring to see that VCD was not associated with inferior PFS, likely due to the eventual transition to maintenance therapy in the majority due to subsequent improvement of renal function. The use of maintenance treatment was uniformly associated with superior outcomes. Disclosures Sidana: Janssen: Consultancy. Kumar:Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Tenebio: Other, Research Funding; Genecentrix: Consultancy; Carsgen: Other, Research Funding; Cellectar: Other; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy. Giralt:Johnson & Johnson: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Actinuum: Other: Advisory board, Research Funding; Amgen: Other: Advisory Board, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; OMEROS: Research Funding; SPECTRUM Pharma: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees, Research Funding; PFIZER: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jensenn: Membership on an entity's Board of Directors or advisory committees, Research Funding; TAKEDA: Membership on an entity's Board of Directors or advisory committees, Research Funding; MILTENYI: Research Funding; JAZZ Pharmaceutical: Membership on an entity's Board of Directors or advisory committees. Qazilbash:Janssen: Research Funding; Bioclinica: Consultancy; Amgen: Research Funding; Angiocrine: Research Funding; Bioline: Research Funding. Shah:GSK, Amgen, Indapta Therapeutics, Sanofi, BMS, CareDx, Kite, Karyopharm: Consultancy; BMS, Janssen, Bluebird Bio, Sutro Biopharma, Teneobio, Poseida, Nektar: Research Funding. D'Souza:Janssen: Consultancy; Akcea: Consultancy; Imbrium: Consultancy; Merck: Research Funding; Pfizer: Consultancy; Teneobio: Research Funding; Amgen: Research Funding.

AbstractWe studied 2,528 patients with upfront autologous haematopoietic cell transplantation (AHCT) for multiple myeloma (MM) from 2008–2017 to develop a prognostic model to predict outcomes. High‐risk cytogenetics included t(4;14), t(14;16), t(14;20), del13q on karyotype, del17p, +1q or 1pdel. A Cox model identified factors prognostic of progression/relapse in a training subset (n = 1,246). A weighted score using these factors was assigned to a validation cohort (n = 774). Presence of high‐risk cytogenetics [hazard ratio, (HR) 1·68 (1·3–2·17)] and pre‐AHCT bone marrow plasma cells (BMPCs) ≥10% [1·68 (1·33–2·12)] were assigned 4 points each; albumin at diagnosis <3·5 g/dl [1·31 (1·07–1·61)] 2; standard risk cytogenetics 1, and no cytogenetics abnormality, BMPCs <10% at AHCT and albumin ≥3·5 g/dl at diagnosis 0 points each. A three‐category system with low risk (0–3), intermediate risk (4–8) and high risk (9–10) showed 3‐year progression‐free survival in the low vs. intermediate vs. high risk of 58% (95% CI: 52–63) vs. 49% (95% CI: 43–56) vs. 31% (95% CI: 12–51), P < 0.001 respectively, and 3‐year OS in low vs. intermediate vs. high risk of 88% (95% CI: 84–91) vs. 81% (95% CI: 76–86) vs. 64% (95% CI: 39–80); P < 0·001. Our prognostic scoring system can identify MM patients at risk for early relapse after AHCT.

BackgroundUpfront autologous hematopoietic stem cell transplantation (AHCT) remains an important therapy in the management of patients with multiple myeloma (MM), a disease of older adults.MethodsThe authors investigated the outcomes of AHCT in patients with MM who were aged ≥70 years. The Center for International Blood and Marrow Transplant Research (CIBMTR) database registered 15,999 patients with MM in the United States within 12 months of diagnosis during 2013 through 2017; a total of 2092 patients were aged ≥70 years. Nonrecurrence mortality (NRM), disease recurrence and/or progression (relapse; REL), progression‐free survival (PFS), and overall survival (OS) were modeled using Cox proportional hazards models with age at transplantation as the main effect. Because of the large sample size, a P value <.01 was considered to be statistically significant a priori.ResultsAn increase in AHCT was noted in 2017 (28%) compared with 2013 (15%) among patients aged ≥70 years. Although approximately 82% of patients received melphalan (Mel) at a dose of 200 mg/m2 overall, 58% of the patients aged ≥70 years received Mel at a dose of 140 mg/m2. On multivariate analysis, patients aged ≥70 years demonstrated no difference with regard to NRM (hazard ratio [HR] 1.3; 99% confidence interval [99% CI], 1‐1.7 [P = .06]), REL (HR, 1.03; 99% CI, 0.9‐1.1 [P = 0.6]), PFS (HR, 1.06; 99% CI, 1‐1.2 [P = 0.2]), and OS (HR, 1.2; 99% CI, 1‐1.4 [P = .02]) compared with the reference group (those aged 60‐69 years). In patients aged ≥70 years, Mel administered at a dose of 140 mg/m2 was found to be associated with worse outcomes compared with Mel administered at a dose of 200 mg/m2, including day 100 NRM (1% [95% CI, 1%‐2%] vs 0% [95% CI, 0%‐1%]; P = .003]), 2‐year PFS (64% [95% CI, 60%‐67%] vs 69% [95% CI, 66%‐73%]; P = .003), and 2‐year OS (85% [95% CI, 82%‐87%] vs 89% [95% CI, 86%‐91%]; P = .01]), likely representing frailty.ConclusionsThe results of the current study demonstrated that AHCT remains an effective consolidation therapy among patients with MM across all age groups.

8515 Background: AL is a clonal plasma cell (PC) disorder causing multiorgan dysfunction from amyloid fibril deposition. While bortezomib (B) induction has been used prior to AHCT recently, AHCT without prior induction has been a common practice. The primary objective of this study was to compare outcomes of AL patients who proceeded to AHCT without induction to those receiving pre-AHCT induction with B. Methods: Outcomes of 426 systemic AL AHCT recipients between 2014-2018 reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) were reviewed. Patients receiving induction with therapy other than B, AHCT occurring > 9 months after diagnosis, no documented AL end-organ involvement, myeloma-defining events and conditioning other than melphalan (MEL) monotherapy were excluded. Multivariate analysis (MVA) was conducted to identify prognostic factors associated with relapse, PFS and overall survival (OS). Results: 286 patients received B induction therapy vs 140 patients receiving no induction. Age, gender, number and type of organs involved, and AL AHCT center volume were similar between the groups. Patients receiving induction had greater PC burden compared with no induction (PC ≥ 10%, 41% vs 11%, p < 0.01). Induction was B, cyclophosphamide and dexamethasone (D) in 83% followed by B, lenalidomide and D (10%) or B+D (7%). Median follow-up was 24.9 months. At 2 years, B induction vs. no induction was associated with 13% (95% CI 10-17%) vs 22% (95% CI 15-30%) relapse risk (p = 0.03); 83% (95% CI 79-87%) vs 74% (95% CI 66-81%) PFS (p = 0.04); 93% (95% CI 90-95%) vs 94% (95% CI 89-97%) OS (p = 0.7). On MVA, the B induction group had improved PFS (HR 0.46, 95% CI 0.3-0.7, p < 0.001) with similar OS (HR 0.6, 95% CI 0.3-1.2, p = 0.1) compared with no induction. Creatinine < 2 mg/dl (HR 0.55, 95% CI 0.3-0.9, p = 0.02) and Karnofsky score ≥90 (HR 0.51, 95% CI 0.33-0.78, p < 0.01) were also associated with improved PFS. MEL dose < 180 mg/m2 was associated with inferior PFS (HR 2.17, 95% CI 1.31-3.61, p < 0.01) and OS (HR 3.6, 95% CI 1.5-8.6, p < 0.01). No deaths were seen in the first 100 days post-AHCT. At last follow-up, 32 deaths occurred, 26 (81%) due to AL. Conclusions: Compared with prior CIBMTR analyses, B induction use has increased in AL AHCT recipients and a higher PC burden was the only clinical determinant. Furthermore, B induction was associated with lower relapse and improved PFS at 2 years with no OS difference despite higher proportion of patients with > 10% PC, which has been associated with poor outcomes.

Background: Novel agent induction and AHCT remains the preferred initial therapeutic strategy for transplant-eligible MM patients. Current prognostic tools in MM focus solely on disease-specific factors at diagnosis to determine patient prognosis-International Staging System (ISS) and revised-ISS (R-ISS). A major limitation to both, the ISS and R-ISS, is that they are not specific for HCT-eligible patients and do not take into account other patient factors that may enter into a decision to pursue AHCT. The data used to generate these staging systems were from broad populations with varying upfront treatment strategies and included patients who were ineligible for intensive therapy. Additionally, there is considerable interest in identifying the population that relapses early despite modern induction/AHCT approaches who are candidates for novel approaches for maintenance/consolidation. To address these problems, we used data from the Center for Blood and Marrow Transplant Research (CIBMTR) registry to identify disease-, patient-, and transplantation-specific variables that are associated with progression-free survival (PFS) in patients undergoing upfront AHCT (within 12 months of diagnosis). Methods: We used the outcomes of 2528 MM patients undergoing upfront AHCT from 2008-2017 reported to the CIBMTR. Patients were divided into training and validation sets with a 50% random split. High risk cytogenetics was defined as the presence of one or more of the following: t(4;14), t (14;16), t (14;20), del 13q, del 17p, 1q gain, or 1p deletion. We used a Cox multivariable model to identify factors prognostic of progression free survival (PFS) in a training subset. The regression coefficients of the final model was transformed into a risk score with an appropriate transformation. A weighted score using these factors was assigned to the training cohort (n = 917) and validation cohort (n=897) using subset that had all values that entered the final model. Kaplan-Meier estimates of the individual scores were used to classify patients into risk groups for both cohorts. Results: Baseline characteristics of these patients are shown in Table 1. No cytogenetic abnormality, VRD induction, pre-AHCT bone marrow plasma cells (BMPCs) &lt;10% and 1 line of induction chemotherapy were assigned 0 points. Pre-AHCT BMPCs ≥10% (hazard ratio HR, 1.47; 95% CI, 1.19-1.83), use of ≥2 lines of induction chemotherapy prior to AHCT (HR 1.32; 95% CI 1.06-1.64), standard cytogenetic risk vs. no abnormality (HR 1.41; 95% CI 1.13-1.77) and induction regimens (non-VRD regimens vs. VRD) (HR 1.4, 95% CI 1.17-1.74) were associated with increased hazard of progression and assigned 1 point in the scoring system. Presence of high-risk cytogenetics vs. no abnormality (HR 1.87; 95% CI 1.45-2.42) was assigned 2 points, and the use of thalidomide and dexamethasone (TD) as an induction regimen (HR 2.19; 95% CI 1.48-3.2) was assigned 3 points. A two-category system was created based on the scoring: low risk (0-3) and high risk (4-6). The scoring system was prognostic for PFS when applied to both cohorts. High-risk group was found to have significantly higher risk of progression and/or death compared to low risk in training (HR 2.2; 95% CI 1.74-2.86; p&lt;0.0001) and validation cohort (HR 1.7, 95% CI 1.30-2.22; p=0.0001) respectively (Table 2). The 3-year PFS in the training cohort was 60% (95% CI 56%-64%) in low risk and 27% (95% CI 17%- 36%) in high risk while in the validation cohort was 51% (95% CI 47%-55%) in low risk and 28% (95% CI 16%- 39%) in high risk (Figure 1A and 1B). Conclusions: We describe a prognostic model specifically for patients undergoing upfront AHCT in MM which can identify patients at very high risk for early relapse/progression. These patients should be ideal candidates for studies of immunotherapy or other interventions after AHCT aimed at reducing relapse. Disclosures Dhakal: Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Shah:Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees; University of California, San Francisco: Employment; Poseida: Research Funding; Indapta Therapeutics: Equity Ownership; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding. Qazilbash:Amgen: Consultancy, Other: Advisory Board; Autolus: Consultancy; Bioclinical: Consultancy; Genzyme: Other: Speaker. D'Souza:EDO-Mundapharma, Merck, Prothena, Sanofi, TeneoBio: Research Funding; Prothena: Consultancy; Pfizer, Imbrium, Akcea: Membership on an entity's Board of Directors or advisory committees. Hari:AbbVie: Consultancy, Honoraria; Cell Vault: Equity Ownership; Sanofi: Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Amgen: Research Funding; Kite: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.