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Positron emission tomography-computed tomography (PET-CT) can identify bony lesions, assess disease burden, and detect extramedullary disease (EMD) in patients with multiple myeloma. We retrospectively reviewed records of patients who underwent PET-CT within 60 days of a new diagnosis (before therapy commenced) to identify the nature and prognostic impact of PET-CT abnormalities. Patients (N = 313) were seen from April 2005 through June 2017. Of the 234 patients (75%) with focal lesions (FLs), 182 (58%) had at least 3 FLs, 38 (12%) had EMD, and 204 (65%) had documented myelomatous lytic lesions. The median maximum standardized uptake value (SUVmax ) for the entire cohort was 5.9 (range 1.5-48.3). Presence of at least 3 FLs and EMD predicted inferior overall survival (OS); median OS was 57.8 months for patients with 3 or more FLs and 103.6 months for patients with fewer than 3 FLs (P = .003). The median OS was 45.5 and 71.8 months for patients with and without EMD, respectively (P = .004). No clear SUVmax cutoff was predictive of progression-free survival or OS. PET-CT is a valuable tool for assessing disease burden and could provide prognostic information about a contemporary cohort of patients with newly diagnosed myeloma who received treatment with novel agents.

Symptomatic hyperviscosity is a well-established phenomenon in Waldenstrom macroglobulinemia (WM). Monoclonal IgM can variably impact intrinsic serum viscosity, leading to widely disparate symptomatic thresholds for development of hyperviscosity-related symptoms. Data regarding the predictors of symptomatic hyperviscosity and outcomes related to this complication remain scarce and a recent study proposed that IgM >6000 mg/dL be considered a new criterion for initiating therapy in otherwise asymptomatic (smoldering) WM to pre-empt hyperviscosity-related injury. Herein, we attempt to identify predictors of the development of symptomatic hyperviscosity and its impact in patients with WM. Of 997 WM patients evaluated from January, 1996 through June, 2017, symptomatic hyperviscosity was observed in 130 (13%) patients. Overall survival (OS) of these 130 patients was similar to that of patients without symptomatic hyperviscosity (median: 11.5 vs 11.6 years; P = 0.63). On multivariate-analysis, only viscosity >1.8 cp (risk ratio: 4.0, P = 0.02) assessed at the time of WM diagnosis was an independent predictor for the development of subsequent symptomatic hyperviscosity. Among patients with smoldering WM and IgM >6000 mg/dL at diagnosis (n = 13) who were managed expectantly, the median time-to-initial therapy was 6.9 years and only 15% developed hyperviscosity-related symptoms subsequently. In summary, the occurrence of symptomatic hyperviscosity does not impact OS. Serum viscosity at diagnosis of WM, and not IgM concentration, represents the single most important independent predictor for development of subsequent hyperviscosity-related symptoms. Patients with smoldering WM and high serum IgM can be safely observed in the absence of any indications per the Consensus recommendations to initiate WM-directed therapy.

Collection and storage of peripheral blood stem cells (PBSCs) for use in autologous stem cell transplantation (ASCT) upon first disease relapse is an accepted practice for eligible patients with multiple myeloma (MM). However, little is known about the factors and outcomes associated with nonuse of these collected and stored PBSCs by MM patients who intended to have a delayed ASCT. From January 1, 2004 to December 31, 2014 we identified 342 patients who underwent collection and storage of their PBSCs in anticipation of a delayed ASCT upon first disease relapse. Among these, 176 patients (11%) had not proceeded to a delayed ASCT at the time of this study analysis. The most common reason for not undergoing an ASCT was not experiencing a relapse on first-line therapy (53%, n = 94). However, 11% of patients (n = 37) who planned for a delayed ASCT were unable to undergo an ASCT at disease relapse. Comparison with a control group of MM patients who underwent an upfront ASCT suggested a worse overall survival from diagnosis in these patients who were ASCT ineligible at disease relapse (112 versus 80 months, P = .011). This study provides valuable data for patients and care providers to take into consideration when deciding on whether to pursue an upfront or a delayed ASCT.

Detection of myeloma progression (PD) relies on serial 24-h urinary M protein measurements in patients without measurable serum M spike. We examined whether serial difference free light chain (dFLC) levels could be used as a surrogate for serial 24-h urine M protein measurements in monitoring for PD in patients with baseline measurable urine M protein. We studied 122 patients who had serial measurement of urine M protein and serum FLC and had demonstrated PD. The median increase in dFLC with progression as defined by urine M spike was 110% (IQR: 55-312) and median absolute increase was 74 mg/dL; while 89% of patients had dFLC increase ≥ 25%, 94% had absolute increase in dFLC > 10 mg/dL, and 98% met at least 1 of these 2 criteria at PD. In patients with baseline measurable serum FLC (n = 118), 89% had increase in dFLC ≥ 25%, 97% had dFLC increase of > 10 mg/dL, and 98% had 1 of the 2. We conclude that serial dFLC assessments can be used in place of serial 24-h urine protein assessments during myeloma surveillance to monitor for PD. Once patients have an absolute increase in dFLC of >10 mg/dL from the nadir, a 24-h urine collection can then be assessed to document PD as per the International Myeloma Working Group criteria.

Myeloma patients failing to achieve a complete response post autologous stem cell transplantation are heterogeneous, some ultimately achieving deeper responses and prolonged remission, whilst others relapse rapidly with poor outcomes. We evaluated the prognostic impact of the plasma cell proliferative index (PCPI) post-therapy, in 382 patients with myeloma failing to achieve complete response at 100 days post-transplant. Sixty percent (n = 230) of patients had zero clonal or too few clonal plasma cells to accurately assess PCPI (No PCPI). The remaining 40% (n = 152) of patients had PCPI performed with 79% (n = 120) having a low PCPI and 21% (n = 32) having an elevated PCPI. Patients with an elevated PCPI had significantly shorter progression free and overall survival. The median PFS was 8 months for elevated PCPI vs. 19 months for low PCPI vs. 24 months for no PCPI (p

Autologous stem cell transplantation (ASCT) remains a mainstay in the treatment of multiple myeloma (MM). While the procedure is generally safe, toxicities associated with high-dose melphalan conditioning are common and significantly affect patient quality of life. Recently, a propylene glycol-free melphalan formulation (PG-free MEL; Evomela®) was approved by the United States Food and Drug Administration as an ASCT-conditioning regimen for MM. PG-free MEL is more soluble and stable than propylene glycol-solubilized melphalan (PG-solubilized MEL; Alkeran®). As such, there is speculation that it could decrease toxicities and increase the efficacy of ASCT. We compared the outcomes of patients conditioned with PG-free MEL (n = 216) to PG-solubilized MEL (n = 200) at our institution. The baseline characteristics were similar between the two groups. After Day +0, there were no differences in terms of hospitalizations, neutropenic fevers, intravenous granisetron requirement, World Health Organization grade ≥ 2 oral/esophageal mucositis, intravenous fluid requirement, or narcotic requirement. However, PG-free MEL patients had a higher incidence of diarrhea, which was mostly C. difficile-negative (82% vs. 71%, P = 0.015*). Day + 100 hematologic responses and progression-free survival after ASCT were comparable. In summary, we demonstrate that switching to PG-free MEL did not significantly reduce short-term complications of ASCT or improve outcomes in MM.

Background and objectives Kidney involvement in Waldenstrom macroglobulinemia is less well described compared with kidney manifestations in multiple myeloma. Design, setting, participants, & measurements Of the 1363 patients seen with Waldenstrom macroglobulinemia and other IgM-secreting B cell lymphoproliferative disorders seen at the Mayo Clinic between 1996 and 2015, 57 kidney biopsies were retrospectively studied. The biopsy findings were correlated with clinical, kidney, and hematologic characteristics. Criteria for inclusion were evidence of a monoclonal IgM protein and availability of a kidney and a bone marrow biopsy for review. Glomerular and tubulointerstitial pathologies were categorized according to whether they were related to the monoclonal IgM. Results Of the 57 patients identified, monoclonal gammopathy–related kidney lesions were identified in 82% (47 of 57 biopsies), whereas nonmonoclonal gammopathy–related kidney lesions were seen in 18% (ten of 57). Monoclonal gammopathy–related kidney lesions included monoclonal Ig–related amyloidosis ( n =19; 33%), nonamyloid glomerulopathy ( n =20, 35%), and tubulointerstitial nephropathies ( n =8; 14%). The most common monoclonal gammopathy–related kidney lesion was monoclonal Ig–related amyloidosis ( n =19; 33%) followed by cryoglobulinemic GN ( n =13; 28%). Lymphoma infiltration was the most common tubulointerstitial lesion ( n =4; 9%). The hematologic diagnosis was Waldenstrom macroglobulinemia in 74% ( n =42), monoclonal gammopathy of renal significance in 16% ( n =9), and marginal zone lymphoma ( n =2), chronic lymphocytic leukemia ( n =2), and low-grade B cell lymphoma ( n =2) in 4% each. Conclusions Our study confirms a diverse variety of kidney lesions in patients with monoclonal IgM gammopathy.

Purpose Autologous stem-cell transplantation (ASCT) has been used in patients with immunoglobulin light chain (AL) amyloidosis for more than two decades. Early experience raised concerns regarding safety with high early-mortality rates. Patients and Methods We report 20 years of experience with ASCT for AL amyloidosis at the Mayo Clinic Rochester. In all, 672 consecutive patients receiving ASCT for AL amyloidosis were divided into three cohorts on the basis of date of transplantation (cohort 1, 1996-2002 [n = 124]; cohort 2, 2003-2009 [n = 302]; and cohort 3, 2010-2016 [n = 246]). Results The median age for the entire cohort was 59 years, with patients in cohort 3 being slightly older than those in the other two cohorts (60 v 58 v 54 years for cohorts 3, 2, and 1, respectively; P < .001). Fewer patients in cohort 3 had more than two organs involved (9% v 18% v 19% for cohorts 3, 2, and 1, respectively; P < .001). More patients received pretransplantation therapy in cohort 3 compared with earlier time periods (49% v 38% v 42% for cohorts 3, 2, and 1, respectively; P = .02). Hematologic response was higher in cohort 3 (84% v 79% v 69% for cohorts 3, 2, and 1, respectively; P = .002). Median overall survival for the entire cohort was 122 months and improved over time (not reached v 120 months v 75 months for cohorts 3, 2, and 1, respectively; P < .001). Treatment-related mortality declined over time (2.4% v 8.6% v 14.5% for cohorts 3, 2, and 1, respectively; P < .001). On multivariable analysis, conditioning dose, Mayo stage 2012, and hematologic response were independent predictors of survival. Conclusion ASCT is a highly effective therapy for AL amyloidosis. The improved survival and markedly reduced treatment-related mortality in eligible patients indicate that this will remain an important first-line option even in the era of treatment approaches that use novel agents.

The plasma cell proliferative index provides an insight into plasma cell biology in plasma cell disorders and is an important prognostic marker in myeloma and smoldering myeloma. We analyzed the prognostic impact of the plasma cell proliferative index in 513 patients with systemic immunoglobulin light chain (AL) amyloidosis undergoing stem cell transplantation at the Mayo Clinic between 1st January 2003 and 31st August 2016. Two cohorts were identified according to Low or Elevated plasma cell proliferative index. Patients with an Elevated plasma cell proliferative index had more cardiac involvement (56% vs. 44%; P=0.01), less renal involvement (55% vs. 70%; P=0.001), and were more likely to have 10% or over bone marrow plasma cells (58% vs. 32%; P

Purpose Selinexor, a first-in-class, oral, selective exportin 1 (XPO1) inhibitor, induces apoptosis in cancer cells through nuclear retention of tumor suppressor proteins and the glucocorticoid receptor, along with inhibition of translation of oncoprotein mRNAs. We studied selinexor in combination with low-dose dexamethasone in patients with multiple myeloma refractory to the most active available agents. Patients and Methods This phase II trial evaluated selinexor 80 mg and dexamethasone 20 mg, both orally and twice weekly, in patients with myeloma refractory to bortezomib, carfilzomib, lenalidomide, and pomalidomide (quad-refractory disease), with a subset also refractory to an anti-CD38 antibody (penta-refractory disease). The primary end point was overall response rate (ORR). Results Of 79 patients, 48 had quad-refractory and 31 had penta-refractory myeloma. Patients had received a median of seven prior regimens. The ORR was 21% and was similar for patients with quad-refractory (21%) and penta-refractory (20%) disease. Among patients with high-risk cytogenetics, including t(4;14), t(14;16), and del(17p), the ORR was 35% (six of 17 patients). The median duration of response was 5 months, and 65% of responding patients were alive at 12 months. The most common grade ≥ 3 adverse events were thrombocytopenia (59%), anemia (28%), neutropenia (23%), hyponatremia (22%), leukopenia (15%), and fatigue (15%). Dose interruptions for adverse events occurred in 41 patients (52%), dose reductions occurred in 29 patients (37%), and treatment discontinuation occurred in 14 patients (18%). Conclusion The combination of selinexor and dexamethasone has an ORR of 21% in patients with heavily pretreated, refractory myeloma with limited therapeutic options.

Organ recovery following anti-plasma cell therapy is associated with improved outcome in patients with AL amyloidosis. Current organ response criteria do not consider the depth of response. Newly diagnosed AL amyloidosis patients who had involvement of at least one evaluable organ and documentation of organ response were included. Cardiac response was seen in 182 patients. Time to cardiac response was 9.4 months. Renal response was seen in 278 patients, at a median time to response of 6 months. Hepatic response was seen in 70 patients, with a median time to response of 6.1 months. In all organs, the deeper the organ response achieved, the longer the survival. This led to four organ response criteria: complete organ response (nadir NT-proBNP ≤400 pg/mL; nadir proteinuria ≤200 mg per 24 h; nadir alkaline phosphatase ≤×2 lower limit of normal); very good partial organ response (>60% reduction in parameter not meeting complete organ response definition); partial organ response (31–60% reduction in parameter); and non-responder (≤30% reduction in organ response parameter). Cardiac and renal progression were associated with baseline organ impairment and inversely associated with the depth of organ response. Grading the depth of organ response provides additional valuable prognostic information for newly diagnosed AL amyloidosis patients.

End‐stage renal disease (ESRD) patients receiving hemodialysis are typically anemic due to a lack of erythropoietin (EPO), a hormone required for red blood cell (RBC) production. EPO replacement therapy is complex, often resulting in oscillating hemoglobin (Hb) levels. EPO dosing protocols do not account for endogenous delays and appear to contribute to, if not cause, Hb variability. The Mayo Clinic Anemia Management System (MCAMS) is based on a physiological simulation of the production and lifespan of RBCs, driven by EPO dosage schedules. Patient‐specific parameters were found such that simulated Hb levels matched historical Hb levels in response to historical EPO doses. The calibrated model was used to identify new dosing regimens that stabilize Hb. MCAMS has been used to recommend individualized EPO dosage regimens to maintain stable Hb levels within a desired target range for more than 600 patients, improving patient outcomes while reducing medication costs by about 40 percent. © 2018 System Dynamics Society

Background :COVID-19 adversely affects individuals with cancer. Several studies have found that seroconversion rates among patients with hematologic malignancies are suboptimal when compared to patients without cancer. Among patients with hematologic malignancies, seroconversion rates also appear to be influenced by recent treatment and the type of treatment they have received. Patients with non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) are immunocompromised due to impaired humoral and cellular immunity in addition to prescribed immunosuppressive therapy. Chimeric antigen receptor T-cell (CAR T) therapy is now widely used for NHL and MM, but little is known about seroconversion rates after COVID-19 vaccination among these populations. Current national guidelines recommend COVID-19 vaccination to be offered to CAR T recipients as early as three months thereafter. We retrospectively evaluated SARS-CoV-2 spike-binding IgG antibody levels following COVID-19 vaccination among NHL and MM CAR T therapy recipients. Methods:This retrospective study was conducted at three Mayo Clinic sites on NHL and MM patients that received CAR T infusions from Sept 2016 to June 2021. Baseline characteristics were ascertained from medical records. All NHL and MM patients who had received CAR T at any point and were alive at the time that the COVID-19 vaccine first became available were eligible for inclusion for antibody response evaluation. For antibody response to vaccination, antibody spike values > 0.80 U/mL were considered positive. Results: Out of 104 CAR T infusions, 73 patients are alive at the time of this submission. We have had 7 patients with known COVID-19 pre-CAR T and all 7 are currently alive (5 have antibody titers and 2 have not been tested yet). Nineteen patients developed known COVID infection post-CAR T (13 alive and 6 deceased). The mortality of COVID post-CAR T in our sample was 31.5%. Furthermore, of the 13 patients that survived COVID-19, they received CAR T an average of 416 days prior to COVID-19 infection (median = 337, range = 54 - 1406); the 6 patients who died from COVID-19 had received CAR T an average of 250 days prior to COVID-19 infection (median = 164, range = 7 - 846). All 6 deceased patients did not receive COVID-19 vaccination pre-CAR T. Out of 17 CAR T patients tested for antibody spike titers post COVID-19 vaccination, 76.4% were able to mount an antibody response. More patients with MM had a higher titer response to the vaccine (>250 U/mL) compared to the NHL counterparts (0.80-249 U/mL). All patients that received the vaccine, regardless of antibody response, were alive at the time of this submission. Conclusions:The majority of CAR T recipients with NHL and MM are able to mount an antibody response following COVID-19 vaccination in our relatively small sample. The frequency of seroconversion among CAR T recipients seems to be similar to patients with hematologic malignancy who had received a hematopoietic cell transplant reported elsewhere. These findings are limited by our small sample size and may be influenced by the timing of vaccination relative to CAR T. Furthermore, almost half of our patients received IVIG post CAR T which could potentially cause false positive antibody results as pooled immunoglobulin preparations may contain COVID-19 antibodies from vaccinated healthy donors. To better understand the characteristics of the immunologic response against SARS-CoV-2 in patients post-CAR T, larger multicenter studies exploring both humoral and cellular immunity will be needed. JEWN, MI and JM are co-first authors and PV, HM and AR are co-senior authors. Figure 1 Figure 1. Disclosures Munoz: Physicians' Education Resource: Honoraria; Seattle Genetics: Honoraria; Bayer: Research Funding; Gilead/Kite Pharma: Research Funding; Celgene: Research Funding; Merck: Research Funding; Portola: Research Funding; Incyte: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Research Funding; Janssen: Research Funding; Millennium: Research Funding; Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Pharmacyclics/Abbvie, Bayer, Gilead/Kite Pharma, Pfizer, Janssen, Juno/Celgene, BMS, Kyowa, Alexion, Beigene, Fosunkite, Innovent, Seattle Genetics, Debiopharm, Karyopharm, Genmab, ADC Therapeutics, Epizyme, Beigene, Servier: Consultancy; Targeted Oncology: Honoraria; OncView: Honoraria; Kyowa: Honoraria. Bergsagel: Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; GSK: Consultancy, Honoraria. Wang: Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; InnoCare: Research Funding; Novartis: Research Funding; MorphoSys: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Fonseca: Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; 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; BMS: Consultancy; Amgen: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Mayo Clinic in Arizona: Current Employment; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy. Palmer: Sierra Oncology: Consultancy, Research Funding; CTI BioPharma: Consultancy, Research Funding; Protagonist: Consultancy, Research Funding; Incyte: Research Funding; PharmaEssentia: Research Funding. Dingli: Novartis: Research Funding; GSK: Consultancy; Apellis: Consultancy; Alexion: Consultancy; Sanofi: Consultancy; Janssen: Consultancy. Kapoor: Sanofi: Research Funding; AbbVie: Research Funding; Takeda: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding. Kumar: Roche-Genentech: Consultancy, Research Funding; Oncopeptides: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Merck: Research Funding; Carsgen: Research Funding; KITE: 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; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; Sanofi: Research Funding. Paludo: Karyopharm: Research Funding. Bennani: Kymera: Other: Advisory Board; Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Verastem: Other: Advisory Board. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Lin: Kite, a Gilead Company: Consultancy, Research Funding; Merck: Research Funding; Gamida Cell: Consultancy; Takeda: Research Funding; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Sorrento: Consultancy; Legend: Consultancy; Vineti: Consultancy. Murthy: CRISPR Therapeutics: Research Funding.

Use of melphalan in multiple myeloma was observed to have a deleterious effect on stem cell collection in older studies. There is limited data on the impact of melphalan in light chain (AL) amyloidosis, especially in the plerixafor era. We retrospectively evaluated stem cell mobilization in 610 patients with AL amyloidosis, of which 79 had prior exposure to melphalan, 167 to other chemotherapeutics, while 364 had no chemotherapy exposure. Collection of CD34+ stem cells × 106/kg was lower in the melphalan group. Median total yields in the melphalan, non-melphalan, and no chemotherapy groups were 5.5, 7.7, and 7.8, respectively; p 150 mg (median: three cycles) resulting in lower yields. Therefore, duration of melphalan exposure prior to stem cell collection should be limited, ideally, not exceeding more than two cycles of treatment.

Background: Systemic light chain (AL) amyloidosis is a plasma cell disorder characterized by multisystem deposition of misfolded immunoglobulin light chains produced by clonal plasma cells. Hematologic and organ responses with treatment have been shown to correlate with survival as early as 3 months from initiation of first-line treatment. Our group recently developed and validated a model integrating organ and hematologic responses for assessment of treatment outcomes at 6 months. Although current organ response criteria do not consider the depth of organ response, this has been shown to have prognostic utility in newly diagnosed patients. So, we designed this study to evaluate a composite hematologic and organ scoring system that also considers the depth of organ response at 1 to 6 months from initiation of first-line treatment. Methods: We included patients with AL amyloidosis who had at least one major organ involvement (cardiac, renal and/or liver involvement) and who had not started a second line treatment by 6 months from the time of initiating first-line treatment. For each patient, we calculated an organ response score and a hematologic response score at 1, 2, 3, 4, 5, and 6 months from initiation of first-line treatment. A score was assigned for each depth of hematologic response as follows: complete response=0, very good partial response=1, partial response=2, and no response/progressive disease=3). To calculate organ response, a score was assigned to each organ based on the depth of organ response (Muchtar et al. 2018): non-evaluable=0, complete response=1, very good partial response=2, partial response=3, and no response=4. The final organ response score was obtained by calculating the average of the individual involved organ scores. We then calculated the composite hematologic and organ response (HOR) score by adding the organ and hematologic responses at each interval and compared overall survival (OS) between patients with HOR score ≤ 5 (group 1) and those with score > 5 (group 2). Results: The cohort included 730 patients diagnosed with AL amyloidosis between February 10 th, 2006 and July 9 th, 2019. Median age was 63 (IQR: 56-69), and 65% were male. The involved light chain was Lambda in 75% of cases. Cardiac, renal, and liver involvement were found in 81%, 61%, and 17% of patients, respectively. Among all patients, 28% underwent autologous stem cell transplantation during their disease course. The median follow up in the entire cohort was 7.0 (95%CI: 6.4-8.0) years and OS was 3.6 (95%CI: 2.6-4.4) years. At 1 to 4 months, we observed a statistically significant difference in OS between patients with HOR score ≤5 vs. >5. However, there was no difference in OS between the 2 groups at 5 and 6 months. These results are presented in Table 1. Conclusion: A composite hematologic and organ response score that takes into consideration the depth of organ response can discriminate 2 groups of patients with distinct survival outcomes as early as 1 month from treatment initiation and maintains its predictive ability for up to 4 months. The lack of predictive ability beyond 4 months in this study may be due to limited sample size especially in group 2 as more patients achieve deeper responses with time. This approach can provide the basis for early changes in treatment but needs validation in future studies. Figure 1 Figure 1. Disclosures Dispenzieri: Janssen: Consultancy, Research Funding; Takeda: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Kapoor: Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Glaxo SmithKline: Research Funding; Pharmacyclics: Consultancy; Amgen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy; BeiGene: Consultancy; Regeneron Pharmaceuticals: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dingli: GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Alexion: Consultancy. Kumar: Oncopeptides: Consultancy; Merck: Research Funding; Antengene: Consultancy, Honoraria; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Carsgen: Research Funding; Tenebio: Research Funding; Celgene: 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; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: 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.

Introduction: Factors contributing to the antitumor activity of systemic oncolytic virotherapy (OV) include (i) generalized innate immune activation due to virus infusion; (ii) direct oncolytic and/or immune-mediated destruction of OV infected tumor cells due to intratumoral spread of the virus infection; (iii) collateral boosting of tumor antigen-specific T cell responses that target uninfected tumor cells. We investigated the relative contributions of these 3 factors T cell lymphoma (TCL) patients (pts) responding to a single intravenous infusion of Voyager-V1, an oncolytic vesicular stomatitis virus (VSV) encoding IFNβ and sodium iodide symporter (NIS) on NCT03017820. Of relevance, the virally encoded IFNβ enhances tumor specificity, boosts proinflammatory activity & serves as a convenient serum biomarker of infection. Methods: In a first in human trial, a single infusion of Voyager-V1 was administered to 15 pts with relapsed refractory hematologic cancers; 4 dose levels (DL) were tested (5x10 9, 1.7x10 10, 5x10 10, 1.7x10 11 TCID50); 7 pts had TCL. Cytokine levels and CRS symptoms were determined as a measure of generalized immune activation; serum IFNβ levels were monitored as a pharmacodynamic biomarker of virus infection; antitumor T cell responses were measured using ELISPOT assays. Results: Of 8 TCL pts, 3 had RECIST responses: PR at DL 2, a CR & PR at DL 4. Most pts experience short lived CRS typically resolving within 24 hours of virus infusion. Serum IFNβ levels increased post-therapy in all pts, typically peaking by 24 hours post virus infusion and returning to baseline by median day 10. T cell responses could not be accurately determined in most cases due to suboptimal T cell viability and/or function after thawing of frozen PBMC. Factors contributing to tumor regression in each of the responding pts appeared to differ significantly, as exemplified by the case reports below. Pt (I) with CTCL experienced grade 1 CRS followed by brisk regression of multiple cutaneous lesions. The PR lasted 3 mo, after relapse of an eye lesion, but responses at other sites deepened after the relapsed lesion was irradiated; pt remained off active therapy for the next 2 yrs. Peak serum IFNβ 4 hours post infusion was only 182 pg/ml suggesting that disease response may have been driven by nonspecific innate immune activation associated with the virus infusion. Pt (IV) (CD30+ PTCL/ cutaneous relapse) had short lived grade 2 CRS, then developed signs of IFNβ toxicity with AST elevation and thrombocytopenia. Oral ruxolitinib was administered for 5 days as IFNβ toxicity mitigation leading to normalization of AST and platelets. All PET-avid tumors regressed completely. This CR continues 16 months post virus infusion. Peak serum IFNβ was 18,213 pg/ml strongly suggesting that response was driven by extensive intratumoral amplification of the virus and oncolytic tumor destruction. Robust CTL responses to tumor neoantigens were detected in this pt at baseline indicating that collateral boosting of tumor-specific T cells may have been responsible for the long term maintenance of this CR Pt (V) (CD30+ PTCL) had short lived grade 2 CRS followed by response at all disease sites (including complete normalization of an enlarged FDG-avid spleen). Her PR ended after 6 months due to relapse in cervical lymph nodes. Peak serum IFNβ level was modest, 600 pg/ml & sustained over 48 hours suggesting slower intratumoral spread of the virus infection. The deepening of the response long after resolution of the oncolytic phase points strongly to a contribution from antitumor CTL but the assay was technically unsatisfactory in this pt. Conclusion: Analysis of the correlative data supports that intravenous Voyager-V1 therapy can recruit diverse antitumor effector mechanisms to impact tumor response in pts with heavily pretreated TCL. Importantly, intratumoral virus amplification, which results in high circulating concentrations of IFNβ, does not necessarily lead to tumor regression perhaps because of defective immune cell recruitment and/or activation in some tumors but not in others. This will be further evaluated in future study participants by performing CTL assays on fresh, rather than frozen PBMC. In conclusion, a single IV infusion of Voyager-V1 shows highly promising activity against treatment refractory TCL and should be further advanced as a new single-shot or combination therapy for this therapeutically challenging indication. Figure 1 Figure 1. Disclosures Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Paludo: Karyopharm: Research Funding. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Bennani: Kymera: Other: Advisory Board; Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Verastem: Other: Advisory Board. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Gertz: Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: Janssen: Consultancy; Sanofi: Consultancy; GSK: Consultancy; Apellis: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Tenebio: Research Funding; Novartis: Research Funding; Bluebird Bio: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, 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; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Bergsagel: Oncopeptides: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Janssen: Consultancy, Honoraria. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Lin: Sorrento: Consultancy; Vineti: Consultancy; Legend: Consultancy; Novartis: Consultancy; Bluebird Bio: Consultancy, Research Funding; Merck: Research Funding; Juno: Consultancy; Celgene: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cell: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding. OffLabel Disclosure: VSV-IFNβ-NIS is an oncolytic virus in clinical trial for systemic administration in hematologic malignancies

Introduction: Smoldering multiple myeloma (SMM) prognostication models routinely used in clinical practice were developed for use at diagnosis. However, retrospective studies have shown that in SMM patients the risk of progression to multiple myeloma (MM) decreases over time. Therefore, this study assessed whether the Mayo 2018 and IMWG 2020 scores could be used dynamically to risk stratify patients post-diagnosis, and whether they could identify SMM patients with evolving disease. Methods: We retrospectively studied 704 SMM patients diagnosed between January 2000 to January 2020. Patients with a baseline FLCr ≥100 and involved FLC ≥10 mg/dL or baseline bone marrow plasma cells ≥60% were excluded. We collected serial laboratory data and available pathology data and re-applied the Mayo 2018 and IMWG 2020 SMM risk stratification models at annual landmark timepoints up to 5 years post SMM diagnosis. Survival analyses were performed using the Kaplan-Meier method. Time to progression (TTP) was defined as time from diagnosis or landmark timepoint to treatment initiation for MM or systemic AL amyloidosis. Cox proportional hazards models were used to estimate hazard ratios. A two-sided p-value Results: At SMM diagnosis, 271 (38%) patients were low risk, 228 (32%) were intermediate risk, and 205 (29%) were high risk per the Mayo 2018 score. Applying the IMWG 2020 score at diagnosis, 90 (34%) of patients were low risk, 111 (42%) were low-intermediate risk, 54 (21%) were intermediate risk, and 9 (3%) were high risk. The Mayo 2018 and IMWG 2020 risk scores was re-assessed annually post-diagnosis in patients without progression (respective sample sizes: n=430 and n=197 at year 1 landmark, n=326 and n=143 at year 2 landmark, n=260 and n=106 at year 3 landmark, n=203 and n=73 patients at year 4 landmark). The Mayo 2018 and IMWG 2020 models reliably stratified patients based on progression risk post diagnosis (as shown in Figure 1 and Figure 2, respectively). As shown in Figure 1, if only diagnostic values were used in risk categorization with the Mayo 2018 model, the TTP between risk categories became less distinct over time. However, when follow-up laboratory values were used to re-stratify patients, the TTP between risk categories was more consistent over time. The respective 2-year progression risk in Mayo 2018 high-risk versus IMWG 2020 intermediate-high risk patients was 51% versus 62% at the 1-year landmark, 60% versus 65% at the 2-year landmark, 47% versus 62% at the 3-year landmark, and 47% versus 45% at the 4-year landmark. To assess the prognostic significance of an increase in SMM risk category, we stratified patients based on whether the SMM risk category at follow-up had increased versus was stable or decreased compared to the baseline SMM risk stratification. We found that patients evolving to a risk category during follow up consistently had an increased risk of progression compared to patients with a stable/decreased risk categorization using both the Mayo 2018 (HR 3.34, 95% CI 2.04-5.48, p Conclusions: Our findings support the use of the Mayo 2018 and IMWG 2020 scores post-diagnosis. We showed that patients migrating to a higher risk category have an increased risk of progression. This suggests that if patients evolve to a high-risk score during follow-up, they should be considered for an early intervention treatment approach. Figure 1 Figure 1. Disclosures Kapoor: Sanofi: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Karyopharm: Consultancy; Cellectar: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Pfizer: Research Funding; Janssen: Consultancy, Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy. Gertz: Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: Janssen: Consultancy; Sanofi: Consultancy; Apellis: Consultancy; Novartis: Research Funding; Alexion: Consultancy; GSK: Consultancy. Kumar: Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; KITE: 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; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Beigene: Consultancy; 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: MASS-FIX is a screening method for serum and urine monoclonal proteins in multiple myeloma and related plasma cell disorders, which uses immunoglobulin enrichment coupled with matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MALDI-TOF). In addition to superior sensitivity over conventional gel-based techniques, MASS-FIX can distinguish therapeutic monoclonal antibodies (MoAb) from patient's M protein. As the utilization of therapeutic MoAbs increases, it is essential to understand the persistence pattern of these therapeutic antibodies in the serum. We designed this study to evaluate the duration of daratumumab detection by MASS-FIX in the serum of treated patients. Methods: We used a prospectively maintained database at Mayo clinic to identify patients with multiple myeloma and related plasma cell disorders who were treated with a daratumumab-containing regimen anytime during their disease course and had serial MASS-FIX data available after discontinuation of daratumumab. A univariate analysis was performed to assess for factors that may impact the clearance of daratumumab. Results: We included 125 patients with plasma cell disorders who received daratumumab as first or subsequent line of treatment between March 15 th, 2016, and March 4 th, 2020. The median age was 60.2 years and 57% were male. The most common diagnoses were multiple myeloma (70%) and light chain amyloidosis (18%). Daratumumab-based treatments were initiated after a median of 28.8 (IQR: 6.4-76.3) months from initial diagnosis. The most common regimen used was daratumumab, bortezomib and dexamethasone (23%); 26% underwent transplant after daratumumab-based induction. The median duration of treatment with a daratumumab-based regimen was 208 (IQR: 99-479) days. The median follow-up from the time of daratumumab discontinuation was 457 (95% CI: 346-NR) days. By last follow up, daratumumab was not detected by MASS-FIX in 93 (74%) patients but remained detectable in 32 (26%) patients. The median time from daratumumab discontinuation to disappearance of daratumumab by MASS-FIX was 160 (IQR: 107-233) days. On univariate analysis, the presence of ≥0.5 grams of urine protein was associated with earlier disappearance of daratumumab on MASS-FIX [risk ratio (RR): 2.0, P=0.02). The median time from daratumumab discontinuation to disappearance of daratumumab on MASS-FIX was 116 (95%CI: 76-160) days in patients with urine protein ≥0.5 grams and 203 (95%CI: 162-216) days in patients with urine protein 2weeks) (RR: 1.0, P=0.97), treatment duration ( Conclusion: The therapeutic monoclonal antibody daratumumab remains detectable in the serum of treated patients by MASS-FIX for several months after discontinuation and the duration varies between individual patients. This data has implications for diagnostic and monitoring testing and may provide guidance for reuse of daratumumab in clinical trials and practice. Proteinuria is associated with earlier disappearance of daratumumab by MASS-FIX and may have implications in patients with amyloidosis and monoclonal immunoglobulin deposition disease (MIDD). Further studies are needed to identify additional factors associated with the timing of disappearance. Disclosures Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Dingli: Alexion: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; GSK: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck: Research Funding; Roche-Genentech: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Astra-Zeneca: 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; BMS: Consultancy, Research Funding; Carsgen: Research Funding; Tenebio: 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.

Introduction Multiple myeloma (MM) is frequently accompanied by renal impairment (RI) in 30-40% patients at presentation (Dimopoulos et al, IMWG 2010). As per International Myeloma Working Group (IMWG), RI is defined as Creatinine clearance (CrCl) Methods We retrospectively reviewed records for MM patients with a new diagnosis of MM who were seen at Mayo Clinic, Rochester between 1/2004 and 12/2018. RI was defined as per IMWG criteria. Categorical variables were compared using chi-square test and continuous variables using Wilcoxon test. Overall Survival (OS) was estimated using Kaplan-Meier method and difference between groups was assessed using log-rank test. Results In our cohort of 2702 patients, median age at diagnosis was 65 (range, 22-96) years and 61% were males. Number of patients with CrCl RI was present in 557 (21%) of patients at the time of presentation. On univariate analysis, factors significantly associated with RI at diagnosis were higher age, ECOG PS ≥2, hemoglobin< 10 g/dL, calcium >11 mg/dL , LDH >222 U/L, β-2-microglobulin >5.5 mg/L, free light chain ratio >100, uric acid >8 mg/dL, higher ISS stage and cytogenetics [gain 1q, t (14;20), absence of any trisomy] as shown in table 1. However, on multivariate analysis, only elevated serum calcium >11 g/dL (OR: 11.5; 95%CI:1.78-74.9; p=0.01) and free light chain ratio>100 (OR: 4.17; 95%CI:1.29-13.4; p=0.016) had significant association with RI. The RI group had inferior OS when compared to patients with no RI at diagnosis (4.5 years vs 7.7 years, p-value Looking at trends over time, the rate of RI at presentation had not changed. Over the last two decades, OS for the CrCl Conclusion In our cohort of 2702 patient, frequency of RI at baseline was 21%, which corroborates with previous studies. Hypercalcemia and serum free light chain ratio were found to be independent factors associated with RI. RI at diagnosis is associated with inferior survival, however, use of novel agents in this population has led to improvement of patient outcomes. Figure 1 Figure 1. Disclosures Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Dingli: Alexion: Consultancy; Novartis: Research Funding; Apellis: Consultancy; GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy. Kumar: Roche-Genentech: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Novartis: Research Funding; Merck: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Bluebird Bio: Consultancy; Oncopeptides: Consultancy; Carsgen: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Background: Achievement of a complete response (CR) to therapy in multiple myeloma (MM) early in disease course correlates with improvement in clinical outcomes, reflective of therapeutically sensitive disease biology. While depth of response is known to impact overall survival (OS) and progression-free survival (PFS), the effect of known prognostic variables at baseline including FISH risk and International Staging System (ISS) score outside of clinical trial settings is not well described. We sought to determine the impact of known prognostic variables in MM including FISH and ISS risk in the context of NDMM patients achieving a CR to therapy and to also examine additional predictors of outcome among this cohort. Methods: A retrospective study was conducted on 1869 NDMM patients who had ≥ 2 consecutive monoclonal protein immunofixation (IFE) studies in the serum and urine available within 24 months from diagnosis. We identified the number of patients who had ≥ 2 negative serum and urine IFE as a surrogate for achieving CR (N=461), since a bone marrow biopsy is not routinely performed to confirm CR in the non-trial setting. A Kaplan-Meier model was used to compare median PFS and OS between patients achieving a CR vs. non-CR and a multivariate analysis was performed to adjust for known prognostic variables. A cox proportional hazards model was used to determine the prognostic impact of baseline FISH (high risk vs. standard risk) and ISS scores (3 vs.1 and 2) on PFS and OS, among patients achieving a CR vs. non-CR, and identify additional prognostically significant variables within the CR cohort. Results: The median length of follow-up for the entire cohort (n=1869) was 64 months (range: 1-199). The median time from diagnosis to achievement of CR among the CR cohort was 9.8 months (0.20-23.8 months). The median PFS for CR (n=461) vs. non-CR (n=1408) patients was 42.0 vs. 29.3 months (p 75 years, HR 2.7 (1.54-4.8; p=.0005); male gender, HR 1.5 (1.1-2.02; p=.008); serum albumin Conclusion: Attainment of an early CR in NDMM confers improvement in PFS and OS. Our study confirms these findings and suggests that achievement of CR neutralizes the impact of baseline FISH and ISS risk on PFS and OS. Among the CR cohort, age> 75 years, male sex, non-IgG involved heavy chain, and hypoalbuminemia at the time of CR predict for inferior overall survival. Figure 1 Figure 1. Disclosures Dingli: Sanofi: Consultancy; Alexion: Consultancy; Novartis: Research Funding; GSK: Consultancy; Apellis: Consultancy; Janssen: Consultancy. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Dispenzieri: Alnylam: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Lin: Vineti: Consultancy; Bluebird Bio: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Juno: Consultancy; Merck: Research Funding; Sorrento: Consultancy; Celgene: Consultancy, Research Funding; Gamida Cell: Consultancy; Novartis: Consultancy; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Legend: Consultancy. Kumar: Merck: Research Funding; Antengene: Consultancy, Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; KITE: Consultancy, 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; Bluebird Bio: Consultancy; Tenebio: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Roche-Genentech: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Introduction: Chimeric antigen receptor T-cell (CAR-T) therapy is an effective treatment that has transformed hematologic malignancy management. However, its significant short-term toxicities, mainly cytokine release syndrome (CRS) and neurotoxicity, require frequent monitoring almost universally achieved via prolonged inpatient admissions. We have reported our institution's specialized, multi-disciplinary hospital-based outpatient (HBO) CAR-T service and experience (Bansal et.al, ASCO 2021). To enhance the HBO practice, we implemented a remote patient monitoring (RPM) program, comprised of in-home, electronic health record-integrated technology to monitor vital signs and neurologic symptoms for 30 days post CAR-T infusion. The RPM program's triaging algorithm generates alerts based on predetermined parameters to guide escalation of care if needed. In this report, we describe the characteristics of RPM program patients (pts), focusing on the alerts received within 48 hours (h) of first hospitalization in the post-CAR-T setting. Methods: Pts undergoing commercial CAR-T cell therapy at Mayo Clinic Rochester were enrolled in the RPM program as part of our standard of care from 06/2020 to 05/2021. Pts with detailed RPM data available were included in this analysis. Patient characteristics, health care utilization, inpatient interventions, and RPM alert data were reviewed. Wilcoxon test was used for continuous variables, chi-squared test was used for categorical variables. Results: Baseline characteristics are summarized in Table 1. Of 20 pts in this analysis, 13 had RPM alerts in the 48h preceding the first hospitalization post CAR-T. For the remaining 7 pts without RPM alerts, 3 were hospitalized within 24h of CAR-T infusion without significant RPM data, 1 patient hospitalized with acute pancreatitis (day +8 post CAR-T infusion), 1 for doubling of CRP (day +10), 1 for acute pain crisis (day +5), and 1 with neutropenic fever (day +5) with not reporting RPM data. The median RPM program duration was 18 days (range 3-32) which accounts for interruptions in the RPM monitoring while pts are hospitalized. The median number of data points per patient was 231 (range 22-532), with a median of 20 alerts per patient (range 2-81). The median missing data points per patient were 20 (10%) (range 0-95). Of the 13 pts with RPM alerts within 48h of first hospitalization, alerts met our definition of urgent criteria in 6 pts [temperature (temp) > 100F (n=3), temp > 100F + tachycardia (n=1), temp > 100F + hypoxia (n=1), and hypoxia (n=1)]. In the remaining 7 pts, the RPM alerts met our routine criteria definition [temp 99-100 (n=2), tachycardia + hypertension + weight loss (n=2), hypertension (n=2), new incontinence (n=1)]. CRS was reported in 12 pts [grade 1-2 (n=11), grade 3-4 (n=1)] and neurotoxicity in 8 pts [grade 1-2 (n=7), grade 3-4 (n=1)]. The median post CAR-T first hospitalization day was day +4 (range day +2-10), Figure 1. The median time from the last RPM alert to hospitalization was 5.8h for pts meeting urgent criteria vs 10.8h for those meeting routine criteria (p=0.13). Tocilizumab was used in 5 pts during the first hospitalization [3 (50%) in the urgent criteria group and 2 (28%) in the routine criteria group], with a median time from admission to tocilizumab of 12h in the urgent criteria group vs 43h in the routine criteria group (p=0.05). Early hospitalization (≤ 3 days) post CAR-T infusion was associated with later need for tocilizumab [median 51h (range 30-57) vs. 11.5h (range 6-33) from admission, p=0.03] than late hospitalization (> 4 days post CAR-T). Upon admission, oxygen supplementation was started on both pts with hypoxia noted in the RPM alerts. Only 1 patient (routine criteria group) required use of vasopressors while hospitalized, initiated more than 48h after admission. Conclusion: A CAR-T RPM program can identify adverse symptoms and vital sign changes in CAR-T pts managed in the outpatient setting. In this pilot implementation, the CAR-T RPM triaging algorithm identified pts requiring expedited hospitalization and facilitated early initiation of tocilizumab. The intermittent monitoring and proportion of missing data are the main limitations of the RPM in the acute care setting post-CAR-T infusion. Incorporation of wearable devices for continuous remote monitoring is being explored as a mitigating strategy to these limitations. Figure 1 Figure 1. Disclosures Paludo: Karyopharm: Research Funding. Dingli: Apellis: Consultancy; Janssen: Consultancy; GSK: Consultancy; Novartis: Research Funding; Sanofi: Consultancy; Alexion: Consultancy. Kapoor: Glaxo SmithKline: Research Funding; Sanofi: Consultancy; Amgen: Research Funding; AbbVie: Research Funding; Sanofi: Research Funding; Karyopharm: Research Funding; Ichnos Sciences: Research Funding; Pharmacyclics: Consultancy; Takeda: Research Funding; Regeneron Pharmaceuticals: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy. Gertz: Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Wang: InnoCare: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Genentech: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kenderian: Humanigen, Inc.: Consultancy, Honoraria, Research Funding. Kumar: Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Oncopeptides: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Bluebird Bio: Consultancy; Beigene: Consultancy; Tenebio: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Lin: Merck: Research Funding; Vineti: Consultancy; Gamida Cell: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Legend: Consultancy; Celgene: Consultancy, Research Funding; Sorrento: Consultancy; Takeda: Research Funding; Janssen: Consultancy, Research Funding; Novartis: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding.

Background: Chimeric antigen receptor T cell therapy (CAR-T) is a recent therapeutic advance for the treatment of myeloma. Among the FDA approved and investigational CAR-T, primary refractory disease post CAR-T infusion is uncommon, however most patients eventually relapse. To gain insight to the myeloma cell and immune cell characteristics associated with early relapse (PD) versus durable response (DR), we examined myeloma cells and immune cells in both the bone marrow and blood by single cell RNA-seq. Method: Bone marrow aspirate and blood samples were collected prior to BCMA targeted CAR-T therapy. CD138 + and CD138 neg cells from bone marrow (BM) and peripheral blood mononuclear cells (PBMNC) were collected for 5' based scRNA-seq (10X Genomics). CD138 + cells were clustered by Harmony integration. Top expressing genes in unique clusters for PD and DR were analyzed by Ingenuity Pathway Analyses. To profile CD138 neg BM cells and PBMNC from myeloma patients, the scRNA-seq dataset was mapped to the human PBMC reference using the Seurat v4 reference-guiding approach. Differential gene expression between responders and non-responders was performed using the FindMarkers function for each of the immune cell clusters in the BM and PB. Results: BM and PB samples from 15 patients were analyzed. Among these, 5 patients had relapsed disease more than 1-year post CAR-T infusion (Durable Response, DR), and 10 patients had relapse within 1 year (early relapse, PD). Among these, CD138+ cells were available from 3 DR and 4 PD for analysis. Multimodal expression of BCMA were seen among the CD138+ cells across all samples. Using the mode of the highest expression level as a cut-off, patients with DR had a trend toward having higher fraction of BCMA high CD138+ cells compared to pts with PD. Clustering of all CD138+ cells by Harmony integration identified 12 distinct clusters, among which two clusters were unique to pts in DR, and one was unique to patients in PD. Ingenuity pathway analysis identified the top marker genes in these 3 clusters to be enriched in pathways for IL-15 signaling, BCR signaling, and primary immunodeficiency signaling. (Figure 1A-E.) Differential gene expression for immune cell clusters from CD138 neg BM cells and PBMNC were compared between pts in PD and DR. Interestingly, different patterns were seen in immune cells in PB and BM (Figure 1G). For example, compared to pts in PD, those with DR had decreased signaling in CD16 PB monocytes for interferon signaling and differentiation to macrophages, whereas the CD16 monocytes in the BM in pts in DR had increased expression of mitochondrial genes for anti-oxidant stress, polarization to M1 macrophage and anti-apoptosis. Similarly, pts in DR had CD8 Tcm in the BM with increased expression of genes involved in cell adhesion and anti-apoptosis, and CD4 Tcm in the BM with increased expression of genes in protein metabolism. Conclusion: scRNAseq analysis of myeloma cells suggest different tumor transcriptome profile may be identified in myeloma cells that could relapse early after CAR-T therapy. In addition, host immune profile both in the BM microenvironment and in systemic PB circulation could be associated with durable clinical response. Figure 1 Figure 1. Disclosures Kapoor: Pharmacyclics: Consultancy; Glaxo SmithKline: Research Funding; Amgen: Research Funding; Sanofi: Research Funding; AbbVie: Research Funding; Ichnos Sciences: Research Funding; Sanofi: Consultancy; Regeneron Pharmaceuticals: Research Funding; Takeda: Research Funding; Karyopharm: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy. Dingli: GSK: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Alexion: Consultancy. Kumar: Bluebird Bio: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: 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; Tenebio: Research Funding; Novartis: Research Funding; BMS: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Carsgen: Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; Amgen: Consultancy, Research Funding; Merck: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Lin: Merck: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Takeda: Research Funding; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Sorrento: Consultancy; Juno: Consultancy; Legend: Consultancy; Gamida Cell: Consultancy; Vineti: Consultancy; Novartis: Consultancy; Janssen: Consultancy, Research Funding.

Background Multiple Myeloma (MM) remains incurable with current approaches and eventually relapses in nearly all patients. At relapse, patients may present with increasing serum and/or urine monoclonal (M) protein or with clinical features suggestive of progression. The outcomes of different progression patterns need to be better understood to provide insight about the optimal time to intervene with salvage therapy. This study aimed to describe the prevalence and outcome of biochemical (BP) versus clinical progression (CP) in a real-world setting. Methods We retrospectively assessed 1347 relapsed MM patients seen at Mayo Clinic between February 2001 and December 2018. CP was defined as per IMWG criteria (increase ≥50% in size or new plasmacytomas/bone lesions, hypercalcemia ≥11.5 mg/dl, decrease in hemoglobin ≥2 g/dl or to ≤10 g/dl, rise in serum creatinine ≥2g/dl, hyperviscosity), while BP was defined as increase in serum or urine M protein leading to initiation of a new line of therapy without meeting criteria for CP. Aggressive relapse was defined as new extramedullary disease (EMD), plasma cell leukemia or hyperviscosity requiring plasmapheresis. The overall survival (OS) was defined as the time from 1 st relapse to last follow-up or death. Time to next treatment (TTNT) was defined as the time between initiation of 2 nd and 3 rd line therapy. Results Prevalence of different patterns of relapse is presented in Table 1. The majority of progressions were BP (60.4%); among the CP (39.6%), the most common presentation was a new bone lesion. Similar proportions of BP and CP patients were diagnosed before 2013 (70% and 73%; p=0.2). The median time from diagnosis to 1 st relapse was 22.8 months (range, 0.4-154.7) and was shorter in the CP group in comparison to BP (20.8 [range, 1.0-152.1] vs 23.7 [range, 0.4-154.7] months, p=0.001). With the exception of ISS stage, patients in the CP group had higher risk features at MM diagnosis including: high-risk (HR) FISH ([4;14], t[14;16], t[14;20], deletion 17p or p53 mutation; 29% vs 20%, p=0.01); elevated LDH (23% vs 17%, p=0.03); and EMD (19% vs 10%, p At 1 st line, patients with eventual CP were less likely to have received novel agents (78% vs 85%, p Patients with CP had shorter median TTNT from 2 nd line therapy compared to BP (9.6 vs 17.0 months, p Using a multivariable Cox proportional hazard model, CP (vs BP) was a predictor of shorter TTNT from 2 nd line therapy (HR 1.40, 95% CI 1.20-1.62, p65 years, male sex, ISS stage III, HR FISH at diagnosis, EMD at diagnosis and relapse while on primary treatment/maintenance. Conclusions Patients with clinical features at relapse have a worse prognosis after 1 st relapse than patients who relapsed solely biochemically. Approximately half of CP presented while on active treatment, which suggests that even patients monitored closely may develop CRAB features at relapse. Factors that help predict the occurrence of CP include male sex, PCLI ≥2% and EMD at diagnosis. Patients with deeper response to 1 st line treatment are less likely to develop CP. Figure 1 Figure 1. Disclosures Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Pfizer: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding; Alnylam: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Dingli: Apellis: Consultancy; Sanofi: Consultancy; GSK: Consultancy; Novartis: Research Funding; Alexion: Consultancy; Janssen: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Sanofi: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Tenebio: Research Funding; Beigene: Consultancy; Celgene: 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; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding.

Background Recommendations for 2 nd line treatment for relapsed multiple myeloma (MM) patients have been changing over the past two decades, given the introduction of novel agents, different side-effect profiles, and attempts at more individualized treatment approaches. We designed this study to characterize how 2 nd line treatment strategies have evolved over the last two decades for MM patients. Methods Patients with MM with at least one relapse treated with a 2 nd line regimen, seen at Mayo Clinic between 2003-2021, were included. To visualize trends in treatment choices we divided the study period into 2-year intervals and for descriptive purpose the period was divided into three 6-year intervals. We used "100% stacked area" charts to show how the constituent parts of the whole have changed over time. The height of each colored stack represents the proportion of patients in that category at a given point in time. Results A total of 1439 patients were included. Patients were diagnosed between 2001 and 2018, the initiation of 2 nd line treatment occurred between June 2003 and February 2021. Median age at diagnosis was 62.7 years (interquartile range, 55.8-69.3), 60.0% were male. International Staging System stage I was present in 23.5% of patients, stage II in 32.9% and stage III in 28.8%. In the 1 st line therapy novel agents were used in 82.8% of cases, regimens based on proteasome inhibitors (PI) in 26.5%, immunomodulatory drugs (IMID) in 42.0% and combination of PI+IMID in 21.1%. Upfront autologous stem cell transplantation (ASCT) was performed in 50.1% of patients, and maintenance after 1 st line was used in 25.2%. For 2 nd line treatment, during 2003-2008 the majority were treated with doublets (70.5%), followed by triplets (14.8%) and salvage ASCT (7.7%) (Figure 1A). Patients were treated with IMID or PI-based therapy (50.7% and 21.8%, respectively); only 3.7% received PI+IMID and 20.1% of patients received alkylating agents/anthracyclines. The most frequently used regimens were lenalidomide-dexamethasone (RD, 32.2%) and bortezomib-dexamethasone (VD, 18.1%, Figure 1B). Between 2009-2014, the use of triplets in 2 nd line increased (43.0%), although doublets were still more common (50.9%). Like previous years, IMID-based therapy was most frequently used (37.3%), however, the use of PI-based therapy increased (36.0%). PI+IMID-based therapy was implemented in 17.9% of patient, and 27.3% received alkylating agents/anthracyclines. Most frequently used regimens included: RD (29.4%), bortezomib-cyclophosphamide-dexamethasone (CYBORD, 17.4%), bortezomib-lenalidomide-dexamethasone (VRD, 13.4%) and VD (13.3%). Finally, during 2015-2021, triplets were most common (68.9%), followed by doublets (23.0%). IMID- and PI+IMID-based therapies were most often implemented (34.2% and 31.1%, respectively), followed by PI-based therapy (26.8%). 28.1% of patients received monoclonal antibodies; only 15.9% received alkylating agents/anthracyclines. Most frequently used regimens include RD (13.8%), carfilzomib-RD (11.6%), daratumumab-RD (9.8%), CYBORD (9.3%), VRD (8.8%), daratumumab-pomalidomide-dexamethasone (5.9%) and daratumumab-VD (5.2%). Median time to next treatment (TTNT) from 2 nd line therapy has improved over the course of the three time periods (p Conclusions Over the past two decades, the effectiveness of 2 nd line treatment has improved, reflected by improved TTNT from 2 nd line therapy. With the introduction of new agents in 2012-2015 (carfilzomib, pomalidomide and daratumumab) and favorable results for triplets demonstrated in randomized trials, the triplet therapies started to be used more frequently. Over time, the landscape of 2 nd line therapies has become more diverse, which may reflect a more individualized approach to each patient. Moreover, the large variety of treatment strategies makes comparisons more and more challenging. Figure 1 Figure 1. Disclosures Kapoor: Ichnos Sciences: Research Funding; Karyopharm: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Cellectar: Consultancy; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: Sanofi: Consultancy; Apellis: Consultancy; Novartis: Research Funding; Alexion: Consultancy; Janssen: Consultancy; GSK: Consultancy. Kumar: Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Tenebio: Research Funding; Carsgen: Research Funding; Beigene: Consultancy; Antengene: Consultancy, Honoraria; Roche-Genentech: Consultancy, Research Funding; Janssen: Consultancy, 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; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Novartis: Research Funding; Sanofi: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy.

Background: The use of immunotherapeutic agents in multiple myeloma (MM) has shown improvements in clinical outcomes, emphasizing the role the host immune system plays in disease control. In recognition of this relationship, efforts aimed at identifying biomarkers of immune surveillance in MM have identified prognostic value in the peripheral absolute lymphocyte (ALC) and absolute monocyte (AMC) counts at various stages of disease and following autologous stem cell transplant (ASCT), with lower ALC and AMC serving as a surrogate for immune dysregulation and correlating with inferior progression free (PFS) and overall survival (OS). With ASCT remaining the standard of care in the treatment of MM, we sought to examine whether CD3 content of the apheresis product during stem cell collection could be used as a biomarker for immune competence and whether it influences outcomes. Methods: A retrospective study was conducted on 1086 MM patients who underwent stem cell (CD34) collection with available CD3 data and subsequent ASCT at our institution. We recorded the total absolute CD3 and CD34 cell count upon completion of mobilization, with a higher CD3 count serving as a surrogate for immune competence. In addition to investigating the absolute CD3 count, we calculated the CD3/CD34 ratio given variation in the CD34 goals. Patients were dichotomized based on whether their absolute CD3 and CD3/CD34 ratio values were above or below medians. A Kaplan-Meier model was used to compare median PFS and OS between groups. A cox proportional hazards model was used to determine its prognostic impact, adjusting for ISS stage 3, high risk FISH, achievement of CR near day 100, and maintenance therapy received post-ASCT. Results: The median length of follow-up from date of ASCT for the entire cohort (N=1086) was 34.1 months (range: 0.26-157 months) and the median time from stem cell collection to ASCT was 9 days (range: 3-3143 days). The most common mobilizing regimen was Neupogen and plerixafor (N=425, 39%) and 694 (64%) patients received ASCT in the first line setting. The median absolute total CD3 count was 4.3 x 10^6/kg (range: 0.1-21.9) with 542 patients above and 544 patients at or below the median. The median absolute total CD34 count was 8.53 x 10^6/kg (range: 0.2-37.0) and median CD3/CD34 ratio was 0.50 (range: 0.01-15), with 536 patients above and 550 patients at or below the median ratio. The median PFS among patients with a CD3 count > 4.25 x 10^6/kg was 23.1 vs. 16.9 months among patients with CD3 count ≤ 4.25 x 10^6/kg (p 0.5 (Figure 1). The prognostic value among patients with a CD3/CD34 ratio > 0.5 was retained after adjusting for ISS stage III, high risk FISH features, and use of maintenance therapy as follows: PFS HR: 0.73 (95% CI: 0.62-0.86; p=0.0002); OS 0.71 (95% CI: 0.59-0.88; p=0.001). Conclusions: Our study demonstrates that patients who have higher CD3 content in their apheresis product have better PFS and OS following ASCT. These findings reveal a possible role for using absolute CD3 and CD3/CD34 ratios in the apheresis product as a surrogate marker for immune competence and in predicting clinical outcomes. Figure 1 Figure 1. Disclosures Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Alexion: Consultancy; Apellis: Consultancy; Novartis: Research Funding. Dispenzieri: Takeda: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Sanofi: Research Funding; Takeda: Research Funding; Ichnos Sciences: Research Funding; Glaxo SmithKline: Research Funding; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding. Kumar: Novartis: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Tenebio: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; BMS: Consultancy, Research Funding; Oncopeptides: Consultancy; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Background: Patients with multiple myeloma (MM) that are refractory to a proteasome inhibitors (PI), immunomodulatory drug (IMiDs) and CD38/SLAMF7 directed monoclonal antibodies are commonly referred to as triple class refractory (TCR). This is an increasingly common clinical problem and here we present the outcomes, prognostic markers and response to therapy for patients with TCR disease. Methods: Consecutive patients with MM diagnosed between 01/01/2013 and 12/31/2018 and seen at Mayo Clinic, Rochester, MN were included in this study after institutional review board approval. Refractoriness to therapy was defined as progression or non-responsiveness (failure to achieve at least a minimal response) to therapy within 60 days of discontinuation of therapy, based on the International Myeloma Workshop Consensus definition. Patients meeting the definition for refractory disease for at least 1 PI (bortezomib, carfilzomib or ixazomib), 1 IMiD (lenalidomide, pomalidomide or thalidomide) and 1 monoclonal antibody (daratumumab, isatuximab or elotuzumab) were considered to have TCR disease and included in the study population. The first date when patients satisfied the above-mentioned criteria for TCR was used to calculate the follow-up, progression free survival (PFS) and OS for TCR disease. The mSMART 3.0 (www.msmart.org) classification was used to characterize high-risk and standard-risk cytogenetics features in interphase fluorescence in situ hybridization (FISH). The currently prevalent international myeloma working group (IMWG) criteria were used for response assessment. The Kaplan-Meier method was used for estimation of time-to-event endpoints. Reverse censoring was used for estimation of follow-up time. Cox regression was used for multivariate analyses. Wilcoxon test was used for comparison of continuous variables and Chi square test or Fisher's exact test were used to compare categorical variables, respectively Results: In this retrospective study, 249 consecutive patients with TCR status were identified. The median follow-up from diagnosis of MM till date of last follow-up was 6.8 years (95% CI: 6.3-7.3 years) and 1.9 years (95% CI: 1.6-2.4) from TCR MM to last follow-up. The median age at diagnosis of MM was 61 years (range 31-89) and at TCR was 65 years (range 32-93). The median number of lines of therapy for the entire cohort were 8 (range 1-17); the patients were exposed to a median of 5 (range 1-12) lines of therapy prior to TCR status. Baseline characteristics for the cohort are depicted in Table 1. The median time to development of triple refractory disease was 2.9 years (95% CI: 2.6-3.2 years) from diagnosis of MM. The time to TCR disease was shorter for high-risk cytogenetics at 2.3 years (95% CI: 2-2.7) compared to 3.4 years (95% CI: 3.1-4.1) with a hazard ratio (HR) of 1.8 (95% CI: 1.4-2.4) p Conclusion: Patients with triple refractory MM have a guarded prognosis and demonstrate an underwhelming median PFS of 4 months and median OS of 1 year. Achievement of a deeper response to therapy at triple refractory status is associated with a prolonged PFS. High-risk cytogenetic features at diagnosis confer a negative prognosis in TCR patients. Newer therapies are the needed to sustain the improvement in outcomes for this group of patients. Figure 1 Figure 1. Disclosures Kapoor: Cellectar: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; BeiGene: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Takeda: Research Funding; Sanofi: Research Funding; Karyopharm: Research Funding; Glaxo SmithKline: Research Funding. Dispenzieri: Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Dingli: Apellis: Consultancy; GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Kumar: Sanofi: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Tenebio: Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Abbvie: 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; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Background: Treatment for multiple myeloma (MM) patients refractory to proteasome inhibitors (PIs), immunomodulatory agents (IMiDs), and monoclonal antibodies remains an unmet need. Belantamab mafodotin is a first in class antibody drug conjugates (ADCs) in MM utilizing a humanized monoclonal antibody targeting B cell maturation antigen (BCMA) conjugated to a microtubule-disrupting monomethyl auristatin F. The efficacy of belantamab in relapsed refractory MM (RRMM) patients has been reported in several randomized clinical trials. However, clinical trials have restricted patients' eligibilty. We report the "real world" efficacy and safety of belanatmab in patients treated at all three Mayo Clinic sites. Methods: We retrospectively reviewed all consecutive MM patients that received at least one dose of belantamab outside a clinical trial. The primary endpoints were PFS and OS, and the secondary endpoints included overall response rates (ORR) and safety. Results: Thirty-seven RRMM patients were treated with belantamab between September 2020 and June 2021. The median age at diagnosis was 61 (range 37-83) and 64% were male. The median age at belantamab administration was 67 (IQR 59-74) and 14 patients (38%) were 70 years or older. Fifteen of 34 patients (44%) had high-risk FISH and 13 patients of 33 (39%) had ISS 3. Two patients had a creatinine of >2.5 mg/dL, and one patient was on dialysis. All three received full dose belantmab (2.5 mg/kg). The median time from diagnosis to belantamab initiation was 7 years (IQR 4-11), and the median prior lines of therapy was 8 (IQR 7-11). Twenty-seven patients (73%) underwent an autologous stem cell transplantation prior to belantamab therapy, and all patients were penta refractory (IMiD, PI, and anti CD38). Seven patients (19%) received CAR-T therapy prior to belantamab. The median number of belantamab doses administered was 3 (range 1-6). Thirty-one (84%) received belantamab monotherapy and 6 patients (16%) received belantamab in combination [pomalidomide (n=3), cyclophosphamide (n=2), or thalidomide (n=1)]. The overall response (ORR) rate to belantamab was 33% (out of 36 evaluable patients). Two patients (6%) achieved complete response (CR), 3 patients (8%) achieved very good partial response (VGPR), and 7 patients (19%) achieved partial response (PR). At data cutoff 20 patients (54%) are alive. Seventeen patients died of MM complications. The median follow-up was 6 months (IQR 3.5-7). The median PFS and OS for the whole cohort was 2 months (95% CI 1-3) and 7 months (95% CI 3--NR), respectively. Two patients died within the first cycle of belantamab (due to PD), and overall, 12 died within 100 days of belantamab therapy, all due to disease progression. Eleven patients (30%) were hospitalized during belantamab therapy. The reasons for hospitalization were related to MM in 4 patients (one patient with malignant ascites, one with hypercalcemia, 2 patients for pain management). Three patients were hospitalized due to thrombocytopenia (related to disease), and one due to an infusion-related reaction (IRR). Other reasons for hospitalization were infection (soft tissue abscess, n=1), proctitis (n=1) and tumor lysis (n=1). Keratopathy developed in 16 patients (43%). Keratopathy was grade 1 in 6 patients, grade 2 in 7 patients, and grade 3 in 3 patients. Only one patient had corneal erosions and 6 patients reported decreased visual acuity, (1 grade 3 keratopathy, 4 had grade 2 keratopathy, and 1 had grade 1 keratopathy). Two patients had IRR. Two patients reported gaining 3.5 kg each after therapy with belantamab was discontinued. Conclusions: The response rates are similar to those reported in randomized clinical trials. The role of belantamab in the era of other BCMA directed therapy (CAR-T, BiTEs) remains unclear. Disclosures Dispenzieri: Janssen: Consultancy, Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Alnylam: Research Funding; Takeda: Research Funding. Kumar: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; KITE: 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; Novartis: Research Funding; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Dingli: Novartis: Research Funding; GSK: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; Alexion: Consultancy; Apellis: Consultancy. Kapoor: Cellectar: Consultancy; BeiGene: Consultancy; Sanofi: Consultancy; Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Amgen: Research Funding; Pharmacyclics: Consultancy; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option.

Background Multiple myeloma (MM) is an incurable disease, and its prognosis is largely influenced by clinicopathological features, response to therapy, and relapse characteristics. Despite novel agents and the attempts to individualize treatment strategies based on baseline risk stratification, significant variations in progression-free survivals (PFS) and overall survivals (OS) are observed between patients. We examined the outcomes of MM patients stratified according to timing of first relapse into early (5 years). Methods We retrospectively assessed 1441 MM patients seen at Mayo Clinic between 2003 and 2018. Patients were 18 years or older and had at least one disease relapse that required an additional line of treatment. The study cohort was divided into three groups based on time of first relapse: early relapse (5 years from diagnosis). The independent predictors of early/late relapse were identified using a forward stepwise multivariate logistic regression. Odds ratios in multivariate models were adjusted for age and sex. Results Early relapse has been recognized in 758 patients (52.6%), relapse between 2-5 years in 561 patients (38.9%), late relapse in 122 patients (8.5%). Six patients had a PFS >10 years. In comparison to patients with late relapse, patients with early relapse were older (median 63 vs 61 years, p=0.04), more frequently ISS stage III (40% vs 20%, p In terms of first line treatment, novel agents use was higher in early relapse group in comparison to late relapse group (82% vs 72%, p=0.007). Early relapse patients more often received PI-based therapy (30% vs 10%, p On multivariable logistic regression model early relapse (vs all remaining patients) was predicted by HR cytogenetic features (odds ratio [OR] 3.06, 95% confidence interval [CI] 1.71-5.46, p The only factor associated with decreased chances of late relapse (vs all remaining patients) on multivariate logistic regression model was the presence of HR FISH features (OR 0.18, 95% CI 0.04-0.82, p=0.03). Median PFS from first relapse for the whole population was 13.9 months (95% CI 12.9-15.1), median OS from first relapse - 44.6 months (95% CI 41.7-183.0). Early relapse group exhibited worse median PFS and OS from first relapse (median PFS 9.1 months; median OS 26.6 months) than patients who relapsed 2-5 years after diagnosis (median PFS 18.5 months; OS 71.9 months), or late relapse group (median PFS 31.6 months; median OS 87.8 months; p Conclusions Early relapse ( Figure 1 Figure 1. Disclosures Kapoor: AbbVie: Research Funding; Glaxo SmithKline: Research Funding; Takeda: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Dingli: Alexion: Consultancy; Janssen: Consultancy; Novartis: Research Funding; GSK: Consultancy; Sanofi: Consultancy; Apellis: Consultancy. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; 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; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Antengene: Consultancy, Honoraria; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Introduction: Multiple gene expression profile assays have successfully prognosticated the overall survival (OS) outcomes of patients with Newly Diagnosed Multiple Myeloma (NDMM) and are now available for use in clinical practice. The genes included in these profiles encompass several aspects of cancer biology broadly such as cell-cycle biology, energy metabolism, migration, adhesion, immune evasion etc. Since altered energy metabolism is one of the hallmarks of all cancer cells, our goal was to take a deep-dive into specific genes associated with intracellular central carbon energy metabolism (CCEM) pathways such as oxidative phosphorylation (OxPhos) as well as glycolysis and lactate fermentation (Glyco-Lac) in MM cells to determine their impact on the pathogenesis and prognosis of MM patients. Methods: Gene expression level data via RNA sequencing from the COMMPASS dataset (made available by the Multiple Myeloma Research Foundation (MMRF)) was utilized. The expression levels of all genes associated with the OxPhos (N = 118) and Glyco-Lac (N = 34) pathways were evaluated in CD138+ cells derived from patients with NDMM. Each gene was dichotomized into low and high expression groups -based on their expression level above and below the median fragments per kilobase of transcript per million (FPKM), respectively. The prognostic significance of dichotomizing each of the 152 genes in this NDMM cohort was evaluated by levels of their hazard ratios (HRs) for OS determined by the log-rank method. Genes from the OxPhos and Glyco-Lac pathways were selected based on their significant negative impact on OS, wide representation of their biologic activity throughout the pathway and high independence from each other. This resulted in the selection of 12 distinct genes of interest. A scoring system consisting of assigning a point for every gene where their FPKM was above the median yielded a minimum of 0 and a maximum of 12 for the set of genes in the OxPhos and Glyco-Lac pathways to create an energy metabolism score (EMS). Patients were then categorized into "low" (0-8) or "high" (9-12) EMS groups. In addition, patients were designated as having high-risk cytogenetics if they had any of the following: t(4;14), t(14;16), t(14;20), del17p, and Amp 1q. Survival analysis was performed using the Kaplan-Meier survival analysis and compared via the log-rank method. Finally, the distribution of the EMS score among patients within a spectrum of plasma cell disorders such as, monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma and MM as well as normal plasma cells was assessed using a previously published transcriptome dataset (GSE6477). Results: A total of 766 patients were included in this study. The selected genes included in this scoring system and their biological relevance in the OxPhos and Glyco-Lac pathways are depicted in Figure A. The distribution of low and high EMS groups across ISS stage and cytogenetic risk are depicted in Figure B and C respectively. The median OS (mOS) and PFS for the high (N = 248) vs. low (N = 518) EMS groups was 55 vs. 94 months (HR: 2.41; (95%CI: 1.85-3.14); P MGUS -> SMM -> MM) (Figure H). Conclusions: The expression levels of specific genes associated with the activity of intracellular CCEM pathways such as glycolysis, lactate fermentation and oxidative phosphorylation in plasma cells provides evidence for the impact of cellular energy metabolism on the pathogenesis and survival outcomes of MM. This provides an opportunity for developing future studies aimed at understanding the energy metabolism pathways of plasma cell malignancies in greater detail so as to exploit them for diagnostic and therapeutic purposes in MM. Figure 1 Figure 1. Disclosures Kumar: Novartis: Research Funding; Amgen: Consultancy, Research Funding; Beigene: Consultancy; Carsgen: Research Funding; Merck: Research Funding; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, 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. Dispenzieri: Alnylam: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Kapoor: AbbVie: Research Funding; Takeda: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding. Dingli: Apellis: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; GSK: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Lin: Gamida Cell: Consultancy; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Juno: Consultancy; Novartis: Consultancy; Legend: Consultancy; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Sorrento: Consultancy; Merck: Research Funding; Vineti: Consultancy. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Fonseca: Aduro: Consultancy; Kite: Consultancy; Juno: Consultancy; Merck: Consultancy; Takeda: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; AbbVie: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mayo Clinic in Arizona: Current Employment; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; GSK: Consultancy.

Background Smoldering multiple myeloma (SMM) prognostication models routinely used in clinical practice were developed for use at diagnosis. However, retrospective studies in SMM patients have shown that the risk of progression to multiple myeloma (MM) decreases over time. Therefore, this study assessed whether the Mayo 2018 and IMWG 2020 scores could be used dynamically to risk stratify patients post-diagnosis, and whether they could identify SMM patients with evolving disease markers. Methods We retrospective studied 704 SMM patients diagnosed between January 2000 to January 2020. Patients with a baseline FLCr ≥100 and involved FLC ≥10 mg/dL or baseline bone marrow plasma cells ≥60% were excluded. We collected serial laboratory data and re-applied the Mayo 2018 and IMWG 2020 SMM risk stratification models at annual landmark timepoints up to 4 years post SMM diagnosis. Survival analyses were performed using the Kaplan-Meier method. Time to progression was defined as time from diagnosis or landmark timepoint to treatment initiation for MM or systemic AL amyloidosis. Results At SMM diagnosis, 271 (38%) patients were low risk, 228 (32%) were intermediate risk, and 205 (29%) were high risk per the Mayo 2018 score. Applying the IMWG 2020 score at diagnosis, 90 (34%) of patients were low risk, 111 (42%) were low-intermediate risk, 54 (21%) were intermediate risk, and 9 (3%) were high risk. The Mayo 2018 and IMWG 2020 risk scores was re-assessed annually post-diagnosis in patients without progression (respective sample sizes: n=430 and n=197 at year 1 landmark, n=326 and n=143 at year 2 landmark, n=260 and n=106 at year 3 landmark, n=203 and n=73 patients at year 4 landmark). The Mayo 2018 and IMWG 2020 models reliably stratified patients based on progression risk post diagnosis; the respective 2-year progression risk in Mayo 2018 high-risk versus IMWG 2020 intermediate-high risk patients was 51% versus 62% at the 1-year landmark, 60% versus 65% at the 2-year landmark, 47% versus 62% at the 3-year landmark, and 47% versus 45% at the 4-year landmark. Patients evolving to a higher Mayo 2018 or IMWG 2020 risk category during follow up consistently had an increased risk of progression compared to patients with a stable/decreased risk categorization. We showed that patients categorized as Mayo 2018 high-risk at follow-up had a similar risk of progression regardless of whether the baseline risk categorization was low-intermediate versus high-risk (HR 0.87, 95% CI 0.51-1.48, p=0.606 at 2-year landmark; HR 1.01, 95% CI 0.59-1.73, p=0.972 at 3-year landmark; HR 0.75, 95% CI 0.34-1.65, p=0.467 at 4-year landmark). Conclusion Our findings support the use of the Mayo 2018 and IMWG 2020 scores post-diagnosis. We showed that patients migrating to a higher risk category have an increased risk of progression, suggesting that patients evolving to a high-risk score during follow-up should be considered for early intervention treatment approaches.

Context Elevated serum LDH level is an adverse prognostic factor in NDMM. Quantitative serum LDH levels range from over the upper limit of normal (ULN) to levels 2- or more-fold higher than ULN. Objective The “normal versus elevated” classification of serum LDH level can fail to discriminate between different NDMM disease biology. Thus, we attempted to further stratify NDMM patients by their serum LDH level and determine the impact on OS outcomes. Design and Setting The cohort included patients diagnosed with NDMM from the Mayo Clinic, Rochester, from 2003 to 2017, treated with novel agent induction therapy with measured serum LDH levels at the time of diagnosis. Patients The cohort consists of 1,196 NDMM patients with median age of 65 (22–95) years. R-ISS classification was available for 968 patients and is distributed as follows: 210 (22%) stage 1, 639 (66%) stage 2, and 119 (12%) stage 3. Cytogenetic risk data was available for 970 patients: 215 (22%) high-risk and 755 (78%) standard-risk. Main Outcome Measures The serum LDH levels were stratified into three levels: normal (LDH 444 U/L). Survival analysis was performed using the Kaplan–Meier method and compared via Wilcoxon method. Results Median serum LDH level was 162 U/L (3–1260), and an elevated LDH was present in 199 patients (17%). Median OS for patients with normal (N = 997; 83%), elevated (N = 170; 13%), and very elevated (N = 29; 3%) LDH levels were 76 months, 57 months, and 23 months respectively (P Conclusion A small subset (3%) of NDMM have very elevated LDH levels that confer exceptionally poor OS, irrespective of R-ISS stage and cytogenetic risk. Future studies determining disease biology responsible for such poor OS outcomes are warranted. Acknowledgments Research was supported by the National Cancer Institute [Grant Number CA254961], the Helen Diller Family Foundation, and the Marion Schwartz Foundation for Multiple Myeloma.

Context Waldenstrom macroglobulinemia (WM) is a rare lymphoma for which scant comparative data exist to guide frontline therapy. Objective To compare the efficacy of the most frequently used rituximab-based fixed-duration anti-WM regimens in routine practice [rituximab, bendamustine (R-Benda); dexamethasone, rituximab, cyclophosphamide (DRC); and bortezomib, dexamethasone, rituximab (BDR)] to inform clinicians about the benefits/limitations of choosing one regimen over the other. Design A retrospective cohort study. Participants Patients with active WM seen at Mayo Clinic Rochester, Arizona, and Florida campuses between 10/01/2000 and 10/31/2019 who received R-Benda, DRC, or BDR as primary therapy were included. Outcomes Measures Overall response rate (ORR), event-free survival (EFS), progression-free survival (PFS), overall survival (OS), time-to-next therapy (TTNT) and treatment related adverse-effects (AEs) based on the three treatment regimens. The MYD88L265P mutation status was assessed using allele-specific polymerase-chain-reaction (sensitivity 1%). Response rates were assessed by Consensus Criteria. Time-to-event analyses were performed from the frontline therapy, using Kaplan-Meier method. CTCAE v4.03 was used to grade toxicities. Results The study included 220 patients with active WM who were treated with R-Benda (n=83), DRC (n=92) or BDR (n=45). The median follow-up was 4.5 (95% CI: 4-5) years. The R-Benda cohort demonstrated superior ORR (98%), in comparison to DRC (78%) or BDR (84%) cohorts, p=0.003. Similarly, longer PFS was evident with R-Benda use [median 5.2 versus 4.3 (DRC) and 1.8 years (BDR), p=0.0003]. The TTNT favored R-Benda [median, not-reached, versus 4.4 (DRC) and 2.6 years (BDR), p=0.0002]. These endpoints were comparable between the DRC and BDR cohorts. Overall survival (OS) was similar across the three cohorts, p=0.77. In a subset analysis of 142 patients genotyped for MYD88L265P mutation, the ORR, PFS and TTNT were unaffected by the MYD88 signature within each cohort. Toxicity profiles across the three groups were comparable, barring a higher incidence of neutropenia and neuropathy in patients who received R-Benda and BDR regimens, respectively. Conclusions The ORR, PFS and TTNT with R-Benda are superior compared to DRC or BDR in treatment-naive patients with active WM. The patient outcomes with any one of these three regimens are unaffected by the MYD88L265P mutation status.

Context Lenalidomide maintenance therapy after autologous stem cell transplantation (ASCT) is standard of care for patients with multiple myeloma (MM). However, optimal duration of maintenance, as well as factors predicting outcomes, need further evaluation. Objective To determine impact of duration of therapy and identify factors affecting outcome of lenalidomide maintenance. Design Retrospective study of consecutive patients with MM seen at Mayo Clinic, Rochester between 1/1/2005 and 12/31/2016. Patients or Other Participants Two hundred thirteen patients treated with lenalidomide-based maintenance post-ASCT were included. Main Outcomes Measures Progression-free survival (PFS), overall survival (OS), and impact of duration of therapy on PFS and OS. Results The median follow-up was 5.4 (95% CI: 4.9, 5.9) years from diagnosis. Median age at initiation of maintenance was 60 years (range: 35–76). Cytogenetics data were available in 202 (95%) patients; 31% (63/203) harbored high-risk cytogenetics based on the mSMART 3.0 criteria. The median PFS was 4 years (95% CI: 3.4, 4.5) from diagnosis of MM and 3 years (95% CI: 2.6, 3.5) from start of maintenance; median OS was not reached from diagnosis of MM (5-year OS: 77%). Excluding patients progressing within 3 years of starting maintenance (n=65), patients receiving ≥3 years of maintenance (n=48) had superior 5-year OS of 100% versus 88% in patients who received Conclusions Maintenance therapy with lenalidomide is well tolerated, and a longer duration (≥3 years) is associated with improvement in OS, irrespective of cytogenetic risk group and ISS stage.

Context Lenalidomide maintenance therapy after autologous stem cell transplantation (ASCT) is standard of care for patients with multiple myeloma (MM). However, most patients relapse, and the optimal choice of therapy at first-relapse post-lenalidomide maintenance is not established. Objective To compare the efficacy of salvage therapies at first relapse post-lenalidomide maintenance. Design Retrospective study of consecutive patients with MM seen at Mayo Clinic, Rochester between 1/1/2005–12/31/2016. Setting Tertiary referral center. Patients or Other Participants Two hundred thirteen patients treated with lenalidomide/lenalidomide-dexamethasone maintenance post-ASCT were screened; 136 patients experienced a first relapse. One hundred eighteen patients receiving salvage therapy were included in subsequent analyses. Interventions N/A Main Outcomes Measures The main outcome measure was second progression-free survival (2nd PFS), which was calculated from the start of therapy at first relapse after maintenance until therapy discontinuation. Results The median follow-up was 5.4 (95% CI: 4.9, 5.9) years from diagnosis. The median 2nd PFS was significantly longer in patients treated with daratumumab-based regimens [18.4 (95% CI: 10.9, 25.9) months; n=32] versus patients without daratumumab [8.9 (95% CI: 5.5, 12.3) months; n=86; p=0.006]. Adjusting for age, ISS stage 3, cytogenetic risk, Rd maintenance, and lenalidomide refractoriness at salvage, daratumumab-based therapy was associated with a significantly improved PFS [hazard ratio 0.31 (95% CI: 0.16, 0.61; p=0.001)]. The median 2nd PFS was superior in daratumumab + IMiD (n=16) compared to daratumumab + PI (n=15) [NR versus 1 yr (95% CI: 0.5, 1.5), respectively; p=0.004]. In patients not receiving daratumumab, median 2nd PFS was comparable between PI-based combinations [9.2 (95% CI: 6.6, 11.7) months; n=44], IMiD-based combinations [6.7 (95% CI: 0.82, 12.6) months; n=18; p=0.7], or PI + IMiD-based combinations [11.2 (95% CI: 0, 28.4 months; n=24; p=0.17]. Without daratumumab, there was also no significant difference in median 2nd PFS between patients who received lenalidomide-based combinations [6.7 (95% CI: 0, 15.4) months] compared with pomalidomide-based regimens [20.1 (95% CI: 0, 41.4) months; p=0.5]. Conclusions Daratumumab-based therapies at relapse are associated with improvement in 2nd PFS, and daratumumab-IMiD combination was superior to daratumumab-bortezomib combination. Without daratumumab, there was no significant difference between doublet versus triplet therapies, IMiD-versus PI-based regimens or lenalidomide versus pomalidomide-based combinations.

Experience with intensive chemotherapy for relapsed/refractory multiple myeloma (RRMM) using VDT PACE regimen and its modifications (VDT PACE-like regimens-VPLRs) outside TOTAL THERAPY trials is limited. We analyzed the outcomes of 141 patients with RRMM who received VPLRs at our center between 2006 and 2017 in an intent-to-treat analysis. Median age was 59.7 years and 66.7% of patients were male. A median of 2.2 years (range, 0.02-11.4) separated diagnosis of myeloma and inititation of VPLR. High-risk cytogenetics were present in 52.4% patients. Patients received a median of 4 (range, 1-14) prior therapies including stem cell transplant (SCT) in 66.7% patients. Ninety five (67.4%) patients received VDT PACE, 20 (14.2%) received VD PACE and 26 (18.4) received other VPLRs. Patients received a median of 1 cycle (range, 1-9) of VPLR. We observed ≥minimal response in 68.4%, ≥partial response (PR) in 54.4% and ≥very good PR in 10.3% patients. Median progression-free survival was 3.1 months (95%CI, 1.9-3.9) and median overall survival (OS) was 8.1 months (CI, 6.2-9.9). One-hundred and sixteen (82.3%) patients received some therapy after VPLR; 71 (61.2%) received systemic chemotherapy, while 45 (38.8%) underwent SCT. Median OS for those who received SCT after VPLR was 15.1 months (CI, 10.3-20.8). Age ≥60 years [hazard ratio (HR)- 2.3 (CI, 1.4-3.7); p

Hematologic response criteria in light chain (AL) amyloidosis require the difference in involved and uninvolved free light chains (dFLC) to be at least 5 mg/dl. We describe the clinical presentation and outcomes of newly diagnosed amyloidosis patients with dFLC

Despite therapeutic advances, multiple myeloma remains incurable, with limited options for patients with refractory disease. We conducted a large, multi-cohort clinical trial testing various doses and treatment schedules of pomalidomide and dexamethasone (Pom/dex) in patients with refractory multiple myeloma. Overall, 345 patients were enrolled to six cohorts based on number and type of prior lines of therapy, pomalidomide dose and schedule. Median prior lines of therapy were three with near universal prior exposure to proteasome inhibitors and/or immunomodulatory drugs. A confirmed response rate of 35% was noted for all cohorts (range 23-65%) with higher responses in cohorts with fewer prior lines of therapy. Median time to confirmed response was ⩽2 months and the longest progression-free survival and overall survival seen in any cohort were 13.1 and 47.9 months, respectively. Observed adverse reactions were as expected, with myelosuppression and fatigue being the most common hematologic and non-hematologic adverse events (AEs), respectively. Longer durations of treatment and response, higher response rates and fewer AEs were noted with the 2 mg pomalidomide dose. This is the longest follow-up data for Pom/dex in refractory multiple myeloma and will help shape the real-world utilization of this regimen.

Post-transplant maintenance is widely used in multiple myeloma (MM); however, there is a lack of data on real-world outcomes. We have analyzed 577 patients with newly diagnosed MM undergoing early auto-transplantation between 2010 and 2015. A total of 341, 132 and 104 patients received no, lenalidomide (Len) or bortezomib (Bort) maintenance, respectively. Patients receiving Len or Bort maintenance had a higher incidence of high-risk cytogenetics by fluorescence in situ hybridization (31% (Len) vs 58% (Bort) vs 8% (No); P

Prior studies have revealed that the presence of increasing number of polyclonal plasma cells (pPCs) in the bone marrow (BM) are associated with better outcomes in newly diagnosed multiple myeloma (MM) patients. This effect has not been studied in patients with MM at the time of disease relapse. We determined the prognostic value of depletion of pPCs in the BM by 7-color multiparameter flow cytometry in a series of 174 relapsing MM patients. The time to next therapy (TTNT) in those with

We analysed factors predicting early treatment failure (ETF), after first-line therapy for light-chain amyloidosis (AL). AL amyloidosis patients seen at Mayo Clinic within 90 days of diagnosis, from 2006 to 2015, excluding those who died within 3 months of initial therapy, were analysed retrospectively. ETF was defined as progression requiring treatment change or death within 12 (ETF12) or 24 (ETF24) months of first-line treatment. Non-ETF included those with a follow-up of more than 12 or 24 months who had progression beyond 12 or 24 months. A total of 724 patients met the study criteria; 244 (33.7%) had ETF12 and 388 (53.6%) had ETF24. Patients with ETF12 were older (64.1 vs. 62.2 years) with higher prevalence of cardiac (81 vs. 64.1%) and multi-organ involvement (67.2 vs. 45.4%) and higher proportion of patients with t(11; 14) (58.5 vs. 44.3%) or in higher Mayo 2012 stage (58.5 vs. 41.1%).The median follow-up was 5.4 years from start of initial therapy. In multivariate analysis, presence of t(11; 14) and non-incorporation of autologous transplant in initial therapy are significant predictors of ETF12 (p = .01and p = .003) and ETF24 (p = .0001 and p = .005) while Mayo stage is predictive of ETF24 (p = .002), but not ETF12.

Objective To describe treatment types, outcomes, and relapse patterns in patients with localized immunoglobulin light chain amyloidosis (AL L ). Patients and Methods We included all patients with AL L seen at Mayo Clinic in Rochester, Minnesota, from January 1, 1968, through June 30, 2014. The diagnosis of AL L was predicated on the presence of a Congo red–positive biopsy specimen and negative serum and urine immunofixation. Treatment response categories were response, stability, and progression. Localized and systemic progressions were defined as progression of disease at the site of origin or appearance of clonal plasma cells in a bone marrow biopsy sample, respectively. Results Of 5551 patients with AL, 413 (7%) had AL L . The most common site involved was urothelial tissue (n=85, 21%), followed by the larynx (n=57, 14%). Coexisting autoimmune diseases were reported in 7% of patients (n=28). The most common first-line treatment was excision of the amyloid deposits (61%), followed by observation or supportive care (28%). When considering symptomatic patients only (n=284), 205 (72%) improved, 23 (8%) had stable disease, and 55 (19%) could not be evaluated for response. Ten-year survival was 78% and was not different from that of the general population. There were no systemic progressions, but 17% of patients (n=72) had localized progression. Conclusion Localized AL is associated with a relatively distinct pattern of organ involvement. The initial laboratory evaluation to exclude systemic disease could be limited to serum and urine immunofixation in most patients. Recurrence after first-line therapy is common, but long-term outcomes are excellent.

We describe a series of 102 patients diagnosed from January 1, 1990 to December 31, 2015 with Type 1 monoclonal cryoglobulinemia (MoC). Symptoms were seen in 89 (87%) patients, including: cutaneous symptoms in 64 (63%) patients, with purpura (n = 43, 42%) and ulcers/gangrene (n = 35, 34%) being most common; neurological findings in 33 (32%) patients, most frequently sensory neuropathy (n = 24, 24%); vasomotor symptoms, mainly Raynaud’s phenomenon in 25 (25%); arthralgias in 24 (24%); and renal manifestations, primarily glomerulonephritis in 14 (14%) patients. An underlying lymphoproliferative disorder was identified in 94 (92%) subjects; MGUS—39, myeloma—20, lymphoplasmacytic lymphoma—21 and others—14. Treatment was initiated in 73 (72%) patients, primarily for cryoglobulinemia-related symptoms in 57. Treatment regimens consisted of: steroids 6-alkylating agents in 29 (40%), novel myeloma therapies in 16 (22%), rituximab with alkylating agents in 12 (16%) and rituximab ± steroids in 11 (15%) patients; 22 patients received plasmapheresis. Six patients underwent autologous stem cell transplant. Cryocrit at treatment initiation, change in cryocrit and time to nadir cryocrit were predictive of symptom improvement. Treatment directed toward the underlying clonal disorder resulted in improvement (n = 47) or stabilization (n = 16) of symptoms in the majority of patients and disappearance of cryoglobulin in over one-half.

Circulating plasma cells at diagnosis, prior to auto-transplant and at relapse have a negative impact on survival in multiple myeloma. However, the impact of kinetics of circulating plasma cells along the course of illness has not been defined. We have analyzed 247 newly diagnosed multiple myeloma patients undergoing early auto-transplant who had paired evaluation of circulating plasma cells at diagnosis and pre-transplant by 6-color flow cytometry. A total of 117 patients had no detectable circulating plasma cells at both time points (CPC−/−), 82 had circulating plasma cells at diagnosis followed by complete eradication after induction (CPC+/−) and 48 had circulating plasma cells at transplant, including persistence of cells (CPC+/+; n=45) or emergence of new cells (CPC−/+; n=3) after induction. The rate of post-transplant stringent complete response was 32% in the CPC−/−, 30% in CPC+/− and 12% in CPC+/+ or −/+ groups (P=0.018). At a median follow up of 58 months from transplantation, the median progression-free survival in the 3 respective groups were 30, 24 and 14 months, and the 5-year overall survival rates were 83%, 70% and 43% (P

MV-NIS is an Edmonston lineage oncolytic measles virus expressing the human sodium iodide symporter-a means for monitoring by non-invasive imaging of radioiodine. Patients with relapsed, refractory myeloma who had explored all other treatment options were eligible for this Phase I trial. Cohort 1 was treated with intravenous MV-NIS, and Cohort 2 received cyclophosphamide 2 days prior to MV-NIS. Thirty-two patients were treated. Cohort 1 initially enrolled to four dose levels without reaching maximum tolerated dose (MTD) and subsequently to two higher dose levels when improved virus manufacture technology made it possible. MTD was not reached in Cohort 1, and TCID50 1011 is the dose being used in a Phase II trial of single agent MV-NIS. Grade 3-4 adverse events in both cohorts at all dose levels were: neutropenia (n=9); leukocyte count decreased (n=5); thrombocytopenia (n=2); and CD4 lymphocytes decreased, anemia and lymphopenia (each n=1). MV-N RNA sequences were amplified from gargle specimens, blood and urine. 123I scans were positive in eight patients. One patient achieved a complete response; transient drops in serum free light chains were seen in other patients. MV-NIS is capable of replicating before being cleared by the immune system. Oncolytic viruses offer a promising new modality for the targeted infection and destruction of disseminated myeloma.