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Abstract Introduction: Renal light chain (AL) amyloidosis typically manifests as proteinuria with or without renal failure and is associated with a risk of progression to renal replacement therapy (RRT). A significant reduction in circulating amyloidogenic light chain is needed to achieve a renal response. Current renal response criteria are binary defining a renal response as >30% reduction in 24-h proteinuria without worsening estimated glomerular filtration rate (eGFR). Several studies suggest that greater reduction in proteinuria following successful therapy improves renal and overall survival. Methods: AL amyloidosis patients diagnosed between 2010 to 2015, achieving at least hematological partial response (hemPR) to therapy and with renal involvement (defined as 24-h non-selective proteinuria >0.5 g/24-h) were included. Four predefined renal response categories were formulated based on reduction level in pretreatment 24-h proteinuria in the absence of renal progression (≥25% decrease in eGFR): renal complete response (renCR, 24-h proteinuria ≤200 mg/24-h); renal very good partial response (renVGPR, >60% reduction in 24-h proteinuria); renal partial response (renPR, 31-60% reduction in 24-proteinuria); and renal no response (renNR, 30% or less reduction). Renal response was assessed at landmark (6-, 12-, and 24 months from treatment initiation) and as best renal response. Graded renal responses were assessed as predictors for time from diagnosis to RRT and overall survival. Results: Seven hundred and thirty-seven patients were included. The median age was 63. The breakdown of renal stage was: I, 34%; II, 52%; and III, 14%. Eighty percent of patients received 1 line of therapy within 12 months of their diagnosis. Bortezomib-based therapy was given to 60% of the patients; 28% received autologous stem cell transplantation (ASCT) as their first line therapy. Hematological CR was achieved in 44% of patients, followed by hematological very good partial response (38%) and hemPR (18%). RRT was required during follow-up in 15% of patients (n=108) with a median time from diagnosis to RRT of 18 (IQR 6-43) months. Twenty-eight percent of the patients died. The median follow-up of the surviving patients was 69 months (IQR 56-86). Reduction in 24-h proteinuria from baseline improved over time with a median reduction of 34%, 50% and 71% at 6-month, 12-month, and 24-months, respectively. At best response, renCR, renVGPR, renPR and renNR were achieved in 27% (n=199), 34% (n=247), 15% (n=112) and 24% (n=179) of patients, respectively. The median time to best renal response among renal responders was 17 (IQR 8-31) months, longer for renCR (23 months, IQR 10-40) compared to renVGPR (16 months, IQR 9-27) or renPR (11 months, IQR 6-19). A renal response as early as 6 months after therapy initiation was able to predict time to RRT with an increase in RRT risk with lower level of renal response at that time point (5-year RRT risk 0%, 3%, 9% and 16% for renCR, renVGPR, renPR and renNR, respectively, P<0.001, Figure 1A). Prediction of risk for RRT based on renal response depth improved at 12- and 24-months (Figure 1B-C) and at best renal response (Figure 1D). Overall survival discrimination based on renal response depth was noted as early as 12 months from therapy initiation and improved with time. Renal response criteria as best response were tested in a univariate analysis and multivariable proportional hazard models for time to RRT and OS. The graded renal response criteria demonstrated an independent prognostic role for time to RRT and OS. Along with renal stage, graded renal responses were the strongest predictors for time to RRT. Conclusions: We validated new graded renal response criteria based on reduction in 24-h proteinuria. These 4-level renal response criteria highlight the importance of achieving a deep renal response to improve renal and overall survival. These findings will allow clinicians to make decisions on therapy changes or augmentation based on response depth as early as 6-months, before irreversible renal failure develops. Figure 1 Figure 1. Disclosures Palladini: Janssen Global Services: Honoraria, Other: advisory board fees; Siemens: Honoraria; Pfizer: Honoraria. Milani: Celgene: Other: Travel support; Janssen-Cilag: Honoraria. Schönland: Sanofi: Research Funding; Prothena: Honoraria, Other: Travel grants; Janssen: Honoraria, Other: Travel grants, Research Funding; Takeda: Honoraria, Other: Travel grants; Pfizer: Honoraria. Hegenbart: Akcea: Honoraria; Alnylam: Honoraria; Janssen: Consultancy, Research Funding; Prothena: Research Funding; Pfizer: Consultancy, Honoraria. Dispenzieri: Oncopeptides: Consultancy; Alnylam: Research Funding; Sorrento Therapeutics: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Kumar: 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; Merck: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Carsgen: Research Funding; Beigene: Consultancy; Novartis: Research Funding; Bluebird Bio: Consultancy; Amgen: Consultancy, Research Funding; Roche-Genentech: Consultancy, 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; Antengene: Consultancy, Honoraria; 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. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding. Dimopoulos: Takeda: Honoraria; Janssen: Honoraria; Beigene: Honoraria; BMS: Honoraria; Amgen: Honoraria. Liedtke: Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Alnylam: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees. Witteles: Pfizer: Honoraria, Research Funding; Alnylam: Honoraria, Research Funding; Eidos: Research Funding. Sanchorawala: Pfizer: Honoraria; Takeda: Research Funding; Celgene: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Regeneron: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptide: Research Funding; Karyopharm: Research Funding; Sorrento: Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees, Research Funding. Landau: Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Genzyme: Honoraria. Cibeira: Celgene: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Akcea: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Wechalekar: Caelum Biosciences: Other: Clinical Trial Funding; Amgen: Research Funding; Janssen: Consultancy; Celgene: Honoraria; Takeda: Honoraria; Alexion, AstraZeneca Rare Disease: Consultancy. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; 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.

Abstract 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.

AbstractGain of 1q22 at diagnosis portends poorer outcomes in multiple myeloma (MM), but the prognostic significance of acquired 1q22 gain is unknown. We identified 63 MM patients seen at Mayo Clinic from 1/2004 to 12/2019 without 1q22 gain at diagnosis who acquired it during follow up and compared them to 63 control patients who did not acquire 1q22 gain with similar follow up. We also compared outcomes in the acquired 1q22 gain group with outcomes in 126 patients with 1q22 gain present at diagnosis. The incidence of acquired 1q22 gain was 6.1% (median follow‐up 6.8 years); median time to acquisition was 5.0 years (range: 0.7–11.5 years). Abnormalities on baseline fluorescence in situ hybridization (FISH) included trisomies (54%) and monosomy 13 (39%); 16 (25%) had high‐risk (HR) translocations or del(17p). Median progression‐free survival with front line therapy was 29.5 months in patients with acquired 1q22 gain, versus 31.4 months in control patients (p = .34) and 31.2 months in patients with de novo 1q22 gain (p = .04). Median overall survival (OS) from diagnosis was 10.9 years in patients with acquired 1q22 gain, versus 13.0 years in control patients (p = .03) and 6.3 years in patients with de novo 1q22 gain (p = .01). Presence of HR FISH at baseline increased risk of 1q22 gain acquisition. We demonstrate that acquisition of 1q22 gain is a significant molecular event in MM, associated with reduced OS. Among HR patients for whom this clonal evolution is determined, a risk‐adapted approach and/or clinical trial should be considered.

Key Points Post-HSCT hemoglobinuria was associated with graft type (BMT+Cord). Post-HSCT hemoglobinuria was associated with early (48–72 hours) post-HSCT AKI. Graft type (BMT+Cord) was associated with AKI among patients with hemoglobinuria. Background Information on risk factors of hemoglobinuria after hematopoietic stem-cell transplant (HSCT) and its association with AKI, mortality, and engraftment is limited. Methods We conducted a retrospective cohort study on all consecutive adults that underwent HSCT from January 6, 1999, to November 6, 2017. The study included 6039 patients that underwent bone marrow transplantation (BMT), umbilical cord blood, and peripheral blood stem-cell transplantation (PBSCT). Results Early post-HSCT, AKI occurred in 393 (7%) patients, and 52 (0.9%) patients had post-HSCT hemoglobinuria. Post-HSCT hemoglobinuria was associated with graft type (BMT+Cord), underlying disease (lymphoma, acute leukemia), and fludarabine-based conditioning regimen. Post-HSCT hemoglobinuria was associated with early (48–72 hours) post-HSCT AKI. Graft type (BMT+Cord) was associated with AKI among patients with hemoglobinuria. AKI in patients with hemoglobinuria was associated with delayed platelet engraftment and delayed WBC engraftment but not 100-day mortality. Conclusion Close monitoring is recommended in this patient group to facilitate a good engraftment outcome.

AbstractHigh‐dose methotrexate (HDMTX) pharmacokinetics (PKs), including the best estimated glomerular filtration rate (eGFR) equation that reflects methotrexate (MTX) clearance, requires investigation. This prospective, observational, single‐center study evaluated adult patients with lymphoma treated with HDMTX. Samples were collected at predefined time points up to 96 h postinfusion. MTX and 7‐hydroxy‐MTX PKs were estimated by standard noncompartmental analysis. Linear regression determined which serum creatinine‐ or cystatin C‐based eGFR equation best predicted MTX clearance. The 80 included patients had a median (interquartile range [IQR]) age of 68.6 years (IQR 59.2–75.6), 54 (67.5%) were men, and 74 (92.5%) were White. The median (IQR) dose of MTX was 7.6 (IQR 4.8–11.3) grams. Median clearance was similar across three dosing levels at 4.5–5.6 L/h and was consistent with linear PKs. Liver function, weight, age, sex, concomitant chemotherapy, and number of previous MTX doses did not impact clearance. MTX area under the curve (AUC) values varied over a fourfold range and appeared to increase in proportion to the dose. The eGFRcys (ml/min) equation most closely correlated with MTX clearance in both the entire cohort and after excluding outlier MTX clearance values (r = 0.31 and 0.51, respectively). HDMTX as a 4‐h infusion displays high interpatient pharmacokinetic variability. Population PK modeling to optimize MTX AUC attainment requires further evaluation. The cystatin C‐based eGFR equation most closely estimated MTX clearance and should be investigated for dosing and monitoring in adults requiring MTX as part of lymphoma management.

Abstract Multiple myeloma (MM) is a heterogeneous disease that may be evaluated by a broad array of imaging and laboratory techniques to measure disease activity and predict prognosis. Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scanning has been shown to be predictive of patient outcomes throughout the disease course. We sought to corroborate these findings by examining the prognostic impact of PET/CT scanning in the posttransplant setting. We retrospectively analyzed PET/CT scans in 229 MM patients receiving an autologous stem cell transplant (ASCT) near day 100, and correlated these findings with time to progression(TTP) and overall survival (OS) to assess the impact of day 100 PET/CT scan findings as an independent prognostic factor. The median OS for the entire cohort was 61.5 months (95% confidence interval [CI], 49-75) and the median TTP was 18.5 months (95% CI, 15.4-21.8). Among patients with abnormal day 100 PET findings (PET+), median TTP was 12.4 months vs 24 months among those with normal PET findings (PET−) (P < .0001). The median OS in the PET+ group was 46 months compared with 99 months in the PET− group (P < .0001). We conclude that an abnormal PET/CT scan near day 100 post-ASCT is predictive of shorter TTP and OS, with prognostic significance retained after adjusting for disease response and other prognostic variables in MM.

AbstractMultiple myeloma (MM) remains an incurable disease despite incorporation of novel agents. Venetoclax, a B‐cell lymphoma 2 (BCL‐2) inhibitor is approved for some hematologic malignancies but not yet for MM, although clinical trials have shown efficacy in patients with MM, particularly those harboring t(11;14). We reviewed the medical records of relapsed and/or refractory MM patients to study the efficacy and safety of venetoclax used outside of clinical trials at Mayo Clinic between December, 2016 and March, 2019. The data cut‐off date was August 06, 2020. We identified 56 patients of whom 42 (75%) harbored t(11;14). The median number of prior therapies was six (range 1–15) and 14% of patients had received ≥10 prior lines of therapy. Fifty‐three (95%) patients were refractory to an immunomodulatory drug and proteasome inhibitor. Venetoclax was used as monotherapy or doublet, in combination with dexamethasone in 55% (n = 31) and a triplet or quadruplet in 45% of patients. No patient experienced tumor lysis syndrome. Overall response rate in 52 evaluable patients was 44%. The median time to best response was 2 months and median duration of response was 13.6 months. The median PFS for the entire cohort was 5.8 (95% CI 4.9–10.3) months and median OS was 28.4 (95% CI 14.6‐not reached) months. The presence of t(11;14) was associated with improved PFS (median 9.7 months vs. 4.2 months, p = 0.019) and OS (median not reached vs. 10.8 9 months, p = 0.015). Venetoclax demonstrates encouraging activity in heavily‐treated patients with relapsed/refractory MM, particularly the t(11;14) patient‐population.

e20016 Background: An elevated serum LDH level is an adverse prognostic factor in NDMM. However, this category includes quantitative serum LDH levels that range from just over the upper limit of normal (ULN) to levels that may be 2 or more-fold higher than the ULN. This binary classification of serum LDH level of “normal versus elevated” fails to discriminate between the different disease biology that exists among NDMM patients with elevated serum LDH levels. Thus, we attempted to further stratify NDMM patients by the level of their serum LDH and determine its impact on OS. Methods: The cohort included patients diagnosed with NDMM from the Mayo Clinic, Rochester from 2003 - 2017 who were treated with novel agent induction therapy and had serum LDH levels measured at the time of diagnosis. The serum LDH levels were stratified into three levels: Normal (LDH < 222 U/L), Elevated (LDH 223-444 U/L), and Very Elevated (LDH >444 U/L or >2x upper limit of normal). Survival analysis was performed using the Kaplan-Meier survival analysis and compared via the log-rank method. Results: The cohort consists of 1,196 NDMM patients with a median age of 65 (22 – 95). R-ISS classification and cytogenetic risk were available for 968 and 970 patients respectively. The median serum LDH level was (162 U/L (3- 1260)) and an elevated LDH was present in 199 patients (17%). The 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 < 0.001). The impact of these different levels of LDH on OS by R-ISS stage and cytogenetic risk is shown in the Table. Conclusions: A very small subset of NDMM patients has very elevated LDH levels that confer an exceptionally poor OS irrespective of R-ISS stage and cytogenetic risk. Future studies elucidating their disease biology responsible for such poor OS outcomes are warranted.[Table: see text]