Dispenzieri, Angela

Abstract Introduction: Binary cardiac response assessment using NT-proBNP is prognostic in light chain (AL) amyloidosis. Previous studies suggested that refining the criteria to multi-level cardiac responses improves prognostic prediction. We validate a graded cardiac response assessment tool in AL amyloidosis using NT-proBNP or BNP. Methods: In this retrospective, multicenter study AL amyloidosis patients who were diagnosed between 2010 and 2015, achieving at least a hematological partial response (PR) within 12 months of diagnosis and were evaluable for cardiac response (defined as baseline NT-proBNP >650 pg/mL or BNP >150 pg/mL) were included. The following response criteria were tested: cardiac complete response (carCR, nadir NT-proBNP≤350 pg/mL or BNP≤80 pg/mL); cardiac very good partial response (carVGPR, >60% reduction in NT-proBNP/BNP); Cardiac PR (carPR 31-60% reduction); and cardiac non response (carNR, ≤30% reduction). Response was assessed at fixed time points (6, 12 and 24 months from therapy initiation) and at best response. The primary outcome was overall survival based on depth of cardiac response. Multivariate Cox proportional models were analyzed to determine independent prognostic factors for OS and time to cardiac progression using variables with p-value <0.1 in a univariate analysis. Results: Six hundred and fifty-one patients were included. The median age was 64 years. Mayo 2004 cardiac stage II, IIIA and IIIB was present in 47.5%, 38% and 14.5% of patients, respectively (by definition, patients with Mayo stage I do not have cardiac amyloidosis evaluable for response). Seventy-six percent of patients received only one line of therapy within the initial 12 months of diagnosis. Bortezomib-based therapy was the most common (70.2% of patients) followed by autologous stem cell transplantation (ASCT) in 15.7% of patients. Hematological CR, hematological VGPR and hematological PR as best response was achieved in 38%, 39% and 23% of patients, respectively. Forty-three percent of the patients have died, with 36% of the patients dying within 5-years of diagnosis. The median follow-up of the surviving patients is 70 months (IQR 56-84). Cardiac response was evaluable using NT-proBNP in 494 patients (75.9%), BNP in 109 patients (16.7%) and both NT-proBNP and BNP in 48 patients (7.4%). The latter two were grouped together for further analysis. The median time to best cardiac response among responders was 12 months (IQR 7-21 months; 18 months for carCR, 11.5 months for carVGPR and 9.5 months for carPR). Cardiac response improved over time with a median percentage reduction in NT-proBNP/BNP compared to baseline of 15%, 37% and 54%, at 6, 12 and 24 months respectively. Cardiac responses at 6-, 12- and 24-months are depicted in Figure 1A. At best cardiac response, carCR, carVGPR, carPR and carNR were achieved in 16%, 26%, 23% and 35% of patients, respectively. Patients who achieved a carCR had lower cardiac stage at diagnosis compared to patients who achieved carVGPR or carPR (stage II 65% vs 47% vs 47%, respectively; P<0.001). At least carPR at 6 and 12 months and at least carVGPR at 24-months was associated with better survival compared with a lower depth of response. At best cardiac response, deeper cardiac response was associated with a longer survival (5-year OS 93%, 80%, 62% and 35% for carCR, carVGPR, carPR and carNR, respectively; P<0.001, Figure 1B). A 2-year landmark analysis (excluding early deaths not evaluable for cardiac response depth) confirmed improved survival with a deeper cardiac response (5-year OS 93%, 82%, 70% and 58%, P<0.001; Figure 1C). These cardiac response criteria were independent predictors of survival and time to cardiac progression (>30% rise in NT-proBNP/BNP) in multivariate analysis that included age, type of first line therapy, light chain burden, cardiac stage, and hematological response. Conclusions: We validated the prognostic value of graded cardiac response. These response criteria allow better discrimination of patient populations and assessment of treatment effectiveness in an era of improved therapies for AL amyloidosis. The study emphasizes the importance of early diagnosis which increases the likelihood of deep and durable cardiac responses. Figure 1 Figure 1. Disclosures Dispenzieri: Oncopeptides: Consultancy; Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Takeda: Research Funding; Alnylam: Research Funding; Janssen: Consultancy, Research Funding. Palladini: Siemens: Honoraria; Pfizer: Honoraria; Janssen Global Services: Honoraria, Other: advisory board fees. Schönland: Janssen: Honoraria, Other: Travel grants, Research Funding; Takeda: Honoraria, Other: Travel grants; Sanofi: Research Funding; Pfizer: Honoraria; Prothena: Honoraria, Other: Travel grants. Hegenbart: Alnylam: Honoraria; Janssen: Consultancy, Research Funding; Prothena: Research Funding; Pfizer: Consultancy, Honoraria; Akcea: Honoraria. Kumar: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Novartis: Research Funding; Merck: Research Funding; Tenebio: Research Funding; Bluebird Bio: Consultancy; 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; Roche-Genentech: Consultancy, Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Janssen: 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; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Kastritis: Genesis Pharma: Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding. Dimopoulos: Beigene: Honoraria; Takeda: Honoraria; BMS: Honoraria; Janssen: Honoraria; Amgen: Honoraria. Liedtke: GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; 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; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Sanofi: Membership on an entity's Board of Directors or advisory committees; Alnylam: 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; 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; Kura Oncology: Membership on an entity's Board of Directors or advisory committees. Witteles: Eidos: Research Funding; Alnylam: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Sanchorawala: Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Proclara: Membership on an entity's Board of Directors or advisory committees; 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; Caelum: Membership on an entity's Board of Directors or advisory committees, Research Funding; Regeneron: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Karyopharm: Research Funding; Oncopeptide: Research Funding; Pfizer: Honoraria; Sorrento: Research Funding. Landau: Genzyme: Honoraria; Takeda: Research Funding; Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees. Cibeira: 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; Celgene: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gertz: 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; Aurora Biopharma: Other: Stock option.

Abstract Background: Advances in supportive care and novel therapies have driven improved outcomes for patients with Multiple myeloma (MM) and Light Chain Amyloidosis (AL). Unfortunately, this progress demands a heavy toll - higher patient costs. Financial toxicity (FT) is the adverse impact of cancer on a patient's financial well-being, contributing to increased distress, lower medication compliance, and even reduced survival. We aimed to evaluate MM and AL patients for financial toxicity over time to better understand its impact on various quality of life (QOL) domains. Methods: Adult patients with MM or AL that receive care at Mayo Clinic, Rochester MN, were recruited for a prospective study between December 2019 and March 2021. FT was measured using the validated COmprehensive Score for financial Toxicity (COST) questionnaire at the time of enrollment, 3 months, and 6 months follow-up. COST scores range from 0-44, with higher scores indicating lower FT. We defined patients with a COST score of ≤ 23 as having substantial FT. Domains of QOL were assessed via the Patient Reported Outcome Measurement Information System (PROMIS)-29 survey. Patient demographics and clinical information were abstracted from the electronic medical record. Statistical analysis included a comparison of COST scores among groups through Wilcoxon rank-sum, Kruskal-Wallis, and Jonckheere-Terpestra tests for binary, unordered, and ordered categorical variables, respectively. Results: One hundred and sixteen patients (96 MM, 83%; AL 20, 17%) enrolled in this study. The cohort is characterized as follows: 49% age 65+ (51% age 35-64), 54% male, 93% White, 4.3% Black, 3.5% Hispanic, 44% with incomes > USD 75k/yr (26% < USD 50k/yr), 77% with at least some college education (32% graduate or doctoral degree), 52% insured through Medicare (4.3% through Medicaid), 36% employed (53% retired), and 71% married (16% divorced). Forty-three percent of patients enrolled in the study were newly diagnosed (56% relapsed), and 72% had received an autologous stem cell transplant. Baseline mean COST score was25.9 (N=116; SD 10.2), with 37% reporting FT. A total of 101 patients (85 MM; 16 AL) completed a baseline and either 3- or 6-month COST survey. Thirty-eight of these patients (38%) reported FT at the time of enrollment. Among those reporting baseline FT, 71% continued to report FT at 3 or 6 months; 29% showed reduced FT. Of the 62% of patients who reported low FT at baseline, 78% showed continued low FT at 3 or 6 months; 22% showed increased FT. Results of longitudinal follow-up are outlined in Figure 1. FT was significantly associated with increased anxiety, depression, and pain intensity domains on the PROMIS-29. Substantial FT was associated with: women, Medicaid as primary insurance, and being divorced. FT was also greater in unemployed/disabled vs retired individuals. Conversely, low FT was associated with: males, earning > USD 75k/yr, Medicare as primary insurance, having at least some college education, being retired, and traveling 300+ miles for care. Financial toxicity did not differ significantly by age, race, ethnicity, disease status (newly diagnosed vs relapsed), or transplant status. Discussion : Financial toxicity was present in more than one-third of AL and MM patients in this high-earning and well-educated cohort. Financial toxicity was associated with increased anxiety, depression, and pain intensity, contributing to lower patient quality of life. Longitudinal follow-up has shown financial toxicity to be dynamic, necessitating routine evaluation of patient financial burdens. Future work will focus on automating FT assessment with incorporation into routine care and developing care processes to support patients. Figure 1 Figure 1. Disclosures Dispenzieri: Alnylam: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding.

Abstract Introduction Systemic immunoglobulin light chain (AL) amyloidosis is a rare disease characterized by amyloid fibril deposits, most commonly in the heart and kidneys. Management of the disease relies primarily on off-label use of multiple myeloma therapies. No treatments are approved for AL amyloidosis in the relapsed/refractory setting. In the phase 3, open-label TOURMALINE-AL1 trial (NCT01659658), patients with relapsed/refractory AL amyloidosis were randomized 1:1 to receive either oral ixazomib plus dexamethasone (Id) or physician's choice (CH) in 28-day cycles, and followed until progression or unacceptable toxicity. An interim analysis demonstrated that Id was well tolerated and, although the primary endpoint of hematologic response rate was not met, time-to-event efficacy analyses consistently favored Id. We report an analysis of patient-reported outcome (PRO) data on health-related quality of life (HRQOL) and AL amyloidosis symptoms from TOURMALINE-AL1; such data for AL amyloidosis in general have been limited. Methods Four PRO instruments were used to collect data to support PRO-related secondary endpoints during the treatment period: the Functional Assessment of Cancer Therapy/Gynecologic Oncology Group Neurotoxicity subscale (FACT/GOG-Ntx), an amyloidosis symptom questionnaire (ASQ), the EuroQoL 5-Dimension 3-Level (EQ-5D-3L), and the Visual Analogue Scale (EQ VAS) were collected at screening, day 1 of each cycle, and end of treatment (EOT), and the 36-item Short Form General Health Survey version 2 (SF-36v2) was collected at screening, day 1 of every third cycle, and EOT. Analysis of PRO data included descriptive summaries of means and change from baseline and a linear mixed model (LMM) for repeated measures for patients in the intent-to-treat (ITT) population with a baseline and at least one postbaseline PRO-specific assessment. No adjustment was made for multiple comparisons. Data cutoff date was 20 February 2019. Results The ITT population included 168 patients (Id: n=85; CH: n=83), who completed up to 58 cycles (Id) and up to 43 cycles (CH); median treatment duration was 11.7 vs 5.0 months, respectively. PRO compliance in the treatment period was high for all instruments (Figure). Baseline HRQOL as measured by the SF-36v2 and EQ VAS was similar between treatment arms. During the treatment period, SF-36v2 Mental and Physical Component Summary (MCS and PCS) scores remained stable relative to baseline and were similar between arms; the 8 subscale scores were also generally maintained over time, and mostly similar between arms. Least-squares (LS) mean changes from baseline were significantly higher (better HRQoL) for Id compared with CH at several cycles in the SF-36v2 Role Physical and Vitality subscales (p<0.05) (Figure); no subscales demonstrated significant differences favoring CH. Symptom burden as measured by the FACT/GOG-Ntx and ASQ was low at baseline, leaving little room for improvement. FACT/GOG-Ntx scores were generally maintained over time. In the treatment period, there were small but significant differences in LS mean changes from baseline favoring Id over CH at multiple cycles for 7 of the 11 individual items and the neurotoxicity and sensory summary scores; there were small but significant differences favoring CH over Id for 1 individual item (trouble hearing) at a few later cycles. The ASQ total score trended downward slightly (lower burden) during treatment after the first few cycles in both arms. There were significant differences per the LMM favoring Id over CH at cycles 7 and 21 (p<0.05). In both arms, EQ VAS scores trended upward (better HRQoL) during treatment and then declined slightly at EOT. (LMM analyses were not conducted for EQ-5D.) At EOT, a slight deterioration from baseline was observed in actual scores for SF-36v2 domains and summary scales, FACT/GOG-Ntx neurotoxicity and sensory subscales, and ASQ items and total score for both Id and CH. Conclusions Relapsed/refractory AL amyloidosis patients treated with Id experienced HRQOL and symptoms that were similar to or trended better than patients treated with CH. These data suggest that treatment with Id, although with a substantially longer treatment duration, did not have a negative impact on HRQOL in patients with relapsed/refractory AL amyloidosis, a population with currently no approved treatment options. Figure 1 Figure 1. Disclosures Sanchorawala: Regeneron: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Oncopeptide: Research Funding; Karyopharm: Research Funding; Sorrento: Research Funding; Pfizer: Honoraria; Caelum: 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; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; Celgene: Research Funding. Wechalekar: Caelum Biosciences: Other: Clinical Trial Funding; Alexion, AstraZeneca Rare Disease: Consultancy; Janssen: Consultancy; Celgene: Honoraria; Amgen: Research Funding; Takeda: Honoraria. Kim: Janssen, BMS: Research Funding. Schönland: Janssen: Honoraria, Other: Travel grants, Research Funding; Takeda: Honoraria, Other: Travel grants; Sanofi: Research Funding; Prothena: Honoraria, Other: Travel grants; Pfizer: Honoraria. Landau: Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Genzyme: Honoraria. Fiona: Pfizer: Research Funding. Suzuki: Janssen: Consultancy, Honoraria; Abie: Honoraria; Sanofi: Honoraria; Novartis: Honoraria; ONO: Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Comenzo: Karyopharm: Research Funding; Takeda: Research Funding; Unum: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Janssen: Patents & Royalties: WO2016187546A1, Research Funding; Prothena Biosciences: Consultancy, Research Funding; Caelum: Consultancy, Research Funding. Cherepanov: Takeda: Current Employment, Current equity holder in publicly-traded company. Hayden: Takeda: Current Employment, Current equity holder in publicly-traded company. Kumar: Takeda: Current Employment, Current holder of stock options in a privately-held company. Labotka: Takeda: Current Employment. Faller: Takeda Pharmaceuticals Co.: Current Employment; Viracta Therapeutics, Inc: Current holder of stock options in a privately-held company, Ended employment in the past 24 months, Membership on an entity's Board of Directors or advisory committees; Briacell, Inc: Current holder of stock options in a privately-held company. Kastritis: Amgen, Genesis Pharma, Janssen, Takeda: Consultancy; Amgen, Janssen, Pfizer: Research Funding; Amgen, Genesis Pharma, Janssen, Takeda, Pfizer: 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.

Abstract Introduction/Objective Amyloidosis encompasses a heterogeneous group of disorders characterized by abnormal deposition of misfolded proteins leading to progressive organ failure. Accurate amyloid typing is essential for proper patient management, as treatment regimens vary dramatically across different types. Bone marrow (BM) biopsy, in conjunction with fat pad aspiration/biopsy, is often the first step in patients with suspected amyloidosis. Although BM involvement by AL amyloid has been previously characterized, little is known about the incidence, morphology and clinical phenotype of non-AL amyloid in BM. Methods/Case Report We retrospectively identified 1469 BM biopsies by querying our reference laboratory database of 19,298 specimens from myriad anatomic sites typed by mass spectrometry-based proteomics (LC-MS/MS). These were reviewed for frequency of amyloid types (N=1469), distribution of amyloid deposits (N=139), and clinical phenotypes (N=345), with particular emphases on cardiac involvement. Results (if a Case Study enter NA) We identified the following amyloid types: AL (N=1172; 79.8%), ATTR (transthyretin) (N=240; 16.3%), AH (immunoglobulin heavy chain) (N=38; 2.6%), AA (serum amyloid A) (N=17; 1.2%), and Aβ2M (β2-microglobulin) (N=2; 0.1%). ATTR deposits showed striking predilection for periosteal soft tissue and/or periosteal vessels, and rarely involved BM stroma and/or interstitial vessels, while AL variably involved these compartments. AA primarily involved interstitial vessels. Both AL and ATTR cases commonly had a monoclonal gammopathy (AL: 92.9%; ATTR: 62.5%) with concomitant cardiac amyloidosis (AL: 91.6%; ATTR: 100%). Compared to AL, ATTR patients had higher stage cardiac amyloidosis and lower overall survival. Conclusion ATTR is common in BM, constituting16.3% of cases in our cohort. Rarer amyloid types, such as AA, AH and AB2M can also occur in BM. ATTR was frequently identified in patients with concomitant monoclonal gammopathy, in whom AL may have been suspected. Although ATTR deposits have distinctive morphologic distribution, primarily involving periosteal soft tissue and/or periosteal vessels and rarely involving BM stroma and/or interstitial vessels, there is considerable morphologic overlap with AL. Therefore, it is imperative to type BM amyloidosis, preferably by LC-MS/MS, to ensure proper patient management. Furthermore, BM involvement by ATTR may be a marker for advanced stage of disease.

Abstract Heavy Chain Disease (HCD) is a group of rare B-cell proliferative disorders. Diagnosis depends on the detection of a truncated heavy chain with no associated light chain, often done by serum or urine immunofixation. This approach has been reported to have low specificity, since associated light chain bands are sometimes not visible and heavy chain bands can be mistaken for polyclonal bands. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) offers improved sensitivity in detecting monoclonal immunoglobulins. Truncation is thought to happen in the constant heavy chain (CH1) region, detected as a fragment of mass 27,000 Da on MALDI-TOF. Other mass patterns have not been reported in the literature. In this study, frozen serum samples from 8 heavy chain disease patients were analyzed by MALDI-TOF mass spectrometry. Spectra were reviewed on Mass-Fix software and visually inspected for monoclonal peaks. We detected two types of patterns for the IgG heavy chain disease. One pattern shows an IgG heavy chain with truncated mass (27,000 Da vs. 50,000 Da) and another in which the mass of the IgG heavy chain is greater than normal (65,000 Da). Follow-up work demonstrates that these are most likely dimers of truncated heavy chains. Thus, mass spectrometry-based immunofixation can provide new insights into heavy chain disease biology, mechanism, and progression, which are not identified by traditional diagnostic methods.

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.

Abstract Background Wild type transthyretin cardiac amyloidosis (wtATTR-CA) is increasingly recognized as a cause of heart failure with preserved ejection fraction (HFpEF) but prognosis is often limited due to late or misdiagnosis.Longitudinal left ventricular strain and biomarkers are established as markers of disease severity, but the role of RV free wall strain, reflecting RV contractility, is less well understood. Purpose We sought to determine whether RV free wall strain might add incremental prognostic value in wtATTR-CA. Methods Consecutive patients diagnosed with wtATTR-CA with tissue confirmation at Mayo clinic between 2013 and 2015 were included. Patients with TTR gene mutations were excluded. Baseline characteristics and transthoracic echocardiography measurements were obtained from the medical records. Speckle tracking RV free wall longitudinal 2D strain and peak LA longitudinal 2D strain were measured using Tom Tec Imaging System. Survival was determined using Kaplan Meier estimates and using the cox proportional hazard ratio, univariate and multivariable analysis were performed to identify predictors of mortality in patients with wtATTR. Results The study group comprised 139 patients (mean age 74.9±8.6, 92.8% male), of which 102 had adequate image quality for RV strain, and 99 for LA strain. Amongst these, 102 (73.3%) had AF and 118 patients (84.8%) had HF. During 3.23±2.0 years of follow up, 66 patients died. Both mean RV and LA strain were impaired at baseline: RV free wall strain was −14.7±4.9, and peak atrial longitudinal strain (PALS) was 13.2±8.8%. Using ROC analysis, RV strain of −16.8% was an independent predictor of all-cause mortality. In univariate modeling, higher levels of NT-proBNP (HR: 1.1 per 1000 pg.ml; 95%, CI 1.05–1.15, p<0.001) and Troponin T (HR: 2.0 per 0.1ng/ml; 95% CI 1.49–2.61, p<0.001) were associated with increased all-cause mortality. In addition, LV GLS (HR: 1.13 per 1%; 95% CI1.04–1.24, p=0.003), RV free wall LS (HR: 2.16 per 5%; 95%, CI 1.57–3.03, p<0.0001), and PALS (HR: 0.91 per1%; 95% CI 0.85–0.96, p<0.0001) were univariate predictors of all-cause mortality. In multivariate analysis using a stepwise regression model, RV free wall longitudinal strain (HR: 1.81; 95% CI 1.29–2.62, p<0.001) and Troponin T (HR: 1.7; 95% CI 1.25–2.26, p=0.001) remained independent predictors. Kaplan-Meier survival analysis demonstrated a higher mortality rate above −16.8 RV strain cut-off (Wilcoxon <0.0001). All stages were divided into two groups by −16.8% RV strain, and survival in individual stages analyzed. Stage 1 and 2 with <−16.8 RV free wall strain value had higher mortality than ≤-16.8% RV strain (Stage 1: Wilcoxon = 0.0041 and Stage 2: Wilcoxon = 0.023). However, there was not a survival difference between two RV strain groups in stage3 (Wilcoxon = 0.34) Conclusion RV free wall strain is an independent predictor of survival in wtATTR patients and may add incremental prognostic value to NT-proBNP and Troponin. Funding Acknowledgement Type of funding sources: None. Kaplan-Meier curve of all patientsKaplan-Meier curve of stages