Milani, Paolo

PURPOSE Binary cardiac response assessment using cardiac biomarkers is prognostic in light chain amyloidosis. Previous studies suggested four-level cardiac responses using N-terminal prohormone of brain natiuretic peptide improves prognostic prediction. This study was designed to validate graded cardiac response criteria using N-terminal prohormone of brain natiuretic peptide/brain natiuretic peptide. PATIENTS AND METHODS This retrospective, multicenter study included patients with light chain amyloidosis who achieved at least a hematologic partial response (PR) and were evaluable for cardiac response. Four response criteria were tested on the basis of natriuretic peptide response depth: cardiac complete response (CarCR), cardiac very good partial response (CarVGPR), cardiac PR (CarPR), and cardiac no response (CarNR). Response was classified as best response and at fixed time points (6, 12, and 24 months from therapy initiation). The study primary outcome was overall survival. RESULTS 651 patients were included. Best CarCR, CarVGPR, CarPR, and CarNR were achieved in 16%, 26.4%, 22.9%, and 34.7% of patients, respectively. Patients in cardiac stage II were more likely to achieve CarCR than patients in cardiac stage IIIA and IIIB (22% v 13.5% v 3.2%; P < .001). A deeper cardiac response was associated with a longer survival (5-year overall survival 93%, 79%, 65%, and 33% for CarCR, CarVGPR, CarPR, and CarNR, respectively; P < .001). Fixed time-point analyses and time-varying covariates Cox regression analysis, to minimize survivorship bias, affirmed the independent survival advantage of deeper cardiac responses. Four-level response performed better than two-level response as early as 12 months from therapy initiation. CONCLUSION Graded cardiac response criteria allow better assessment of cardiac improvement compared with the traditional binary response system. The study re-emphasizes the importance of early diagnosis, which increases the likelihood of deep cardiac responses.

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 &gt;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 &gt;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, &gt;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&lt;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 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 &gt;650 pg/mL or BNP &gt;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, &gt;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 &lt;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&lt;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&lt;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&lt;0.001; Figure 1C). These cardiac response criteria were independent predictors of survival and time to cardiac progression (&gt;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.

Introduction: Light chain deposition disease (LCDD) is a rare complication of monoclonal gammopathies, defined by non-amyloid linear monoclonal light chain (most commonly kappa) deposits in the kidney and other organs. The rarity of LCDD has hampered clinical studies and staging systems and response criteria are lacking. The International Kidney Myeloma Working Group (IKMG) started a clinical data collection from all participating centers in order to define the natural history of LCDD, and to establish prognostic factors and response criteria in a large, international, unselected patient population. Methods: Eight referral centers have yet participated in the data collection at the data lock of July 31, 2020. Patient inclusion is ongoing and expected accrual is 500 patients. The diagnosis of LCDD had to be biopsy-proven. The patients were diagnosed between 1992 to 2020. Response was assessed 6 months after treatment initiation according to the criteria used in light chain (AL) amyloidosis. Renal survival (RS) was defined as time from diagnosis to dialysis or last follow-up. Patients who died without requiring dialysis were censored at the time of death. The analysis of factors predicting RS was performed in patients whose baseline estimated glomerular filtration rate (eGFR) was &gt;15 mL/min. The cutoffs of baseline variables, as well as the cutoffs measured at the time of response, best predicting RS or OS at 12 months were identified by means of Receiver Operator Characteristics (ROC) analyses. All patients gave written informed consent for their clinical data to be used for research purposes. Results: Overall, 359 patients have been included in this first analysis. Sixteen (4%) subjects had concomitant cast nephropathy. The main clinical characteristics are reported in the Table. Median overall survival (OS) was 13 years and RS was 12 years (Figure1 A and 1B) and median survival of living patients is 4.5 years. At univariate analysis the only baseline variables predicting RS were proteinuria [best cutoff 2.5 g/24h, HR 2.25 (95%CI 1.13-4.60), P=0.02], and eGFR [best cutoff &gt;30 mL/min, HR 0.50 (95%CI 0.26-0.96) P=0.037], but at multivariate analysis only proteinuria predicted RS [HR 2.17 (95% CI 1.08, 4.33), P=0.027]. At univariate analysis, a higher bone marrow plasma cell infiltrate (best cutoff ≥20%) at diagnosis was associated with a significantly lower OS [HR 1.96 (95% CI 1.23-3.13) P=0.004], as was having end stage renal disease (ESRD) defined as an eGFR &lt;15 mL/min [HR 1.81 (95%CI 1.11-2.92) P=0.015]. We then tested the ability of the hematologic response criteria for AL amyloidosis to discriminate groups with different survival after treatment in a 6 months landmark analysis. Our choice of adopting the amyloidosis response criteria was corroborated by the results of the ROC analysis showing that the difference between involved and uninvolved free light chains (dFLC) cutoff (40 mg/L) used in AL amyloidosis to define very good partial response (VGPR) had 87% sensitivity and 65% specificity in identifying patients who needed dialysis within 12 months. Partial response (PR, 19% requiring dialysis at 3 years) was not associated with a RS benefit over no-response (29% requiring dialysis at 3 years, P=0.511). However, VGPR conferred a significant RS advantage (10% requiring dialysis at 3 years) over PR (P=0.002). No significant difference in RS was seen between complete response (CR, 0% requiring dialysis at 3 years) and VGPR (P=0.178). Thus, achieving VGPR or CR by amyloidosis response criteria [post-treatment dFLC&lt;40 mg/L (VGPR by AL criteria), with or without negative serum and urine immunofixation and normal FLC-ratio (CR by AL criteria)] was adopted as a provisional criterion for hematologic response in LCDD (Figure 1D). LCDD response was also associated with prolonged OS (Figure 1C). Conclusions: Almost one-third of patients with LCDD are diagnosed when they already have ESRD resulting in shorter OS. The degree of proteinuria and of bone marrow plasma cell infiltration predict RS and OS, respectively. Achievement of post treatment dFLC &lt;40 mg/L or negative serum and urine immunofixation at 6 months is proposed as a provisional criterion for hematologic response, being able to predict both improved RS and OS. Planned expanded recruitment might allow a validation analysis of the results, the analysis of organ response data and the evaluation of different time-points for response assessment. Disclosures Milani: Celgene: Other: Travel support; Janssen: Other: Speaker honoraria; Pfizer: Other: Speaker honoraria. Kastritis:Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Consultancy, Honoraria. Schönland:Janssen, Prothena, Takeda: Honoraria, Other: travel support to meetings, Research Funding. Bridoux:Baxter: Consultancy; Janssen: Honoraria; Celgene: Honoraria. Tuchman:Celgene: Honoraria, Research Funding, Speakers Bureau; Oncopeptides: Consultancy; Amgen: Research Funding; Caelum: Honoraria; Sanofi: Honoraria, Research Funding; Janssen: Research Funding; Roche: Research Funding; Karyopharm: Honoraria, Research Funding. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Palladini:Jannsen Cilag: Honoraria, Other; Celgene: Other: Travel support. Wechalekar:Celgene: Honoraria; Caelum: Other: Advisory; Janssen: Honoraria, Other: Advisory; Takeda: Honoraria, Other: Travel.

Abstract Background: Amyloidosis is a multisystem disease with extracellular deposition of pathological insoluble beta-fibrillar proteins. Involvement of the heart is seen in more than one-half of the patients with systemic AL amyloidosis and it is the most important determinant of clinical outcome. Cardiac amyloidosis is a restrictive infiltrative cardiomyopathy in which, despite declines in stroke volume that accompany disease progression, the ejection fraction (EF) often remains preserved even in advanced stages of the disease. King et al. proposed a novel index of myocardial function, the myocardial contraction fraction (MCF), defined as the ratio of stroke volume (SV) to myocardial volume (MV). MCF is a measure of myocardial shortening, which differentiated myocardial performance in patients with similar degrees of hypertrophy and in a recent small cohort of AL amyloidosis patients appeared superior to left ventricular ejection fraction (EF) in predicting overall survival (OS). It was our goal to assess the prognostic role of MCF in a large cohort of patients with AL amyloidosis in the context of other prognostic variables. Methods: Patients seen between 4/1/1999 and 2/1/2015 were eligible for this retrospective study if they had an ECHO at the Mayo Clinic, Rochester, MN within 30 days of their AL amyloidosis diagnosis with measurements of left ventricular chamber size and wall thickness needed to calculate MCF, EF, and the presence or absence of pericardial effusion. To capture the full cohort, modeling was done first excluding Mayo (2012) staging and global averaged left ventricular longitudinal peak systolic strain (LV strain) since limited numbers of patients had these studies, 342 and 294, respectively. Thresholds of continuous variables were chosen based on receiver operator curves targeting death at 1-year. Cox proportional hazards analysis was used to identify factors that were prognostic for OS. Statistical analyses were done using JMP 9.0 (SAS, Cary, NC). Results: Among the 722 patients satisfying entry criteria,median age was 64 years (range 32-94) and 66% were male. The best cutoff for MCF was 21% (sensitivity: 74%, specificity: 60%; AUC=0.699) and distinguished two groups with different OS (median 53 vs. 9 months, P<0.0001; Figure). On univariate analysis the baseline ECHO variables predicting OS were interventricular septum thickness (IVS) >12 mm (RR 1.8, P=0.0002), EF <60% (RR 1.7), MCF ≤21% (RR 2.1), and presence of pericardial effusion (RR 2.0), all with P<0.0001. On multivariate MCF ≤21% (RR 1.6, P <0.0001), EF <60% (RR 1.4, P=0.0007) and the presence of pericardial effusion (RR 1.3, P=0.002) were independent predictors of OS. Additional modeling was done with the subset of 342 patients who were assessable for Mayo (2012) staging, (i.e. measurements of immunoglobulin free light chain, NT-proBNP, and troponin T). On univariate analysis, patients with a Mayo (2012) stage ≥ 3 had a RR 2.1, p<0.0001. On multivariate, only MCF ≤21% (RR 1.5, P =0.01), Mayo (2012) stage ≥ 3 (RR 1.5, P=0.01) and EF<60% (RR 1.7, P=0.0006) were independent prognostic determinants. Finally, we addressed LV-strain among the 294 patients in whom the study was performed. There was a significant correlation between MCF and LV strain (rho =-0.86, P<0.0001). On univariate, LV-strain less negative than -13 generated a RR of 2.3, p<0.0001. In contrast to the model containing MCF, on LV-strain multivariate, EF was no longer significant, but LV-strain less negative than -13 (RR 2.0, P=0.008) and Mayo (2012) stage ≥ 3 (RR 2.0, P=0.008) predicted independently OS. Conclusions: MCF ≤21% identified a subgroup of patients with a high mortality risk, and it was independent of the Mayo (2012) staging but highly correlated with LV strain. An advantage of MCF, which is a novel volumetric measurement of the left ventricular chamber, is that, unlike LV-strain, MCF is simple to calculate from routine ECHO measures. Figure 1. Overall survival of 722 patients according to MCF<21%. Figure 1. Overall survival of 722 patients according to MCF<21%. Disclosures Kumar: AbbVie: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Skyline, Noxxon: Honoraria; Celgene, Millenium, Sanofi, Skyline, BMS, Onyx, Noxxon,: Other: Consultant, no compensation,; Sanofi: Research Funding; Millenium/Takeda: Research Funding; Onyx: Research Funding.

Abstract Background: Both MM specific and patient specific parameters place patients at risk for death. Patient frailty has been delineated primarily by age and ECOG performance score (PS) and secondarily with creatinine, eGFR, and the International Staging System (ISS), which reflect both renal function and disease burden. In an attempt to improve upon these commonly used measures, a frailty score for elderly patients that combines functional status [Activity of Daily Living (ADL) and Instrumental Activity of Daily living scores], comorbidities [Charlson comorbidity index (CCI)] and age has been developed by the IMWG. Incorporation of these tools into a busy clinical practice is challenging due to time constraints. Therefore, the identification of frail patients with an easily applicable, rapid and objective tool remains a challenge and an unmet need. A reliable, non-invasively assessable, biochemical marker of frailty would be an ideal tool to identify patients at higher risk of death. It was our goal to determine the role of NT-proBNP, a well-established cardiovascular risk biomarker, as a marker of frailty in patients with MM and in predicting overall survival (OS). Methods: Patients were elegible for this retrospective study if they were seen at the Mayo Clinic, Rochester, MN within 30 days of their myeloma diagnosis during the interval between 1/1/2007 and 12/31/2011. As part of the Mayo Clinic registration, all patients complete forms containing their past medical history, symptoms, and ADLs. Data from that first visit was abstracted and used to calculate a CCI. We excluded all patients with a concomitant diagnosis of light-chain AL amyloidosis. NT-proBNP concentration was measured in frozen sera collected within 30 days of diagnosis. NT-proBNP assay was run on the E170 Modular analyzer (Roche Diagnostics, Penzberg, Germany). We evaluated the prognostic role of NT-proBNP and these indices on OS using the Kaplan-Meier method. Results: Among the 351 consecutive patients satisfying entry criteria, median age was 65 years (range 22-95), 33% were ≥70 years, and 56% were male. Twenty-eight percent were ISS stage III, 13% had a creatinine ≥2 mg/dL, 19% had PS ≥2, and 11% had ADL score ≥2, and 30% CCI ≥2. The median value of NT-proBNP was 109 ng/L (interquartile range: 30-375 ng/L). NT-proBNP concentrations differed in the three ISS stages (median: 122 ng/L stage I, 190 ng/L stage II and 1822 ng/L stage III, P<0.0001). Median OS was 5.6 years. The best cutoff of NT-proBNP predicting OS at one year was 301 ng/L (sensitivity: 57.88%, specificity: 74.29%; AUC=0.668) and distinguished two groups with different OS (median not reached vs. 35 months, P<0.0001). Variables predictive for OS are shown in the Table and included PS, age, CCI, ISS, NT-proBNP. On multivariate analysis, ISS and NT-proBNP were independent of each other as long as age, PS and/or CCI were excluded from the model. NT-proBNP withstood these clinical variables better than did ISS (data not shown). We built two different models (table). In model 1, NT-proBNP >301 ng/L was an independent predictor of survival while age ≥70 and PS ≥2 and CCI were not significant. However, if we considered ISS stage instead of NT-proBNP in the same model, ISS stage was not significant. Conclusions: In this unselected cohort of patients with newly diagnosed multiple myeloma, NT-proBNP was a useful predictor of survival independent of age and PS. The threshold of 301 ng/L is remarkably similar to the well-established cutoff for heart failure of 300 ng/L. NT-proBNP outperformed the CCI and the ISS as risk factors. NT-proBNP is a widely available biomarker that could be added to the panel of laboratory tests of newly diagnosed MM patients and serve as a simple means of determining patient frailty in a busy clinical practice. Table. Results of univariate and multivariate analysis of various prognostic factors (NS, not significant; NI, not included). Univariate Multivariate Multivariate RR (95% CI) P Model 1 P Model 2 P PS ≥2 3.4 (2.4-4.8) <0.0001 2.5 (1.7-3.6) <0.0001 2.8 (1.9-4.0) <0.0001 Age ≥70 2.7 (1.9-3.6) <0.0001 2.1 (1.5-2.9) <0.0001 1.9 (1.3-2.7) 0.0003 CCI >=2 1.9 (1.4-2.6) <0.0001 NS NS 1.5 (1.0-2.0) 0.03 ISS stage 1.1 (1.1-1.8) 0.0004 NI NI NS NS NT-proBNP >301 ng/L 2.3 (1.7-3.2) <0.0001 1.6 (1.1-2.2) 0.007 NI NI Disclosures Merlini: Janssen-Cilag: Honoraria; Prothena: Honoraria; Millennium-Takeda: Honoraria; Pfizer: Honoraria. Kumar:Janssen: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Millenium/Takeda: Research Funding; AbbVie: Research Funding; Onyx: Research Funding; Celgene, Millenium, Sanofi, Skyline, BMS, Onyx, Noxxon,: Other: Consultant, no compensation,; Skyline, Noxxon: Honoraria.

Abstract AL is a rare plasma cell disorder, resulting from clonal bone marrow plasma cells secreting immunoglobulin light chains (LC), which aggregate abnormally into fibrils, and leads to amyloid deposits in different organs. Previous studies using LC immunopurification and MALDI-TOF/MS (MASS-FIX) on patients with known plasma cell disorders (PCDs), demonstrated that monoclonal LC from AL patients display unusually complex mass to charge spectra (m/z) for their LCs at much higher frequencies than other PCDs such as multiple myeloma. We hypothesized that these were post-translational modification, presumably glycoforms. Here, we report investigations into LC glycosylation using MASS- FIX. Serum from 212 lambda and 72 kappa AL patients were collected following Mayo Clinic IRB guidelines. LC was purified from serum using nanobody enrichment method, followed by MASS-FIX. The LCs spectra acquired on MASS-FIX were visually analyzed and were classified into different patterns. The kappa and lambda LC mass distributions with abnormal complex patterns were interrogated for the presence of glycosylation by exposure to the LC to a deglycoslylating enzyme (PNGase F) and analysis of LC mass distribution using MASS-FIX and by LC-ESI-Orbitrap. Monoclonal LCs demonstrating significantly mass shifted peak outside the normal kappa and lambda mass distribution were observed in 31% of kappa and 6% of lambda patients with AL. In order to determine if this characteristic mass shift was due to glycosylation, 16 kappa and 6 lambda LCs were treated with a PNGase F and LC spectrum were re-examined by MASS-FIX and LC-ESI-Orbitrap. The monoclonal LCs whose masses were significantly shifted beyond normal kappa and lambda mass distributions were found to shift to lower molecular weight after PNGase F treatment, confirming the presence of N-glycosylation. Moreover, an additional 5 kappa and 23 lambda samples had other complex patterns, typically with multiple additional peaks at increments of 162 Da. These samples did not shift with PNGase F suggesting either glycation or O-glycosylation. This work is significant as it confirms that N-glycosylated LCs are over represented in patients with AL in comparison to other PCDs. In patients with AL, the frequency of N-glycosylation of kappa LC clones was 5 times higher than that of lambda LC clones. More work is needed to explore the mechanism for this finding, the role of glycosylation in fibril formation, and the other complex patterns observed. In addition, MASS-FIX method used in this work is currently being validated in the clinical lab such that rapid detection of N-glycosylation in patients with monoclonal gammopathies will be possible routinely, potentially leading to earlier clinical suspicion for AL among patients with monoclonal gammopathies and hence to earlier detection of AL. Citation Format: Sanjay Kumar, Angela Dispenzieri, Surendra Dasari, Paolo Milani, Giampaolo Merlini, MeLea Hetrick, David Barnidge, Benjamin Madden, David Murray. Mass spectrometric approach to identify N-glycosylation of light chain in patients with immunoglobulin light chain amyloidosis (AL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2693.

Background: Heart involvement is the most important prognostic determinant in AL amyloidosis patients. Echocardiography is a cornerstone for the diagnosis and provides important prognostic information. Methods and Results: We studied 754 patients with AL amyloidosis who underwent echocardiographic assessment at the Mayo Clinic, including a Doppler-derived measurement of stroke volume (SV) within 30 days of their diagnosis to explore the prognostic role of echocardiographic variables in the context of a well-established soluble cardiac biomarker staging system. Reproducibility of SV, myocardial contraction fraction, and left ventricular strain was assessed in a separate, yet comparable, study cohort of 150 patients from the Pavia Amyloidosis Center. The echocardiographic measures most predictive for overall survival were SV index <33 mL/min, myocardial contraction fraction <34%, and cardiac index <2.4 L/min/m 2 with respective hazard ratios (95% confidence intervals) of 2.95 (2.37–3.66), 2.36 (1.96–2.85), and 2.32 (1.91–2.80). For the subset that had left ventricular strain performed, the prognostic cut point was −14% (hazard ratios, 2.70; 95% confidence intervals, 1.84–3.96). Each parameter was independent of systolic blood pressure, Mayo staging system (NT-proBNP [N-terminal pro-B-type natriuretic peptide] and troponin), and ejection fraction on multivariable analysis. Simple predictive models for survival, including biomarker staging along with SV index or left ventricular strain, were generated. Conclusions: SV index prognostic performance was similar to left ventricular strain in predicting survival in AL amyloidosis, independently of biomarker staging. Because SV index is routinely calculated and widely available, it could serve as the preferred echocardiographic measure to predict outcomes in AL amyloidosis patients.