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INTRODUCTION: The amyloidoses are a group of protein-folding disorders characterized by extracellular tissue deposition of aggregated proteins as ß-pleated sheet fibrils. One of the most common and severe types is immunoglobulin light chain (AL), or "primary", amyloidosis. Prior studies of healthcare cost and resource use were hampered by the absence of an International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code specific to AL amyloidosis. Since 10/1/2017, the ICD-10-CM has included a diagnosis code for AL amyloidosis (E85.81). We believe the current study is the first to report healthcare cost and resource use using this new code. METHODS: To understand characteristics, healthcare resource utilization, costs, and clinical outcomes associated with AL amyloidosis for patients treated in US hospitals, this retrospective analysis used 2017-2020 data from the Premier Perspective® Database. The study population comprised of hospitalized patients aged ≥18 years with ≥1 inpatient claim consistent with AL amyloidosis (ICD-10-CM: E85.81) in any diagnosis field; the first qualifying hospitalization during the study period was included. Study outcomes included APR-DRG severity of illness subclass (a measure of disease burden based on the extent of organ system loss of function or physiologic decompensation), length of stay (LOS), intensive care unit (ICU) use, mortality and hospitalization costs and charges as reported in the database (inflated to 2020 USD). To provide context, we compared costs and charges to most recent national averages calculated from the 2018 National Impatient Sample (NIS). We will also tabulate NT-proBNP, troponin and differential free light chain values and report Mayo stage when possible. RESULTS: 1,341 patients were admitted to the hospital with a diagnosis of AL amyloidosis; mean (SD) age was 67.2 (11.2) years, 44.1% were female, 64.3% were White, and 62.4% had Medicare coverage. The mean (SD) Charlson Comorbidity Index was 3.9 (2.3), and 90.9% of patients had cardiac and/or renal impairment (Table 1). More than 80% of patients had either major or extreme disease according to the APR-DRG severity of illness measure. 87.6% of admissions were urgent or emergent, and 8.0% (95% CI [6.5%,9.4%]) of admitted patients died in the hospital. The mean (SD) LOS was 9.5 (9.7) days (Figure 1); during the hospital stay, 20.1% of patients were admitted to the ICU, with a mean (SD) ICU LOS of 6.5 (7.6) days (Table 2). The mean (SD) total hospitalization costs were $27,099 ($34,849) and total charges were $111,234 ($144,853) for hospitalized patients with AL amyloidosis while similar measures for all US hospital stays were $13,702 ($121) and $57,991 ($694), respectively (Figure 2). CONCLUSIONS: Disease burden and hospital costs associated with AL amyloidosis are high, particularly within this group of patients who have advanced disease as indicated by the APR-DRG classification. Mean hospitalization costs were above $27,000 per patient and many patients were admitted to the ICU. New therapies aimed at improving survival and providing clinical benefits have the potential to reduce disease burden and to yield substantial cost savings. Figure 1 Figure 1. Disclosures Quock: Prothena Biosciences, Inc: Current Employment. Chang: Dompe US, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Dompe US, Inc. to conduct research; Mirum Pharmaceuticals, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Mirum Pharmaceuticals, Inc. to conduct research; Greenwich Biosciences, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Greenwich Biosciences to conduct research; Genentech, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Genentech to conduct research; Verde Technologies: Other: I am an employee of PHAR, LLC, which was paid by Verde Technologies to conduct research; Sage: Other: I am an employee of PHAR, LLC, which was paid by Sage to conduct research; Prothena: Other: I am an employee of PHAR, LLC, which was paid by Prothena to conduct research; Pathnostics: Other: I am an employee of PHAR, LLC, which was paid by Pathnostics to conduct research; Otsuka: Other: I am an employee of PHAR, LLC, which was paid by Otsuka to conduct research; Novartis: Other: I am an employee of PHAR, LLC, which was paid by Novartis to conduct research; Kite: Other: I am an employee of PHAR, LLC, which was paid by Kite to conduct research; Jazz: Other: I am an employee of PHAR, LLC, which was paid by Jazz to conduct research; Ionis: Other: I am an employee of PHAR, LLC, which was paid by Ionis to conduct research; Illumina: Other: I am an employee of PHAR, LLC, which was paid by Illumina to conduct research; Helsinn: Other: I am an employee of PHAR, LLC, which was paid by Helsinn to conduct research; GRAIL: Other: I am an employee of PHAR, LLC, which was paid by GRAIL to conduct research; Ethicon: Other: I am an employee of PHAR, LLC, which was paid by Ethicon to conduct research; Eisai: Other: I am an employee of PHAR, LLC, which was paid by Eisai to conduct research; Celgene: Other: I am an employee of PHAR, LLC, which was paid by Celgene to conduct research; Boston Scientific Corporation: Other: I am an employee of PHAR, LLC, which was paid by Boston Scientific Corporation to conduct research; Bristol Myers Squibb: Other: I am an employee of PHAR, LLC, which was paid by BMS to conduct research; AstraZeneca: Other: I am an employee of PHAR, LLC, which was paid by AstraZeneca to conduct research; Amgen: Other: I am an employee of PHAR, LLC, which was paid by Amgen to conduct research; Akcea: Other: I am an employee of PHAR, LLC, which was paid by Akcea to conduct research; AbbVie: Other: I am an employee of PHAR, LLC, which was paid by AbbVie to conduct research; Partnership for Health Analytic Research (PHAR), LLC: Current Employment, Other; Sanofi US Services, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Sanofi US Services Inc. to conduct research; Sunovion Pharmaceuticals, Inc.: Other: I am an employee of PHAR, LLC which was paid by Sunovion Pharmaceuticals, Inc. to conduct research. ; BioMarin Pharmaceuticals Inc.: Other: I am an employee of PHAR, LLC which was paid by BioMarin Pharmaceuticals, Inc. to conduct research. ; Takeda Pharmaceuticals U.S.A., Inc.: Other: I am an employee of PHAR, LLC which was paid by Takeda Pharmaceuticals U.S.A., Inc., to conduct research. ; Exact Sciences Corporation: Other: I am an employee of PHAR, LLC which was paid by Exact Sciences Corporation to conduct research. . Bognar: Prothena Biosciences, Inc: Other: I am an employee at Partnership for Health Analytic Research LLC which received funding from Prothena Biosciences, Inc. to conduct the research described in this abstract.; Akcea: Other: I am an employee of PHAR, LLC, which was paid by Akcea to conduct research; Amgen: Other: I am an employee of PHAR, LLC, which was paid by Amgen to conduct research; AstraZeneca: Other: I am an employee of PHAR, LLC, which was paid by AstraZeneca to conduct research; BMS: Other: I am an employee of PHAR, LLC, which was paid by BMS to conduct research; Boston Scientific Corporation: Other: I am an employee of PHAR, LLC, which was paid by Boston Scientific Corporation to conduct research; Celgene: Other: I am an employee of PHAR, LLC, which was paid by Celgene to conduct research; Eisai: Other: I am an employee of PHAR, LLC, which was paid by Eisai to conduct research; Ethicon: Other: I am an employee of PHAR, LLC, which was paid by Ethicon to conduct research; GRAIL: Other: I am an employee of PHAR, LLC, which was paid by GRAIL to conduct research; Helsinn: Other: I am an employee of PHAR, LLC, which was paid by Helsinn to conduct research; Illumina: Other: I am an employee of PHAR, LLC, which was paid by Illumina to conduct research; Ionis: Other: I am an employee of PHAR, LLC, which was paid by Ionis to conduct research; Jazz: Other: I am an employee of PHAR, LLC, which was paid by Jazz to conduct research; Kite: Other: I am an employee of PHAR, LLC, which was paid by Kite to conduct research; Novartis: Other: I am an employee of PHAR, LLC, which was paid by Novartis to conduct research; Otsuka: Other: I am an employee of PHAR, LLC, which was paid by Otsuka to conduct research; Pathnostics: Other: I am an employee of PHAR, LLC, which was paid by Pathnostics to conduct research; Sage: Other: I am an employee of PHAR, LLC, which was paid by Sage to conduct research; Verde Technologies: Other: I am an employee of PHAR, LLC, which was paid by Verde Technologies to conduct research; Genentech, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Genentech to conduct research; Greenwich Biosciences, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Greenwich Biosciences to conduct research; Mirum Pharmaceuticals, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Mirum Pharmaceuticals to conduct research; Dompe US, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Dompe US to conduct research; Sanofi US Services, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Sanofi US to conduct research; Sunovion Pharmaceuticals, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Sunovian to conduct research; BioMarin Pharmaceuticals Inc.: Other: I am an employee of PHAR, LLC, which was paid by BioMarin to conduct research; Takeda Pharmaceuticals U.S.A., Inc.: Other: I am an employee of PHAR, LLC, which was paid by Takeda to conduct research; Exact Sciences Corporation: Other: I am an employee of PHAR, LLC, which was paid by Exact Sciences to conduct research. D'Souza: Sanofi, Takeda, Teneobio, CAELUM, Prothena: Research Funding; Janssen, Prothena: Consultancy; Imbrium, Pfizer, BMS: Membership on an entity's Board of Directors or advisory committees. Broder: Prothena Biosciences, Inc: Other: I am an employee at Partnership for Health Analytic Research LLC which received funding from Prothena Biosciences, Inc. to conduct the research described in this abstract.; Akcea: Other: I am an employee of PHAR, LLC, which was paid by Akcea to conduct research; Amgen: Other: I am an employee of PHAR, LLC, which was paid by Amgen to conduct research; AstraZeneca: Other: I am an employee of PHAR, LLC, which was paid by AstraZeneca to conduct research; BMS: Other: I am an employee of PHAR, LLC, which was paid by BMS to conduct research; Boston Scientific Corporation: Other: I am an employee of PHAR, LLC, which was paid by Boston Scientific Corporation to conduct research; Celgene: Other: I am an employee of PHAR, LLC, which was paid by Celgene to conduct research; Eisai: Other: I am an employee of PHAR, LLC, which was paid by Eisai to conduct research; Ethicon: Other: I am an employee of PHAR, LLC, which was paid by Ethicon to conduct research; GRAIL: Other: I am an employee of PHAR, LLC, which was paid by GRAIL to conduct research; Helsinn: Other: I am an employee of PHAR, LLC, which was paid by Helsinn to conduct research; Illumina: Other: I am an employee of PHAR, LLC, which was paid by Illumina to conduct research; Ionis: Other: I am an employee of PHAR, LLC, which was paid by Ionis to conduct research; Jazz: Other: I am an employee of PHAR, LLC, which was paid by Jazz to conduct research; Kite: Other: I am an employee of PHAR, LLC, which was paid by Kite to conduct research; Novartis: Other: I am an employee of PHAR, LLC, which was paid by Novartis to conduct research; Otsuka: Other: I am an employee of PHAR, LLC, which was paid by Otsuka to conduct research; Pathnostics: Other: I am an employee of PHAR, LLC, which was paid by Pathnostics to conduct research; Prothena: Other: I am an employee of PHAR, LLC, which was paid by Prothena to conduct research; Sage: Other: I am an employee of PHAR, LLC, which was paid by Sage to conduct research; Verde Technologies: Other: I am an employee of PHAR, LLC, which was paid by Verde Technologies to conduct research; Genentech, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Genentech to conduct research; Greenwich Biosciences, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Greenwich Biosciences to conduct research; Mirum Pharmaceuticals, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Mirum Pharmaceuticals, Inc. to conduct research; Dompe US, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Dompe US, Inc. to conduct research; Sanofi US Services, Inc.: Other: I am an employee of PHAR, LLC, which was paid by Sanofi US Services Inc. to conduct research; Sunovion Pharmaceuticals, Inc.: Other: I am an employee of PHAR, LLC which was paid by Sunovion Pharmaceuticals, Inc. to conduct research. ; BioMarin Pharmaceuticals Inc.: Other: I am an employee of PHAR, LLC which was paid by BioMarin Pharmaceuticals, Inc. to conduct research. ; Takeda Pharmaceuticals U.S.A., Inc.: Other: I am an employee of PHAR, LLC which was paid by Takeda Pharmaceuticals U.S.A., Inc., to conduct research. ; Exact Sciences Corporation: Other: I am an employee of PHAR, LLC which was paid by Exact Sciences Corporation to conduct research. .

Introduction Hepatic veno-occlusive disease (VOD), also known as sinusoidal obstruction syndrome (SOS) is a potentially fatal complication of HSCT and is characterized by hepatomegaly, right upper quadrant pain, jaundice, and ascites (Gratwohl A et al JAMA 2010). Severe VOD (sVOD) is clinically characterized by multi-organ dysfunction and is estimated to have a mortality rate of over 80% (Coppell JA et al BBMT 2010). VOD and particularly sVOD pose a significant economic burden in direct medical costs by adding an estimated $53,000 to HSCT (2004 U.S. dollars; Saito et al BBMT 2008), or $78,000 in 2015 dollars. However, little research has been conducted in ascertaining the indirect costs associated with premature death due to VOD. In our study, we developed an economic model to evaluate the indirect cost associated with premature death due to sVOD among HSCT patients in the U.S. Methods An Excel-based model was developed to estimate the indirect cost associated with premature death due to sVOD among HSCT patients. Model inputs included prevalence of sVOD as well as mortality, age, salary, employment rate, and life expectancy. Inputs were obtained from the published literature, Center for International Blood & Marrow Transplant Research (CIBMTR), Centers for Disease Control and Prevention (CDC), U.S. Census Bureau, and Organisation for Economic Co-operation and Development (OECD). The model considered lost productivity as the result of premature death by calculating the number of years between the age of sVOD-related death and the assumed age of retirement (65 years old); it was assumed that the lifetime salary reflected underlying productivity of HSCT survivors who did not develop sVOD. Annual salary and life expectancy among HSCT survivors were adjusted from the general population to reflect decreased productivity in the first 2 years immediately following HSCT. Annual average salary inputs by age categories were assumed to be the same as the general population. Age of the working population was assumed to be between 18 and 65 years old. Excess mortality from sVOD was calculated as number of deaths among sVOD patients minus the number of deaths among HSCT patients who did not develop sVOD. Indirect cost was expressed as the cumulative salary for all productive years contributed by a patient and included a 3% discount for each additional year. Total lost productivity years and indirect costs by age category were obtained by multiplying each respective per patient value by the number of excess deaths in each age category. A sensitivity analysis was performed to examine the impact of changes in key model parameters on model results. Results The model estimated 361 excess deaths per year due to sVOD in the HSCT population. The excess deaths due to sVOD were associated with indirect costs of over $68 million due to reduced life expectancy and consequent productivity loss. AlloSCT patients were younger on average, resulting in greater indirect costs ($39 million) compared to AutoSCT ($29 million). AlloSCT patients lost 3,637 productive years on average compared to 2,353 lost productive years for AutoSCT patients despite fewer patients receiving AlloSCT than AutoSCT. A sensitivity analysis showed that the total indirect costs due to overall VOD (non-severe and severe) were as high as $73.3 million. Conclusion sVOD imposes a substantial economic burden on patients in terms of excess deaths, lost productivity, and indirect costs. The model underestimates indirect costs largely due to not accounting for productivity loss among children and their caregivers or those older than 65. It also does not calculate productivity loss among HSCT survivors. Future research is warranted to elicit the additional indirect costs associated with non-severe VOD. Figure 3. Deterministic Sensitivity Analysis: Total Indirect Costs due to Excess Deaths due to sVOD Compared with HSCT Survivors without VOD. Figure 3. Deterministic Sensitivity Analysis: Total Indirect Costs due to Excess Deaths due to sVOD Compared with HSCT Survivors without VOD. Disclosures Quock: Jazz Pharmaceuticals: Employment, Equity Ownership. Zhou:Jazz Pharmaceuticals: Other: Analysis Group received funding for this analysis from Jazz Pharmaceuticals, Inc.; Analysis Group: Employment. Dai:Jazz Pharmaceuticals: Other: Analysis Group received funding for this analysis from Jazz Pharmaceuticals, Inc.; Analysis Group: Employment. Tang:Jazz Pharmaceuticals: Other: Analysis Group received funding for this analysis from Jazz Pharmaceuticals, Inc.; Analysis Group: Employment. Villa:Jazz Pharmaceuticals: Employment, Equity Ownership.