Predictors of 30-day Readmissions Post-CAR-T in Patients with Relapsed/Refractory Multiple Myeloma using the United States Nationwide Readmission Database

Predictors of 30-day Readmissions Post-CAR-T in Patients with Relapsed/Refractory Multiple Myeloma using the United States Nationwide Readmission Database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Predictors of 30-day Readmissions Post-CAR-T in Patients with Relapsed/Refractory Multiple Myeloma using the United States Nationwide Readmission Database Raj Shah, Nikhil Vojjala, Tiewei Cheng, Charmi Bhanushali, Sanjana Mullangi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8571194/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Annals of Hematology → Version 1 posted 7 You are reading this latest preprint version Abstract B-cell maturation antigen (BCMA)-directed chimeric antigen receptor T-cell (CAR-T) therapy has changed the therapeutic landscape of relapsed/refractory multiple myeloma (RRMM). Despite the efficacy, these products have been associated with an adverse effect profile including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), which require monitoring and early intervention. This is a retrospective cohort study using the National Readmission Database (NRD) aimed at evaluating hospital outcomes, economic burden, and readmission risks for ide-cel and cilta-cel in a real-world cohort of RRMM patients treated across various hospitals in the USA. During the study period,1291 RRMM patients receiving BCMA CAR-T cell therapy were identified in the United States. After excluding December admissions to allow for 30-day follow-up, 1180 patients were included in the final analysis. We found a 17% readmission rate within 30 days, with immune effector cell–related complications and infections constituting the most common causes of readmission. These findings highlight the significant clinical and economic burden of post-CAR-T care, despite the transformative impact of these therapies on outcomes for RRMM. Main B-cell maturation antigen (BCMA)-directed chimeric antigen receptor T-cell (CAR-T) therapy has changed the therapeutic landscape of relapsed/refractory multiple myeloma (RRMM). As of November 2025, the FDA has approved Idecabtagene vicleucel (Ide-cel) and Ciltacabtagene autoleucel (Cilta-cel); both these products have demonstrated overall response rates between 73% and 98% in various clinical trials. 1–3 Despite the efficacy, these products have been associated with an adverse effect profile including cytokine release syndrome (CRS), and immune effector cell-associated neurotoxicity syndrome (ICANS), which require monitoring and early intervention 4 . Our study aimed to evaluate the hospital outcomes, economic burden, and readmission risks for ide-cel and cilta-cel using a real-world cohort of RRMM population treated across various hospitals in the USA. This is a retrospective cohort study using the National Readmission Database (NRD), which included data from January 1, 2021, to November 30, 2022. The NRD is an administrative database developed by the Agency for Healthcare Research and Quality for the Healthcare Cost and Utilization Project (HCUP). This extensive, publicly available database contains de-identified patient information and hospital-level data on approximately 35 million hospital discharges. All adult patients (≥ 18 years) with RRMM having a primary discharge diagnosis of RRMM having a procedure diagnosis of CAR-T cell administration were included in the study. Product-specific data is obtained using product-specific codes. Medical comorbidities, including hypertension, type 2 diabetes mellitus, obesity, coronary artery disease, atrial fibrillation, congestive heart failure, and chronic kidney disease, pre-existing neurological diseases were identified as additional secondary diagnoses (I10-DX2) using coding algorithms (Supplementary Table 1 ). In addition, several patient-level (age, sex, race, primary payer (Medicare, Medicaid, private insurance, and uninsured)) and hospital-level (bed size (small, medium, and large), teaching status, location (rural or urban), geographic region (Northeast, Midwest, West, or South)) variables were also extracted. Additionally, in-hospital complications such as cytopenias, CAR-T related complications like CRS, ICANS, and Hemophagocytic Lymphohistiocytosis (HLH) were also captured. The primary outcome during index hospitalization is in-hospital mortality. Subsequently, we extracted 30-day readmission rates and identified key predictors of 30-day readmission. We used the Student’s t-test for Continuous variables and the Pearson χ2 test to obtain percentages for categorical variables. A univariate analysis was used to identify variables associated with readmissions post CAR-T therapy to obtain independent predictors of 30-day all-cause readmission. We included those variables having a p-value <0.2 in the final multivariate regression analysis to identify predictors of 30-day readmissions. All analyses were performed using STATA, version 18 (StataCorp, College Station, TX, USA). During the study period,1291 RRMM patients receiving BCMA CAR-T cell therapy were identified in the United States. After excluding December admissions to allow for 30-day follow-up, 1180 patients were included in the final analysis. Out of 1180 patients, 965 (82%) received Ide-Cel and 215 (18%) received Cilta-Cel. The mean age (±SD) of the study cohort is 62.9 years (±1.1), with most participants being males (n = 732, 62%). Most patients were treated at urban teaching hospitals with large bed sizes (n = 944, 80.0%) and resided in the same state as their treatment center (n = 956, 81%). Socioeconomic distribution showed that 37% (n=437) belonged to the highest income quartiles, with Medicare being the most common insurance coverage (n= 602,51%). The most common identifiable comorbidities included hypertension (36%), diabetes mellitus (14.11%), and chronic kidney disease (7.4%). 15% of patients have the diagnosis of protein-energy malnutrition (PEM). Pre-existing neurological diseases included dementia (2.5%), Parkinson’s disease (3.2%), and 25% reported sleep disorders. A history of alcohol use disorder was present in 0.3%, and 25% were current smokers. 52.6% (n= 620) had a prior history of autologous stem cell transplant. (Table 1). Notably, 38% of patients developed neutropenia and 7.1% developed hypogammaglobulinemia during index admission. However, 4.3% of the index admissions developed sepsis, and 1.6% developed septic shock. CMV infection was seen in 2% of the hospitalizations, and Clostridium difficile infection was seen in 3.3% of the hospitalizations. 11% of patients developed anemia requiring blood transfusion, and 12.8% developed thrombocytopenia. Among CAR-T related complications, 68.4% developed CRS, of which 5.3% required Tocilizumab, 1.1% developed HLH, and 7.6% developed ICANS (Grades- 1, 40%, 2- 32.5%, 3-7.3%). The incidence of ICANS in Ide-Cel was 7.1% and Cilta Cel was 9.4%. In terms of primary outcomes, the mean length of stay was 16 days for Cilta-Cel and 14.3 days for Ide-Cel. Inpatient mortality was 3.6% for Cilta-Cel and 2.3% for Ide-Cel. Among survivors, 83.1% were discharged home and 2.6% were sent to a skilled nursing facility. Of 1155 alive discharges, 226 were readmitted in 30 days with a readmission rate of 17%. In subgroup analysis, the 30-day readmission rates are 18% for Cilta-cel compared to 16% for Ide-cel (p = 0.65). Immune effector complications constituted the single most common cause of readmission (n=75, 33%), followed by infections (n=39,17.3%). Thrombotic and bleeding complications accounted for 4.7% (n=11). Mean LOS (±SD) during readmission is 6.5 days (±0.77) with 7% mortality during readmission. The mean hospitalization charge during readmission was $105,390. Those significant on univariate analysis with a p-value>0.2 were included in the multivariate model. On multivariate logistic regression analysis, several predictors were identified for 30-day readmissions. HLH (HR 3.42, p<0.001), mechanical ventilation (HR 11.30, P<0.012) non-metropolitan hospital setting (HR 4.77, p<0.001) were associated with significantly higher readmission rates. CRS (HR 0.46, P<0.001) was paradoxically found to have lower readmission rates. Conversely, no significant correlation was found between other comorbidities and prior transplant status. (Table 2) Our nationwide analysis provides one of the most comprehensive assessments of 30-day readmission rates and predictors of readmission following BCMA-directed CAR-T therapy in RRMM. We found a 17% readmission rate within 30 days, with immune effector cell–related complications and infections constituting the most common causes of readmission. These findings highlight the significant clinical and economic burden of post-CAR-T care, despite the transformative impact of these therapies on outcomes for RRMM. Compared to other real-world studies, our observed readmission rate in RRMM is consistent with reported post-CAR-T outcomes in diffuse large B-cell lymphoma, where 30-day readmissions range between 15% and 20%. 5,6 The comparable magnitude suggests that, despite differences in disease biology and targets, CAR-T uniformly carries a high risk of early readmission. Specifically, immune effector complications accounted for one-third of all readmissions in our cohort, highlighting that the toxicities of CAR-T persist beyond index admission. Infections were the second most common cause of readmission, likely due to profound and prolonged cytopenias observed in this patient population. 7,8 Together, these results support vigilant outpatient surveillance with structured monitoring protocols, timely immunoglobulin replacement, and aggressive infection prophylaxis strategies. 8 Our regression analysis identifies several notable predictors of readmission. Mechanical ventilation during index admission confers an exceptionally high risk of readmission, reflecting the severity of acute toxicities of CAR-T therapy during index admission that negatively impact long-term non-disease-related outcomes. Similarly, patients with HLH had a four-fold higher readmission risk, which may mirror both the aggressive disease course and the need for prolonged immunosuppression. Patients discharged to skilled nursing facilities also had a significantly increased risk, possibly due to higher baseline frailty and limited capacity for specialized toxicity management in post-acute settings. Interestingly, treatment at non-metropolitan hospitals was associated with higher readmission rates, which may reflect disparities in supportive infrastructure, access to subspecialty care, or availability of standardized CAR-T monitoring programs. Patients with CRS had lower readmission rates, which could be due to more intense post-hospital monitoring. These findings emphasize the importance of multidisciplinary post-CAR-T care pathways, particularly in non-tertiary centers. Notably, patient comorbidities such as diabetes, chronic kidney disease, and cardiovascular disease did not emerge as significant predictors. This suggests that disease- and treatment-related factors outweigh baseline comorbidity in driving early readmissions. Moreover, no significant difference in readmission risk was observed between ide-cel and cilta-cel, reinforcing that toxicity management strategies need to be broadly applicable across CAR-T products. 9 Previously, the FDA-mandated Risk Evaluation and Mitigation Strategy (REMS) program required institutions administering CAR-T to be specially certified, maintain staff trained in recognizing and managing toxicities, and ensure 24/7 availability of tocilizumab and intensive care support. These structured frameworks are designed to reduce morbidity and mortality from immune effector cell–associated toxicities. The removal of REMS requirements will need to be met with increased education on close outpatient monitoring and seamless communication between certified centers and community providers. 10 We acknowledge several limitations of our study. The use of an administrative database introduces potential coding errors and precludes the collection of granular data on CAR-T manufacturing, prior lines of therapy, and toxicity grading. Additionally, we lacked information on outpatient interventions such as prophylactic antimicrobials or immunoglobulin replacement, which may influence readmission risk. The NRD excludes discharges with missing or unverified patient linkage numbers, which may result in underestimation of readmission rates. Patients who are transferred to a different hospital or readmitted in a different state than their index hospitalization were not included in the dataset. Despite these limitations, the large sample size and real-world national scope provide robust insights into post-CAR-T readmissions. In conclusion, nearly one in six RRMM patients undergoing BCMA CAR-T therapy experience a 30-day readmission, predominantly due to immune effector toxicities and infections. Identifying patients at the highest risk and implementing proactive post-discharge strategies, including reinforcement of REMS principles in outpatient practice, will be essential to improve patient outcomes, reduce healthcare utilization, and maximize the transformative potential of BCMA CAR-T therapy. Table 1: Baseline characteristics, in-hospital outcomes, and readmission rates: Variable (%) CAR-T in RRMM (n=1180) (%) Mean age (±SD) 62.8 (± 1.0) Males (%) 62% Primary expected payer Medicare Medicaid Private Other 618 (52.4) 42 (3.6) 512(43.4) 8 (0.6) Income Quartiles 1 st quarter 2 nd quarter 3 rd quarter 4 th quarter 198 (16.8) 245 (20.8) 297(25.2) 440 (37.2) Hospital bed size Small Medium Large 174 (14.8) 66 (5.6) 940 (79.6) State of residency Same state as the CAR-T center Other state 956 (81) 224 (19) Comorbidities Hypertension Type 2 Diabetes Mellitus Obesity Coronary artery disease Congestive heart failure Atrial fibrillation Chronic kidney disease Protein-calorie malnutrition Smoking status Alcohol Dementia Parkinsons Sleep disorders 425(36) 165 (14) 106 (9) 94 (8) 80 (6.8) 130 (11) 87 (7.4) 184 (15.6) 295(25) <10 30(2.5) 38(3.2 295(25) History of ASTCT 620(52.6) Type of CAR-T Cilta Cel Ide Cel 215 (18) 965 (82) In hospital complications Acute Kidney Injury Septic shock CMV infection Clostridium difficile infection 215 (18.3) 18 (1.5) 24 (2.0) 49 (3.3) CAR-T related complications Neutropenia Thrombocytopenia Hypogammaglobinemia CRS (any grade) ICANS HLH 448 (38) 153 (13) 84 (7.1) 802 (68) 89 (7.5) 11 (1.1) Procedures Blood transfusion Mechanical Ventilation Tocilizumab use 130 (11) 12(1.0) 62 (5.3) ICU stay 300 (25.4) Disposition of the patient Home Home with HHC SNF Other 979 (83.1) 139 (11.8) 30 (2.5) 32(2.6) Outcomes Mortality Length of stay (±SD) -Cilta cel -Ide Cel Total Hospitalization charges -Cilta Cel -Ide Cel 30-day readmission rates (Overall) -Cilta Cel -Ide Cel 25 (2.1) 16days (±0.9) 14 days (±0.9) 1363757 1161199 200(17%) 40(18%) 160(16%) Causes of 30-day re-admission Immune effector complications Infections Disease progression Thrombosis & bleeding Others 75 (33.0) 39 (17.3) 33 (14.7) 11 (4.7) 67 (30) Abbreviations: CAR-T: Chimeric antigen receptor T-cell therapy, RRMM: Relapsed/refractory multiple myeloma, SD: Standard deviation, ASTCT: Autologous stem cell transplantation, Cilta Cel: Ciltacabtagene autoleucel, Ide Cel: Idecabatagene vicileucel, CMV: Cytomegalovirus, CRS: Cytokine release syndrome, ICANS: Immune effector cell-associated neurotoxicity syndrome, HLH: Hemophagocytic lymphohistiocytosis, ICU: Intensive care unit, HHC: Home health care, SNF: Skilled nursing facility Table 2: Predictors of 30-day readmission in patients post BCMA CAR-T cell therapy Predictor Hazard Ratio P-value 95% Confidence Interval Hospital urban/rural category (Non metro) 4.77 0.000 2.14-10.61 Mechanical ventilation 11.30 0.012 1.70-75.13 HLH 3.42 0.028 1.14-10.23 CRS 0.46 0.001 0.29- 0.73 Borderline significant predictors (p value 0.05 to 0.1) Parkinsons disease 4.27 0.057 0.96-19.06 Administration of Tocilizumab 0.19 0.099 0.03-1.36 Hypertension 0.57 0.109 0.28-1.13 Length of Stay 1.02 0.134 0.99-1.05 Non-significant predictors (p-value more than 0.1) Age 1.01 0.388 0.98-1.04 Female 0.70 0.257 0.38-1.29 Atrial fibrillation 0.65 0.260 0.30-1.38 Encephalopathy 1.44 0.499 0.50- 4.17 Type 2 diabetes mellitus 1.31 0.412 0.69- 2.48 Chronic kidney disease 1.17 0.708 0.50-2.74 CMV 1.04 0.965 0.20-5.28 ICANS Grade 2 0.46 0.470 0.05-3.87 ICANS Grade 3 2.55 0.276 0.47-13.75 Protein Energy Malnutrition 0.90 0.823 0.35-2.28 Congestive heart failure 0.73 0.518 0.27-1.92 Coronary artery disease 0.87 0.771 0.33-2.28 Blood transfusion 0.91 0.799 0.46-1.83 Obesity 1.03 0.951 0.42-2.54 Table 2: Multivariate logistic regression was done to determine the predictors of 30-day readmission. The following variables are included in the Cox regression model. Age, sex, type of insurance, income in quartiles, comorbid illnesses, in-hospital complications, type of disposition, and ICU admission. Significant predictors are those whose p-value is less than 0.05, borderline predictors are those whose p-value is 0.05 to 0.1, and non-significant predictors are those whose p-value is more than 0.1. Abbreviations: CAR-T: Chimeric antigen receptor T-cell therapy, RRMM: Relapsed/refractory multiple myeloma, SD: Standard deviation, ASTCT: Autologous stem cell transplantation, Cilta Cel: Ciltacabtagene autoleucel, Ide Cel: Idecabatagene vicileucel, CMV: Cytomegalovirus, CRS: Cytokine release syndrome, ICANS: Immune effector cell-associated neurotoxicity syndrome, HLH: Hemophagocytic lymphohistiocytosis, ICU: Intensive care unit, HHC: Home health care, SNF: Skilled nursing facility Declarations Human Ethics and Consent to Participate declarations Not applicable. Conflict of interest: None Grant support None Funding: None Author Contribution R.S, N.V, T.C, and C.B. wrote the main manuscript text, and L.S and R.S revised, reviewed, and edited the manuscript. All authors reviewed the manuscript. Acknowledgement We thank all the co-authors for their support in preparing the manuscript. References Munshi NC, Anderson LD, Shah N et al (2021) Idecabtagene Vicleucel in Relapsed and Refractory Multiple Myeloma. N Engl J Med 384(8):705–716. 10.1056/NEJMoa2024850 Berdeja JG, Madduri D, Usmani SZ et al (2021) Ciltacabtagene autoleucel, a B-cell maturation antigen-directed chimeric antigen receptor T-cell therapy in patients with relapsed or refractory multiple myeloma (CARTITUDE-1): a phase 1b/2 open-label study. Lancet 398(10297):314–324. 10.1016/S0140-6736(21)00933-8 Martin T, Usmani SZ, Berdeja JG et al (2023) Ciltacabtagene Autoleucel, an Anti–B-cell Maturation Antigen Chimeric Antigen Receptor T-Cell Therapy, for Relapsed/Refractory Multiple Myeloma: CARTITUDE-1 2-Year Follow-Up. J Clin Oncol 41(6):1265–1274. 10.1200/JCO.22.00842 Wesson W, Dima D, Suleman N et al (2024) Timing of Toxicities and Non-Relapse Mortality Following CAR T Therapy in Myeloma. Transpl Cell Ther 30(9):876–884. 10.1016/j.jtct.2024.06.012 Nastoupil LJ, Jain MD, Feng L et al (2020) Standard-of-Care Axicabtagene Ciloleucel for Relapsed or Refractory Large B-Cell Lymphoma: Results From the US Lymphoma CAR T Consortium. J Clin Oncol 38(27):3119–3128. 10.1200/JCO.19.02104 Gagelmann N, Bishop M, Ayuk F et al (2024) Axicabtagene Ciloleucel versus Tisagenlecleucel for Relapsed or Refractory Large B Cell Lymphoma: A Systematic Review and Meta-Analysis. Transpl Cell Ther 30(6):584. .e1-584.e13 Jain T, Knezevic A, Pennisi M et al (2020) Hematopoietic recovery in patients receiving chimeric antigen receptor T-cell therapy for hematologic malignancies. Blood Adv 4(15):3776–3787. 10.1182/bloodadvances.2020002509 Yakoub-Agha I, Chabannon C, Bader P et al (2020) Management of adults and children undergoing chimeric antigen receptor T-cell therapy: best practice recommendations of the European Society for Blood and Marrow Transplantation (EBMT) and the Joint Accreditation Committee of ISCT and EBMT (JACIE). Haematologica 105(2):297–316. 10.3324/haematol.2019.229781 Mamo T, Dreyzin A, Stroncek D, McKenna DH (2024) Emerging Biomarkers for Monitoring Chimeric Antigen Receptor T-Cell Therapy. Clin Chem 70(1):116–127. 10.1093/clinchem/hvad179 Locke FL, Mahmoudjafari Z, Kebriaei P et al (2025) Awakening from REMS: ASTCT 80/20 Ongoing Recommendations for Safe Use of Chimeric Antigen Receptor T Cells. Transpl Cell Ther 31(6):349. .e1-349.e12 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Annals of Hematology → Version 1 posted Editorial decision: Revision requested 12 Feb, 2026 Reviews received at journal 02 Feb, 2026 Reviewers agreed at journal 20 Jan, 2026 Reviewers invited by journal 20 Jan, 2026 Editor assigned by journal 19 Jan, 2026 Submission checks completed at journal 19 Jan, 2026 First submitted to journal 10 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8571194","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":577422018,"identity":"a255916a-f1c3-4640-8677-86b3d0787c08","order_by":0,"name":"Raj Shah","email":"","orcid":"","institution":"University of Kansas-Wichita","correspondingAuthor":false,"prefix":"","firstName":"Raj","middleName":"","lastName":"Shah","suffix":""},{"id":577422019,"identity":"cc2c02ab-7616-4c36-af15-807bdd5fda7e","order_by":1,"name":"Nikhil Vojjala","email":"","orcid":"","institution":"Trinity Health Oakland 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16:30:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":765229,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8571194/v1/2b536f24-b46f-4c20-a63f-cff02ea56d38.pdf"},{"id":100951852,"identity":"548bbdc2-205a-4175-94af-7dcdeeecf6da","added_by":"auto","created_at":"2026-01-23 07:11:21","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17533,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8571194/v1/3caac1c559042cc87f99bb1a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictors of 30-day Readmissions Post-CAR-T in Patients with Relapsed/Refractory Multiple Myeloma using the United States Nationwide Readmission Database","fulltext":[{"header":"Main","content":"\u003cp\u003eB-cell maturation antigen (BCMA)-directed chimeric antigen receptor T-cell (CAR-T) therapy has changed the therapeutic landscape of relapsed/refractory multiple myeloma (RRMM). As of November 2025, the FDA has approved Idecabtagene vicleucel (Ide-cel) and Ciltacabtagene autoleucel (Cilta-cel); both these products have demonstrated overall response rates between 73% and 98% in various clinical trials. \u003csup\u003e1\u0026ndash;3\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite the efficacy, these products have been associated with an adverse effect profile including cytokine release syndrome (CRS), and immune effector cell-associated neurotoxicity syndrome (ICANS), which require monitoring and early intervention\u003csup\u003e4\u003c/sup\u003e. Our study aimed to evaluate the hospital outcomes, economic burden, and readmission risks for ide-cel and cilta-cel using a real-world cohort of RRMM population treated across various hospitals in the USA.\u003c/p\u003e\n\u003cp\u003eThis is a retrospective cohort study using the National Readmission Database (NRD), which included data from January 1, 2021, to November 30, 2022. The NRD is an administrative database developed by the Agency for Healthcare Research and Quality for the Healthcare Cost and Utilization Project (HCUP). This extensive, publicly available database contains de-identified patient information and hospital-level data on approximately 35 million hospital discharges. All adult patients (\u0026ge; 18 years) with RRMM having a primary discharge diagnosis of RRMM having a procedure diagnosis of CAR-T cell administration were included in the study. Product-specific data is obtained using product-specific codes. Medical comorbidities, including hypertension, type 2 diabetes mellitus, obesity, coronary artery disease, atrial fibrillation, congestive heart failure, and chronic kidney disease, pre-existing neurological diseases were identified as additional secondary diagnoses (I10-DX2) using coding algorithms \u003cstrong\u003e(Supplementary\u003c/strong\u003e \u003cstrong\u003eTable 1\u003c/strong\u003e). In addition, several patient-level (age, sex, race, primary payer (Medicare, Medicaid, private insurance, and uninsured)) and hospital-level (bed size (small, medium, and large), teaching status, location (rural or urban), geographic region (Northeast, Midwest, West, or South)) variables were also extracted. Additionally, in-hospital complications such as cytopenias, CAR-T related complications like CRS, ICANS, and Hemophagocytic Lymphohistiocytosis (HLH) were also captured. The primary outcome during index hospitalization is in-hospital mortality. Subsequently, we extracted 30-day readmission rates and identified key predictors of 30-day readmission.\u003c/p\u003e\n\u003cp\u003eWe used the\u0026nbsp;Student\u0026rsquo;s t-test\u0026nbsp;for\u0026nbsp;Continuous variables and the\u0026nbsp;Pearson \u0026chi;2 test to obtain percentages for categorical variables.\u0026nbsp;A univariate analysis was used to identify variables associated with readmissions post CAR-T therapy to obtain independent predictors of 30-day all-cause readmission. We included those variables having a p-value \u0026lt;0.2 in the final multivariate regression analysis\u0026nbsp;to identify predictors of 30-day readmissions. All analyses were performed using STATA, version 18 (StataCorp, College Station, TX, USA).\u003c/p\u003e\n\u003cp\u003eDuring the study period,1291 RRMM patients receiving BCMA CAR-T cell therapy were identified in the United States. After excluding December admissions to allow for 30-day follow-up, 1180 patients were included in the final analysis. Out of 1180 patients, 965 (82%) received Ide-Cel and 215 (18%) received Cilta-Cel. The mean age (\u0026plusmn;SD) of the study cohort is 62.9 years (\u0026plusmn;1.1), with most participants being males (n = 732, 62%). \u0026nbsp;Most patients were treated at urban teaching hospitals with large bed sizes (n = 944, 80.0%) and resided in the same state as their treatment center (n = 956, 81%). Socioeconomic distribution showed that 37% (n=437) belonged to the highest income quartiles, with Medicare being the most common insurance coverage (n= 602,51%). The most common identifiable comorbidities included hypertension (36%), diabetes mellitus (14.11%), and chronic kidney disease (7.4%). 15% of patients have the diagnosis of protein-energy malnutrition (PEM). Pre-existing neurological diseases included dementia (2.5%), Parkinson\u0026rsquo;s disease (3.2%), and 25% reported sleep disorders. A history of alcohol use disorder was present in 0.3%, and 25% were current smokers. 52.6% (n= 620) had a prior history of autologous stem cell transplant.\u003cstrong\u003e\u0026nbsp;(Table 1).\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNotably, 38% of patients developed neutropenia and 7.1% developed hypogammaglobulinemia during index admission. However, 4.3% of the index admissions developed sepsis, and 1.6% developed septic shock. CMV infection was seen in 2% of the hospitalizations, and Clostridium difficile infection was seen in 3.3% of the hospitalizations. 11% of patients developed anemia requiring blood transfusion, and 12.8% developed thrombocytopenia. Among CAR-T related complications, 68.4% developed CRS, of which 5.3% required Tocilizumab, 1.1% developed HLH, and 7.6% developed ICANS (Grades- 1, 40%, 2- 32.5%, 3-7.3%). The incidence of ICANS in Ide-Cel was 7.1% and Cilta Cel was 9.4%. In terms of primary outcomes, the mean length of stay was 16 days for Cilta-Cel and 14.3 days for Ide-Cel. Inpatient mortality was 3.6% for Cilta-Cel and 2.3% for Ide-Cel. Among survivors, 83.1% were discharged home and 2.6% were sent to a skilled nursing facility.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf 1155 alive discharges, 226 were readmitted in 30 days with a readmission rate of 17%. In subgroup analysis, the 30-day readmission rates are 18% for Cilta-cel compared to 16% for Ide-cel (p = 0.65). Immune effector complications constituted the single most common cause of readmission (n=75, 33%), followed by infections (n=39,17.3%). Thrombotic and bleeding complications accounted for 4.7% (n=11). Mean LOS (\u0026plusmn;SD) during readmission is 6.5 days (\u0026plusmn;0.77) with 7% mortality during readmission. The mean hospitalization charge during readmission was $105,390.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThose significant on univariate analysis with a p-value\u0026gt;0.2 were included in the multivariate model. On multivariate logistic regression analysis, several predictors were identified for 30-day readmissions. HLH (HR 3.42, p\u0026lt;0.001), mechanical ventilation (HR 11.30, P\u0026lt;0.012) non-metropolitan hospital setting (HR 4.77, p\u0026lt;0.001) were associated with significantly higher readmission rates. CRS (HR 0.46, P\u0026lt;0.001) was paradoxically found to have lower readmission rates. Conversely, no significant correlation was found between other comorbidities and prior transplant status. \u003cstrong\u003e(Table 2)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur nationwide analysis provides one of the most comprehensive assessments of 30-day readmission rates and predictors of readmission following BCMA-directed CAR-T therapy in RRMM. We found a 17% readmission rate within 30 days, with immune effector cell\u0026ndash;related complications and infections constituting the most common causes of readmission. These findings highlight the significant clinical and economic burden of post-CAR-T care, despite the transformative impact of these therapies on outcomes for RRMM.\u003c/p\u003e\n\u003cp\u003eCompared to other real-world studies, our observed readmission rate in RRMM is consistent with reported post-CAR-T outcomes in diffuse large B-cell lymphoma, where 30-day readmissions range between 15% and 20%.\u003csup\u003e5,6\u003c/sup\u003e The comparable magnitude suggests that, despite differences in disease biology and targets, CAR-T uniformly carries a high risk of early readmission. Specifically, immune effector complications accounted for one-third of all readmissions in our cohort, highlighting that the toxicities of CAR-T persist beyond index admission. Infections were the second most common cause of readmission, likely due to profound and prolonged cytopenias observed in this patient population.\u003csup\u003e7,8\u003c/sup\u003e Together, these results support vigilant outpatient surveillance with structured monitoring protocols, timely immunoglobulin replacement, and aggressive infection prophylaxis strategies.\u003csup\u003e8\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur regression analysis identifies several notable predictors of readmission. Mechanical ventilation during index admission confers an exceptionally high risk of readmission, reflecting the severity of acute toxicities of CAR-T therapy during index admission that negatively impact long-term non-disease-related outcomes. Similarly, patients with HLH had a four-fold higher readmission risk, which may mirror both the aggressive disease course and the need for prolonged immunosuppression. Patients discharged to skilled nursing facilities also had a significantly increased risk, possibly due to higher baseline frailty and limited capacity for specialized toxicity management in post-acute settings. Interestingly, treatment at non-metropolitan hospitals was associated with higher readmission rates, which may reflect disparities in supportive infrastructure, access to subspecialty care, or availability of standardized CAR-T monitoring programs. Patients with CRS had lower readmission rates, which could be due to more intense post-hospital monitoring. These findings emphasize the importance of multidisciplinary post-CAR-T care pathways, particularly in non-tertiary centers. Notably, patient comorbidities such as diabetes, chronic kidney disease, and cardiovascular disease did not emerge as significant predictors. This suggests that disease- and treatment-related factors outweigh baseline comorbidity in driving early readmissions. Moreover, no significant difference in readmission risk was observed between ide-cel and cilta-cel, reinforcing that toxicity management strategies need to be broadly applicable across CAR-T products. \u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003ePreviously, the FDA-mandated Risk Evaluation and Mitigation Strategy (REMS) program required institutions administering CAR-T to be specially certified, maintain staff trained in recognizing and managing toxicities, and ensure 24/7 availability of tocilizumab and intensive care support. These structured frameworks are designed to reduce morbidity and mortality from immune effector cell\u0026ndash;associated toxicities. The removal of REMS requirements will need to be met with increased education on close outpatient monitoring and seamless communication between certified centers and community providers.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge several limitations of our study. The use of an administrative database introduces potential coding errors and precludes the collection of granular data on CAR-T manufacturing, prior lines of therapy, and toxicity grading. Additionally, we lacked information on outpatient interventions such as prophylactic antimicrobials or immunoglobulin replacement, which may influence readmission risk. The NRD excludes discharges with missing or unverified patient linkage numbers, which may result in underestimation of readmission rates. Patients who are transferred to a different hospital or readmitted in a different state than their index hospitalization were not included in the dataset. Despite these limitations, the large sample size and real-world national scope provide robust insights into post-CAR-T readmissions. In conclusion, nearly one in six RRMM patients undergoing BCMA CAR-T therapy experience a 30-day readmission, predominantly due to immune effector toxicities and infections. Identifying patients at the highest risk and implementing proactive post-discharge strategies, including reinforcement of REMS principles in outpatient practice, will be essential to improve patient outcomes, reduce healthcare utilization, and maximize the transformative potential of BCMA CAR-T therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Baseline characteristics, in-hospital outcomes, and readmission rates:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAR-T in RRMM (n=1180) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean age (\u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.8 (\u0026plusmn; 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary expected payer\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eMedicare\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eMedicaid\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003ePrivate\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e618 (52.4)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e42 (3.6)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e512(43.4)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e8 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome Quartiles\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e1\u003csup\u003est\u003c/sup\u003e quarter\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e2\u003csup\u003end\u003c/sup\u003e quarter\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e3\u003csup\u003erd\u003c/sup\u003e quarter\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e4\u003csup\u003eth\u003c/sup\u003e quarter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e198 (16.8)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e245 (20.8)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e297(25.2)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e440 (37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital bed size\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eSmall\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eMedium\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e174 (14.8)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e66 (5.6)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e940 (79.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eState of residency\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eSame state as the CAR-T center\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eOther state\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e956 (81)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e224 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eHypertension\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eType 2 Diabetes Mellitus\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eObesity\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eCoronary artery disease\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eCongestive heart failure\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eAtrial fibrillation\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eChronic kidney disease\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eProtein-calorie malnutrition\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eSmoking status\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eAlcohol\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eDementia\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eParkinsons\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eSleep disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e425(36)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e165 (14)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e106 (9)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e94 (8)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e80 (6.8)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e130 (11)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e87 (7.4)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e184 (15.6)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e295(25)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026lt;10\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e30(2.5)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e38(3.2\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e295(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of ASTCT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e620(52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of CAR-T\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eCilta Cel\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eIde Cel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e215 (18)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e965 (82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn hospital complications\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eAcute Kidney Injury\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eSeptic shock\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eCMV infection\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eClostridium difficile infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e215 (18.3)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e18 (1.5)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e24 (2.0)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e49 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAR-T related complications\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eNeutropenia\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eThrombocytopenia\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eHypogammaglobinemia\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eCRS (any grade)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eICANS\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eHLH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e448 (38)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e153 (13)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e84 (7.1)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e802 (68)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e89 (7.5)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e11 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProcedures\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eBlood transfusion\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eMechanical Ventilation\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eTocilizumab use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e130 (11)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e12(1.0)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e62 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU stay\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e300 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisposition of the patient\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eHome\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eHome with HHC\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eSNF\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e979 (83.1)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e139 (11.8)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e30 (2.5)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e32(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eMortality\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eLength of stay (\u0026plusmn;SD)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e-Cilta cel\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e-Ide Cel\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eTotal Hospitalization charges\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e-Cilta Cel\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e-Ide Cel\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e30-day readmission rates (Overall)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e-Cilta Cel\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e-Ide Cel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25 (2.1)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e16days (\u0026plusmn;0.9)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e14 days (\u0026plusmn;0.9)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e1363757\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e1161199\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e200(17%)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e40(18%)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e160(16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCauses of 30-day re-admission\u003c/strong\u003e\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eImmune effector complications\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eInfections\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eDisease progression\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eThrombosis \u0026amp; bleeding\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75 (33.0)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e39 (17.3)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e33 (14.7)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e11 (4.7)\u003c/p\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cp\u003e67 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: CAR-T: Chimeric antigen receptor T-cell therapy, RRMM: Relapsed/refractory multiple myeloma, SD: Standard deviation, ASTCT: Autologous stem cell transplantation, Cilta Cel: Ciltacabtagene autoleucel, Ide Cel: Idecabatagene vicileucel, CMV: Cytomegalovirus, CRS: Cytokine release syndrome, ICANS: Immune effector cell-associated neurotoxicity syndrome, HLH: Hemophagocytic lymphohistiocytosis, ICU: Intensive care unit, HHC: Home health care, SNF: Skilled nursing facility\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Predictors of 30-day readmission in patients post BCMA CAR-T cell therapy\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"740\" class=\"fr-table-selection-hover\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence Interval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHospital urban/rural category (Non metro)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.14-10.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMechanical ventilation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e11.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.70-75.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHLH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.14-10.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.29-\u0026nbsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBorderline significant predictors (p value 0.05 to 0.1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eParkinsons disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.96-19.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAdministration of Tocilizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.03-1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.28-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLength of Stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.99-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-significant predictors (p-value more than 0.1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.98-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.38-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAtrial fibrillation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.30-1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEncephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.50-\u0026nbsp;4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eType 2 diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.69-\u0026nbsp;2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChronic kidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.50-2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCMV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.20-5.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eICANS Grade 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.05-3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eICANS Grade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.47-13.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eProtein Energy Malnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.35-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCongestive heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.27-1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary artery disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.33-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBlood transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.46-1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.42-2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eTable 2: Multivariate logistic regression was done to determine the predictors of 30-day readmission. The following variables are included in the Cox regression model. Age, sex, type of insurance, income in quartiles, comorbid illnesses, in-hospital complications, type of disposition, and ICU admission. Significant predictors are those whose p-value is less than 0.05, borderline predictors are those whose p-value is 0.05 to 0.1, and non-significant predictors are those whose p-value is more than 0.1. Abbreviations: CAR-T: Chimeric antigen receptor T-cell therapy, RRMM: Relapsed/refractory multiple myeloma, SD: Standard deviation, ASTCT: Autologous stem cell transplantation, Cilta Cel: Ciltacabtagene autoleucel, Ide Cel: Idecabatagene vicileucel, CMV: Cytomegalovirus, CRS: Cytokine release syndrome, ICANS: Immune effector cell-associated neurotoxicity syndrome, HLH: Hemophagocytic lymphohistiocytosis, ICU: Intensive care unit, HHC: Home health care, SNF: Skilled nursing facility\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003ch2\u003eGrant support\u003c/h2\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eR.S, N.V, T.C, and C.B. wrote the main manuscript text, and L.S and R.S revised, reviewed, and edited the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe thank all the co-authors for their support in preparing the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMunshi NC, Anderson LD, Shah N et al (2021) Idecabtagene Vicleucel in Relapsed and Refractory Multiple Myeloma. N Engl J Med 384(8):705\u0026ndash;716. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMoa2024850\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa2024850\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerdeja JG, Madduri D, Usmani SZ et al (2021) Ciltacabtagene autoleucel, a B-cell maturation antigen-directed chimeric antigen receptor T-cell therapy in patients with relapsed or refractory multiple myeloma (CARTITUDE-1): a phase 1b/2 open-label study. 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Transpl Cell Ther 31(6):349. .e1-349.e12\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8571194/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8571194/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eB-cell maturation antigen (BCMA)-directed chimeric antigen receptor T-cell (CAR-T) therapy has changed the therapeutic landscape of relapsed/refractory multiple myeloma (RRMM). Despite the efficacy, these products have been associated with an adverse effect profile including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), which require monitoring and early intervention. This is a retrospective cohort study using the National Readmission Database (NRD) aimed at evaluating hospital outcomes, economic burden, and readmission risks for ide-cel and cilta-cel in a real-world cohort of RRMM patients treated across various hospitals in the USA. During the study period,1291 RRMM patients receiving BCMA CAR-T cell therapy were identified in the United States. After excluding December admissions to allow for 30-day follow-up, 1180 patients were included in the final analysis. We found a 17% readmission rate within 30 days, with immune effector cell\u0026ndash;related complications and infections constituting the most common causes of readmission. These findings highlight the significant clinical and economic burden of post-CAR-T care, despite the transformative impact of these therapies on outcomes for RRMM.\u003c/p\u003e","manuscriptTitle":"Predictors of 30-day Readmissions Post-CAR-T in Patients with Relapsed/Refractory Multiple Myeloma using the United States Nationwide Readmission Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-22 19:43:18","doi":"10.21203/rs.3.rs-8571194/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-12T18:47:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-02T09:39:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93934194294820756928686034335026501329","date":"2026-01-20T10:54:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-20T06:57:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-19T10:32:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-19T10:31:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Annals of Hematology","date":"2026-01-11T03:10:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b46e5d2d-aec0-4eae-b52b-db4c9116a232","owner":[],"postedDate":"January 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:24:54+00:00","versionOfRecord":{"articleIdentity":"rs-8571194","link":"https://doi.org/10.1007/s00277-026-06927-z","journal":{"identity":"annals-of-hematology","isVorOnly":false,"title":"Annals of Hematology"},"publishedOn":"2026-03-23 16:08:46","publishedOnDateReadable":"March 23rd, 2026"},"versionCreatedAt":"2026-01-22 19:43:18","video":"","vorDoi":"10.1007/s00277-026-06927-z","vorDoiUrl":"https://doi.org/10.1007/s00277-026-06927-z","workflowStages":[]},"version":"v1","identity":"rs-8571194","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8571194","identity":"rs-8571194","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}