Background: CAR T-cell therapy has revolutionized the treatment of patients with hematologic malignancies, but it can result in prolonged hospitalizations and serious toxicities. However, data on the impact of CAR T-cell therapy on healthcare utilization and end-of-life (EoL) outcomes are lacking. Methods: We conducted a retrospective analysis of 236 patients who received CAR T-cell therapy at 2 tertiary care centers from February 2016 through December 2019. We abstracted healthcare utilization and EoL outcomes from the electronic health record, including hospitalizations, receipt of ICU care, hospitalization and receipt of systemic therapy in the last 30 days of life, palliative care, and hospice referrals. Results: Most patients (81.4%; n=192) received axicabtagene ciloleucel. Overall, 28.1% of patients experienced a hospital readmission and 15.5% required admission to the ICU within 3 months of CAR T-cell therapy. Among the deceased cohort, 58.3% (49/84) were hospitalized and 32.5% (26/80) received systemic therapy in the last 30 days of life. Rates of palliative care and hospice referrals were 47.6% and 30.9%, respectively. In multivariable logistic regression, receipt of bridging therapy (odds ratio [OR], 3.15; P=.041), index CAR-T hospitalization length of stay >14 days (OR, 4.76; P=.009), hospital admission within 3 months of CAR T-cell infusion (OR, 4.29; P=.013), and indolent lymphoma transformed to diffuse large B-cell lymphoma (OR, 9.83; P=.012) were associated with likelihood of hospitalization in the last 30 days of life. Conclusions: A substantial minority of patients receiving CAR T-cell therapy experienced hospital readmission or ICU utilization in the first 3 months after CAR T-cell therapy, and most deceased recipients of CAR T-cell therapy received intensive EoL care. These findings underscore the need for interventions to optimize healthcare delivery and EoL care for this population.
P. Connor Johnson, Caron Jacobson, Alisha Yi, Anna Saucier, Tejaswini M. Dhawale, Ashley Nelson, Mitchell W. Lavoie, Mathew J. Reynolds, Carlisle E.W. Topping, Matthew J. Frigault, and Areej El-Jawahri
P. Connor Johnson, Netana H. Markovitz, Tamryn F. Gray, Sunil Bhatt, Ryan D. Nipp, Nneka Ufere, Julia Rice, Matthew J. Reynolds, Mitchell W. Lavoie, Carlisle E.W. Topping, Madison A. Clay, Charlotta Lindvall, and Areej El-Jawahri
Background: Social support plays a crucial role for patients with aggressive hematologic malignancies as they navigate their illness course. The aim of this study was to examine associations of social support with overall survival (OS) and healthcare utilization in this population. Methods: A cross-sectional secondary analysis was conducted using data from a prospective longitudinal cohort study of 251 hospitalized patients with aggressive hematologic malignancies at Massachusetts General Hospital from 2014 through 2017. Natural Language Processing (NLP) was used to identify the extent of patients’ social support (limited vs adequate as defined by NLP-aided chart review of the electronic health record). Multivariable regression models were used to examine associations of social support with (1) OS, (2) death or readmission within 90 days of discharge from index hospitalization, (3) time to readmission within 90 days, and (4) index hospitalization length of stay. Results: Patients had a median age of 64 years (range, 19–93 years), and most were White (89.6%), male (68.9%), and married (65.3%). A plurality of patients had leukemia (42.2%) followed by lymphoma (37.9%) and myelodysplastic syndrome/myeloproliferative neoplasm (19.9%). Using NLP, we identified that 8.8% (n=22) of patients had limited social support. In multivariable analyses, limited social support was associated with worse OS (hazard ratio, 2.00; P=.042) and a higher likelihood of death or readmission within 90 days of discharge (odds ratio, 3.11; P=.043), but not with time to readmission within 90 days or with index hospitalization length of stay. Conclusions: In this cohort of hospitalized patients with aggressive hematologic malignancies, we found associations of limited social support with lower OS and a higher likelihood of death or readmission within 90 days of hospital discharge. These findings underscore the utility of NLP for evaluating the extent of social support and the need for larger studies evaluating social support in patients with aggressive hematologic malignancies.