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  • Author: Netana H. Markovitz x
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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.