Abstract
Background: Waldenström's macroglobulinemia (WM) is a rare B-cell malignancy with limited data on inpatient outcomes and the role of social determinants of health (SDOH). Understanding how race, insurance, income, and hospital factors affect hospitalization-related outcomes may help us to improve care and efficiency.
Methods: In this study, we analyzed adult WM hospitalizations from the 2020–2022 Nationwide Inpatient Sample (N=4,291). Primary outcomes included in-hospital mortality, length of stay (LOS), and total hospital cost (inflation-adjusted to 2022 USD). Multivariable logistic regression assessed mortality; negative binomial and gamma regressions were used for LOS and cost, respectively. Covariates included age, sex, race/ethnicity, primary payer, ZIP-code income quartile, comorbidity burden (Elixhauser index), hospital region, location (urban/rural), and teaching status.
Results: The cohort had a median age of 67 years; 43% were female. Median LOS was 3 days, and median total cost was $41,290. In-hospital mortality was 3.0%. Mortality increased with age (OR 1.03 per 5 years; p<0.001) and comorbidity burden (OR 1.05 per point; p<0.001). Mortality was lower among females (OR 0.72; p=0.01). Race, income, insurance, and hospital characteristics were not independently associated with mortality.
LOS showed increase with age (IRR 1.02 per 5 years), Elixhauser comorbidity index (IRR 1.03 per point), Medicaid (IRR 1.18), and self-pay status (IRR 1.31). Admissions to urban teaching hospitals had 22% longer LOS versus rural non-teaching facilities (p<0.001).
Total costs were significantly higher for self-pay patients (cost ratio 1.75 vs Medicare; p=0.005) and for admissions to urban teaching hospitals (cost ratio 2.00; p<0.001). Costs were lower in the South versus the Northeast (cost ratio 0.84; p<0.001). Age and comorbidity modestly increased costs.
Conclusions: Among hospitalized WM patients, age and comorbidities were key predictors of mortality, while insurance type and hospital setting strongly influenced LOS and cost. Race and income were not independently associated with adverse outcomes. These findings suggest that health system–level factors, particularly insurance barriers and hospital resource use, may drive cost and efficiency more than individual socioeconomic status. Interventions targeting high-cost payer groups and high-resource settings may help improve value without compromising survival.
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