Introduction: The discovery of new therapeutic options in plasma cell dyscrasias (PCDs) has advanced significantly over the last decade. However, beyond the recent advancements in treatment, the influence of socioeconomic and hospital-level factors on inpatient outcomes remains underexplored. This study aims to characterize and describe the association between socioeconomic factors, hospital characteristics, and inpatient mortality of patients (pts) with PCDs.

Methods: We conducted a retrospective analysis using the National Inpatient Sample (NIS) database from 2016 to 2022 to identify adult pts with PCDs, including multiple myeloma (MM) (63.5%), MGUS (27%), AL amyloidosis (5%), Waldenström's macroglobulinemia (4%), and plasma cell leukemia (PCL) (0.5%), using ICD-10 codes. Pts with missing data on key variables were excluded. Smoldering myeloma was not included in this analysis due to the absence of a specific ICD-10 code. The primary outcome was in-hospital mortality.A multivariable survey-weighted logistic regression model was used to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CI). Variables included demographics, Charlson Comorbidity Index (CCI), primary payer, and hospital-level factors. Socioeconomic status was assessed using ZIP-code–linked income quartiles, with Q1 as the reference, and modeled with predictive margins to estimate adjusted probabilities of death.

Results: A total of 195,384 pts who met the inclusion criteria were analyzed. The overall mean age was 68 yrs, and 44.2% were female. The cohort was predominantly White (70.1%), followed by Black (17.3%) and Hispanic (7.9%). The overall mean Charlson CCI was 6.7. Medicare was the most common primary payer (60.5%), followed by private insurance (27.5%). Most pts were treated at large urban teaching hospitals, primarily in the South.

When comparing the lowest (Q1) and highest (Q4) quartiles, pts in Q1 had a higher CCI (mean 6.9 vs. 6.4) and a smaller proportion of White pts (65.1% vs. 75.3%). The proportion of Black (20.3% vs. 13.4%) and Hispanic (9.8% vs. 5.4%) pts was larger compared to Q4. Furthermore, pts in Q1 were more likely to be covered by Medicare (65.2%) or Medicaid (9.7%). In contrast, a higher proportion of Q4 pts had private insurance (34.7% vs. 21.2%). Additionally, pts in Q1 were less commonly treated at urban teaching hospitals (61.9% vs. 69.5%) and large hospitals (65.5% vs. 70.6%) compared to Q4.

After adjusting for patient and hospital characteristics, the multivariable model showed that primary payer status and income level were significantly associated with inpatient mortality. Compared to Medicare, the odds of death were higher for Self-pay (aOR 1.60, 95% CI 1.31–1.96; p<0.001) and Medicaid pts (aOR 1.28, 95% CI 1.15–1.43; p<0.001), while pts with private insurance had lower odds (aOR 0.77, 95% CI 0.69–0.85; p<0.001). This pattern was also evident across income levels, where pts in Q4 (aOR 0.91, 95% CI 0.85–0.97; p=0.004) had reduced odds of mortality vs Q1. Notably, PCL (aOR 2.88, 95% CI 2.32–3.57; p<0.001) and relapsed MM (aOR 1.62, 95% CI 1.48–1.76; p<0.001) were strongly associated with higher mortality. The CCI demonstrated the strongest association with each one-point increase corresponding to a 14% mortality risk increase (aOR 1.14; 95% CI 1.13–1.15). The odds of death were significantly higher for several racial groups vs White pts, including Asian/Pacific Islanders (aOR 1.17, 95% CI 1.02–1.33; p=0.021), Native Americans (aOR 1.39, 95% CI 1.03–1.87; p=0.032), and pts of Other race (aOR 1.21, 95% CI 1.06–1.37; p=0.003). Treatment in the Midwest (aOR 0.90, 95% CI 0.84–0.96; p=0.001) and South (aOR 0.91, 95% CI 0.85–0.96; p=0.001) was associated with lower odds of death compared to the Northeast. Treatment at medium (aOR 1.08, 95% CI 1.01–1.15; p=0.025) or large hospitals (aOR 1.10, 95% CI 1.04–1.17; p=0.001) was associated with higher mortality compared to small hospitals.

Conclusion: This study demonstrates that although significant treatment advancements have been made in the last decade, inpatient mortality for pts with PCDs is significantly influenced by social determinants of health, including income, insurance status, race, and hospital-level characteristics. These findings highlight the need for healthcare policies and targeted interventions to mitigate the impact of financial toxicity and structural inequities in order to improve outcomes for vulnerable populations.

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2025
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