Real-world outcomes of newly diagnosed multiple myeloma patients in the veterans affairs healthcare system

A Alexander Lazzaro (1Boston Medical Center, Medicine, Boston, United States) K Kaelyn Nannini (2Massachusetts Veterans Epidemiology Research and Information Center, Boston, United States) C Cenk Yildirim (2Massachusetts Veterans Epidemiology Research and Information Center, Boston, United States) L Linden Huhmann (2Massachusetts Veterans Epidemiology Research and Information Center, Boston, United States) J John Culnan (2VA Boston Healthcare System, Boston, United States) J June Corrigan (2VA Boston Healthcare System, Boston, United States) D Danne Elbers (VA CSP Boston Informatics, Castleton, Vermont, United States) N Nhan Do (Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts, United States) M Mary Brophy (Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts, United States) N Nikhil Munshi (3VA Boston Healthcare System, Boston, MA) N Nathanael Fillmore (Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts, United States) C Camille Edwards (1Boston University Chobanian & Avedisian School of Medicine, Boston, United States)

Abstract

Abstract Introduction: Multiple myeloma (MM) is a largely incurable hematologic malignancy with a complex and evolving therapeutic landscape. The number of FDA-approved treatments for MM at various stages of disease has increased substantially over the past two decades, encompassing immunomodulatory agents, proteasomal inhibitors and immunotherapies including monoclonal antibodies, antibody-drug conjugates, chimeric antigen receptor (CAR) T-cells, bispecific T cell engagers (BiTEs), and adoptive T cell therapies (ACT). Randomized clinical trials have historically shaped treatment strategies; however, patients experiencing socioeconomic barriers are often enrolled at lower rates. Our prior work demonstrated that patients experiencing socioeconomic barriers are significantly less likely to receive optimal frontline MM therapy even in equal access settings. Given the increasing complexity of MM treatment decisions, we sought to understand the relationship between social determinants of health and outcomes to inform targeted interventions. Methods We retrospectively evaluated 20,385 patients from the national Veterans Health Administration (VHA) with newly diagnosed MM between 2000 and 2024. The single-payer structure of the VHA eliminates cost-related barriers to healthcare, allowing us to assess trends in treatment decisions and outcomes across diverse socioeconomic strata. Baseline data at time of MM diagnosis was collected and included demographics, smoking status, weighted Charlson co-morbidity index (CCI), distance from VA hospital, geographic region, serum lactate dehydrogenase (LDH), serum β2-microglobulin (β2m), serum creatinine (sCr), serum albumin, MM diagnosis date by era, MM treatment regimen, staging system (international staging system, ISS) and area deprivation index (ADI) as a measure of socioeconomic status that incorporates income, education, employment, and housing quality. Survival analysis was performed using a cox proportional hazards model. Overall survival was the primary outcome. We analyzed overall survival (OS) by treatment regimen, diagnosis era, and sociodemographic features. Results The median age at diagnosis was 71.2 [interquartile range (IQR), 64.2 – 77.5]. Patients with newly diagnosed MM over the age of 65 had a 69% higher risk of death compared to patients with newly diagnosed MM under the age of 65 (HR 1.69, C.I. 1.59 – 1.80, p < 0.01). Female patients had a 18% lower risk of death compared to male patients (HR 0.82, C.I. 0.68 – 0.98, p = 0.03). Patients in the Midwest geographic region had a 7% lower risk of death compared to patients in the Continental geographic region (HR 0.31, C.I. 0.86 – 1.00, p = 0.04). There was a notable shift in treatment regimens over time, with the use of proteasome inhibitor (PI) or immunomodulatory drug (IMiD) monotherapy declining and triplet/quadruplet therapy increasing after 2017. Patients treated with PI monotherapy had an 82% higher risk of death (HR 1.82, C.I. 1.63 – 2.02, p < 0.01), while patients on IMiD monotherapy had a 27% higher risk of death (HR 1.27, C.I. 1.16 – 1.38, p < 0.01) compared to those receiving triplet therapy. Median OS improved across treatment eras. Higher ADI was independently associated with increased mortality despite equal healthcare access as patients in the highest quintile experienced a 21% greater risk of death than those in the lowest quintile (HR 1.21, C.I. 1.11 – 1.31, p < 0.01). Conclusion Novel therapies have been adopted for frontline treatment of MM and have led to improved overall survival. However, socioeconomic barriers to care persistently lead to poorer clinical outcomes despite equal access to care within the VHA system. These findings underscore the need for targeted interventions beyond healthcare access alone.

Article Details

Journal Blood
Volume / Issue Vol. 146, Issue Supplement 1
Published November 03, 2025
Pages 3979-3979
ISSN 0006-4971
Publisher Elsevier BV

Journal Info

Blood

Elsevier BV

ISSN: 0006-4971 Health Sciences

Authors (12)

A

Alexander Lazzaro

1Boston Medical Center, Medicine, Boston, United States

K

Kaelyn Nannini

2Massachusetts Veterans Epidemiology Research and Information Center, Boston, United States

C

Cenk Yildirim

2Massachusetts Veterans Epidemiology Research and Information Center, Boston, United States

L

Linden Huhmann

2Massachusetts Veterans Epidemiology Research and Information Center, Boston, United States

J

John Culnan

2VA Boston Healthcare System, Boston, United States

J

June Corrigan

2VA Boston Healthcare System, Boston, United States

D

Danne Elbers

VA CSP Boston Informatics, Castleton, Vermont, United States

N

Nhan Do

Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts, United States

M

Mary Brophy

Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts, United States

N

Nikhil Munshi

3VA Boston Healthcare System, Boston, MA

N

Nathanael Fillmore

Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts, United States

C

Camille Edwards

1Boston University Chobanian & Avedisian School of Medicine, Boston, United States