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3790 Disparities in Multiple Myeloma (MM): Race/Ethnicity-Specific Sociodemographic and Economic Factors That May Drive Patient Decisions to Refuse Treatment

Program: Oral and Poster Abstracts
Session: 907. Outcomes Research: Plasma Cell Disorders: Poster II
Hematology Disease Topics & Pathways:
Research, Clinical Research, Plasma Cell Disorders, Health disparities research, Diseases, Real-world evidence, Lymphoid Malignancies
Sunday, December 8, 2024, 6:00 PM-8:00 PM

Firas Baidoun, MD1*, Vivek Roy, MD1, Ricardo D. Parrondo, MD1, Andre Fernandez, P.A. -C1*, Caitlin Flott1*, Taimur Sher, MD2*, Rami Manochakian, MD1*, Asher A. Chanan-Khan, MD1 and Sikander Ailawadhi1

1Division of Hematology-Oncology, Mayo Clinic-Florida, Jacksonville, FL
2Division of Hematology, Mayo Clinic, Jacksonville, FL

Introduction: Myeloma therapeutics have tremendously improved in recent times, leading to unprecedented outcomes. Timely initiation of effective treatment is vital to improving survival and quality of life. Patient refusal to receive treatment is infrequent but certainly leads to increased morbidity/mortality. We studied factors associated with treatment refusal.

Methods: The National Cancer Database (NCDB) was queried for adult patients diagnosed with MM between 2004-2021. Those who refused treatment for initial management despite physician’s recommendation were identified. Patients with multiple primary malignancies or unknown treatment status were excluded. Patients’ demographics and socioeconomic factors were collected. Kaplan-Meier and multivariate Cox regression were used to evaluate the likelihood of treatment refusal in the whole cohort and in each racial/ethnic group.

Results: Out of 86,350 eligible patients with MM who were recommended to initiate therapy, 2,508 (2.9%) did not receive any treatment due to refusal. Of these, 52.6% were females, 64% were non-Hispanic White (NHW), 21.3% were non-Hispanic African American (NHAA), and 5.2% were Hispanic. On multivariate analysis, patients who were treated at comprehensive and integrated facilities were more likely to refuse treatment as compared to those at academic facilities (OR=1.36; 95% CI: 1.22-1.52, p<0.001 and OR=1.22; 95% CI: 1.07-1.4, p=0.004, respectively). Patients on Medicare (OR=1.42; 95% CI: 1.16-1.73, p<0.001), and presence of higher Charlson Comorbidity Index (CCI) also had a higher likelihood of refusing treatment. Lower refusal rates were seen for male gender (OR=0.83; 95% CI: 0.76-0.91, p<0.001), NHW racial/ethnic group (as against NHAA; OR=0.34; 95% CI: 0.16-0.71, p=0.004), being insured (OR=0.69; 95% CI: 0.52-0.93, p=0.015), having private insurance (compared to Medicaid; OR=0.47; 95% CI: 0.38-0.59, p<0.001) and having a higher income level (OR=0.82; 95% CI: 0.70-0.96, p=0.013). Among NHAA patients, 2.8% refused treatment and were more likely to have Medicare (OR=1.4; 95% CI: 1.03-1.9, p=0.032). Having private insurance (compared to Medicaid; OR=0.61; 95% CI: 0.43-0.88, p=0.008) had a lower likelihood of refusing treatment. Among NHW, 2.9% refused treatment and they were more likely to be treated at community, comprehensive and integrated facilities compared to academic facilities (OR=1.39; 95% CI: 1.12-1.73, p=0.003, OR=1.54; 95% CI: 1.33-1.77, p<0.001 and OR=1.38; 95% CI: 1.16-1.64, p<0.001, respectively), be from rural areas (OR=1.43; 95% CI: 1.05-1.96, p=0.025), and have a higher CCI. On the other hand, male gender (OR=0.79; 95% CI: 0.72-0.89, p<0.001), private insurance (compared to Medicaid; OR=0.42; 95% CI: 0.30-0.59, p<0.001) and higher income level (OR=0.80; 95% CI: 0.66-0.98, p=0.029) had a lower likelihood of refusing treatment. Among Hispanic patients, 2.3% refused treatment and were more likely to have Medicare (OR=1.96; 95% CI: 1.13-3.4, p=0.016), while those with private insurance (compared to Medicaid; OR=0.32; 95% CI: 0.14-0.73, p=0.007) had a lower likelihood of refusing treatment.

Conclusions: This large real-world analysis highlights the intricate sociodemographic and economic factors that affect the decision of a MM to not proceed with the recommendation for treatment. (1) NHW are less likely to refuse treatment as compared to NHAA. (2) Insurance status is an important driver of refusal and transcends race/ethnicity. Furthermore, in this study, we highlight characteristics that are specific to different racial/ethnic groups like CCI which affect only certain racial/ethnic groups. This provides an opportunity to develop targeted interventions such that the benefit of therapeutic advancements can be realized by all.

Disclosures: Parrondo: Sanofi Aventis: Honoraria; AstraZeneca: Honoraria; Bristol Myers Squibb, GSK: Research Funding. Sher: Caelum pharma: Other; Alpha: Consultancy, Membership on an entity's Board of Directors or advisory committees; 2 Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Prothena: Other. Manochakian: BMS: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Onochost: Membership on an entity's Board of Directors or advisory committees. Chanan-Khan: Starton Therapeutics: Membership on an entity's Board of Directors or advisory committees. Ailawadhi: Amgen: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Johnson and Johnson: Consultancy, Research Funding; Cellectar: Consultancy, Honoraria, Research Funding; Ascentage: Research Funding; Abbvie: Research Funding; Xencor: Research Funding; Regeneron: Consultancy; Beigene: Consultancy; Takeda: Consultancy; BMS: Consultancy, Research Funding; GSK: Consultancy, Research Funding; Sanofi: Consultancy; Pharmacuclics: Consultancy, Research Funding.

*signifies non-member of ASH