Disparity in Access to Myeloma CAR-T: A Geospatial Analysis of Distance to CAR-T Centers and Its Impact on Mortality

Introduction Novel therapy with chimeric antigen receptor T-cell therapy (CAR-T) has revolutionized treatment options for patients with multiple myeloma (MM). However, disparities in access persist. One such disparity is related to access to CAR-T services, limited to specialized academic centers nationwide. We aimed to examine the disparity in access based purely on geographic distance to the nearest CAR-T center in the lower United States. Methods MM age-adjusted mortality per 100,000 persons organized by county was obtained from the NCI Cancer Atlas for both sexes and all races. A list of CAR-T centers was obtained from ide-cel and cilta-cel websites. These data were uploaded as Geographic Information System (GIS) layers using QGIS software. Distance from each county with available mortality data to nearest CAR-T center was then calculated. A comparison of mortality and distance from CAR-T center was performed for both ide-cel and cilta-cel using simple linear regression and Pearson bivariate correlations. Statistics were calculated using SPSS software. Results Based on NCI data, 747 US Counties had available mortality data for patients with multiple myeloma; 156 had available data by race. A total of 76 ide-cel and 55 cilta-cel sites were identified. For ide-cel, distance was correlated to age-adjusted mortality per 100,000 persons (r=.093, p=.011) and regression suggested that distance to nearest ide-cel site accounted for 0.9% of age-adjusted mortality (F=6.42, p=.011). For cilta-cel, distance was correlated to age-adjusted mortality per 100,000 persons (r=.122, p<.001) and regression suggested that distance to nearest cilta-cel site accounted for 1.5% of age-adjusted mortality (F=11.24, p<.001). When assessing disparity by race, non-Hispanic Blacks had a more age-adjusted mortality due to distance from CAR-T Center. For ide-cel, distance accounted for 2.5% of non-Hispanic Black age-adjusted mortality (F=3.929, p=.049). For cilta-cel, distance accounted for 6.4% of non-Hispanic Black age-adjusted mortality (F=10.404, p=.002). Conclusions Using geospatial analysis, we identified that a county's distance to CAR-T center had a statistically significant impact on age-adjusted multiple myeloma mortality. This impact was more pronounced for Non-Hispanic Black patients, of particular interest as MM is more likely to affect the Black patient. As more patients become eligible for CAR-T therapy, the benefit of living near a CAR-T center will likely grow. Distance to CAR-T centers may form a new interface with a patient's social determinants of health, creating a new health care disparity in MM.

Authors

Institutions

Publication Details

Journal
Blood
Published
2024-11-05
DOI
https://doi.org/10.1182/blood-2024-212286
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Disparity in Access to Myeloma CAR-T: A Geospatial Analysis of Distance to CAR-T Centers and Its Impact on Mortality

James J. Ignatz-Hoover, Michael Daunov, Benjamin Gorham
Blood
Health Systems, Economic Evaluations, Quality of Life
article

Disparity in Access to Myeloma CAR-T: A Geospatial Analysis of Distance to CAR-T Centers and Its Impact on Mortality

James J. Ignatz-Hoover, Michael Daunov, Benjamin Gorham
article en

Abstract

Introduction Novel therapy with chimeric antigen receptor T-cell therapy (CAR-T) has revolutionized treatment options for patients with multiple myeloma (MM). However, disparities in access persist. One such disparity is related to access to CAR-T services, limited to specialized academic centers nationwide. We aimed to examine the disparity in access based purely on geographic distance to the nearest CAR-T center in the lower United States. Methods MM age-adjusted mortality per 100,000 persons organized by county was obtained from the NCI Cancer Atlas for both sexes and all races. A list of CAR-T centers was obtained from ide-cel and cilta-cel websites. These data were uploaded as Geographic Information System (GIS) layers using QGIS software. Distance from each county with available mortality data to nearest CAR-T center was then calculated. A comparison of mortality and distance from CAR-T center was performed for both ide-cel and cilta-cel using simple linear regression and Pearson bivariate correlations. Statistics were calculated using SPSS software. Results Based on NCI data, 747 US Counties had available mortality data for patients with multiple myeloma; 156 had available data by race. A total of 76 ide-cel and 55 cilta-cel sites were identified. For ide-cel, distance was correlated to age-adjusted mortality per 100,000 persons (r=.093, p=.011) and regression suggested that distance to nearest ide-cel site accounted for 0.9% of age-adjusted mortality (F=6.42, p=.011). For cilta-cel, distance was correlated to age-adjusted mortality per 100,000 persons (r=.122, p<.001) and regression suggested that distance to nearest cilta-cel site accounted for 1.5% of age-adjusted mortality (F=11.24, p<.001). When assessing disparity by race, non-Hispanic Blacks had a more age-adjusted mortality due to distance from CAR-T Center. For ide-cel, distance accounted for 2.5% of non-Hispanic Black age-adjusted mortality (F=3.929, p=.049). For cilta-cel, distance accounted for 6.4% of non-Hispanic Black age-adjusted mortality (F=10.404, p=.002). Conclusions Using geospatial analysis, we identified that a county's distance to CAR-T center had a statistically significant impact on age-adjusted multiple myeloma mortality. This impact was more pronounced for Non-Hispanic Black patients, of particular interest as MM is more likely to affect the Black patient. As more patients become eligible for CAR-T therapy, the benefit of living near a CAR-T center will likely grow. Distance to CAR-T centers may form a new interface with a patient's social determinants of health, creating a new health care disparity in MM.

BloodVol. 144(Supplement 1)
University Hospitals Seidman Cancer Center (US), Case Comprehensive Cancer Center, Case Western Reserve University (US)
Good health and well-being
Openalex Percentile: Top 73%
Health Systems, Economic Evaluations, Quality of Life
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.