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Updated: Feb 8, 2026

Establishment of a Human Multiple Myeloma Xenograft Model in the Chicken to Study Tumor Growth, Invasion and Angiogenesis
Published on: May 1, 2015
Differential life expectancies and life years lost associated with multiple myeloma in the United States: a
Tzeyu L Michaud1,2, Yi-Hsuan Shih3, Mengmeng Ji4
1Department of Health Promotion, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, United States.
Background:
Multiple myeloma (MM) health disparities are well-documented, with non-Hispanic Black (NHB) and male individuals experiencing higher disease burdens than their non-Hispanic White (NHW) or female counterparts. However, no studies have shown that how these disparities translate into differences in life expectancy, particularly for monoclonal gammopathy of undetermined significance (MGUS), a precursor to MM. This study quantified the remaining life years and life years lost associated with MGUS and MM to inform MM prevention and control priorities.
Methods:
We developed a discrete-event simulation (DES) model of the natural history of MM, calibrated using nationally representative data on serologic-detected MGUS and registry-based MM. The model was stratified by race and gender (NHB/NHW men and women). Life years lost was computed as the difference in life years between populations without and with MGUS/MM.
Results:
Remaining life years for MGUS/MM were 17.8/6.3 (95% prediction interval [PI]: 17.4-18.2/5.9-6.9) for NHB men, 20.1/7.7 (95% PI: 19.7-20.5/7.1-8.3) for NHB women, 20.9/7.3 (95% PI: 20.3-21.4/6.7-8.0) for NHW men, and 23.0/8.5 (95% PI: 22.5-23.6/7.7-9.4) for NHW women. Corresponding life years lost associated with MGUS/MM was 7.6/14.2 (95% PI: 7.3-8.0/13.3-15.1), 8.0/16.0 (95% PI: 7.7-8.4/15.0-17.0), 8.4/16.0 (95% PI: 8.0-8.9/14.7-17.3), and 8.8/18.1 (95% PI: 8.4-9.2/16.9-19.4), respectively.
Conclusion:
Substantial racial and gender differences were identified and quantified in disease burden associated with MGUS and MM, which provides concrete targets for MM prevention and control efforts. Our findings underscore the need for tailored strategies to reduce MM disparities, for example, enhancing disease monitoring among NHB populations and improving treatment adherence among men with MM.
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