A study looking at U.S. veterans aged 65 and older identified five distinct patterns of multimorbidity for multiple myeloma (MM) that affected outcomes.
Traditionally, comorbidities are measured in oncology as a function of the number of comorbid conditions or as a count-based index. For older patients with MM, certain comorbid conditions may pose as much a threat to a patient’s health as the cancer itself.
A study published recently in the Journal of the National Cancer Institute, measured 66 chronic conditions in 5,076 veterans aged 65 and older with newly treated MM and used latent class analysis to identify patterns of multimorbidity among the conditions. These patterns were then assessed for any association with survival.
In all, the researchers identified five patterns of multimorbidity. The first pattern (29.7%) included veterans who had minimal comorbidity beyond myeloma. The second pattern (30.9%) included veterans with cardiovascular and metabolic diseases, including diabetes, ischemic heart disease, and chronic kidney disease. The third pattern (9.7%) was veterans with psychiatric and substance use disorders. The fourth (15.9%) was veterans with chronic lung disease and tobacco use disorder. Finally, the fifth pattern (13.8%) included veterans with multisystem impairment, including cardiovascular disease, lung disease, psychiatric disorders, and sensory impairments.
Survival varied across these multimorbidity patterns. Older veterans with cardiovascular and metabolic disease (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.21–1.45), psychiatric and substance use disorders (HR, 1.58; 95% CI, 1.39–1.79), chronic lung disease (HR, 1.69; 95% CI, 1.53–1.87), and multisystem impairment (HR, 2.25; 95% CI, 2.03–2.50) all had higher mortality compared with veterans with minimal comorbidity.
“Future research should elucidate the mechanisms by which these multimorbidity patterns lead to worse outcomes. Moreover, future work should compare patterns of multimorbidity that arise in other malignancies as well as patterns that arise in other, nonveteran populations,” the researchers wrote. “If this approach is validated, then tools should be developed to assist oncologists at the point of care with identifying patterns of multimorbidity and the specific comorbidities within each patient.”