Defining Multimorbidity and Its Impact in Older United States Veterans Newly Treated for Multiple Myeloma.

Summary

Older veterans with multiple myeloma exhibit distinct patterns of chronic illness, such as multisystem impairment or lung disease, which are more predictive of death than a simple count of comorbidities. These findings suggest that identifying specific clusters of coexisting diseases can better help clinicians predict survival and hospitalization risks for patients with this cancer.

Key result

Veterans with multisystem impairment had the highest mortality risk among identified multimorbidity patterns, with a hazard ratio of 2.25 (95% CI, 2.03 to 2.50) compared to those with minimal comorbidity.

Abstract

BACKGROUND: Traditional count-based measures of comorbidity are unlikely to capture the complexity of multiple chronic conditions (multimorbidity) in older adults with cancer. We aimed to define patterns of multimorbidity and their impact in older United States veterans with multiple myeloma (MM). METHODS: We measured 66 chronic conditions in 5076 veterans aged 65 years and older newly treated for MM in the national Veterans Affairs health-care system from 2004 to 2017. Latent class analysis was used to identify patterns of multimorbidity among these conditions. These patterns were then assessed for their association with overall survival, our primary outcome. Secondary outcomes included emergency department visits and hospitalizations. RESULTS: Five patterns of multimorbidity emerged from the latent class analysis, and survival varied across these patterns (log-rank 2-sided P < .001). Older veterans with cardiovascular and metabolic disease (30.9%, hazard ratio [HR] = 1.33, 95% confidence interval [CI] = 1.21 to 1.45), psychiatric and substance use disorders (9.7%, HR = 1.58, 95% CI = 1.39 to 1.79), chronic lung disease (15.9%, HR = 1.69, 95% CI = 1.53 to 1.87), and multisystem impairment (13.8%, HR = 2.25, 95% CI = 2.03 to 2.50) had higher mortality compared with veterans with minimal comorbidity (29.7%, reference). Associations with mortality were maintained after adjustment for sociodemographic variables, measures of disease risk, and the count-based Charlson Comorbidity Index. Multimorbidity patterns were also associated with emergency department visits and hospitalizations. CONCLUSIONS: Our findings demonstrate the need to move beyond count-based measures of comorbidity and consider cancer in the context of multiple chronic conditions.