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 5,076 Veterans age ≥ 65 years newly-treated for MM in the national Veterans Affairs healthcare system from 2004 to 2017. Latent class analysis (LCA) 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 LCA, and survival varied across these patterns (log-rank two-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 to Veterans with minimal comorbidity (29.7%, reference). Associations with mortality were maintained after adjustment for socio-demographic 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.