Relation between drug therapy-based comorbidity indices, Charlson's comorbidity index, polypharmacy and mortality in...

Area of Science:

• Geriatrics
• Clinical Epidemiology
• Health Services Research

Background:

• Comorbidity indices assess disease burden and predict clinical outcomes like mortality, particularly in older, intensively treated populations.
• Charlson's Comorbidity Index (CCI) is widely used, but therapy-based comorbidity indices (TBCI) like Drug Derived Complexity Index (DDCI), Medicines Comorbidity Index (MCI), and Chronic Disease Score (CDS) are alternatives when diagnostic data is limited.

Purpose of the Study:

• To evaluate the predictive accuracy of various comorbidity indices and polypharmacy for 1-year mortality.
• To compare the performance of CCI, DDCI, MCI, and CDS in different healthcare settings.

Main Methods:

• Survival analysis and Receiver Operating Characteristic (ROC) analysis were applied.
• Data from three Italian cohorts were analyzed: nursing home residents (Korian), and older adults in acute geriatric or internal medicine wards (REPOSI, ELICADHE).

Main Results:

• Higher CCI scores were consistently associated with increased 1-year mortality risk across all cohorts.
• DDCI and excessive polypharmacy showed similar predictive trends, while MCI and CDS were not consistently significant.
• The overall predictive power of all comorbidity indices, assessed via ROC curves, was poor and comparable across settings.

Conclusions:

• Comorbidity indices demonstrated suboptimal performance in predicting 1-year mortality in the evaluated cohorts.
• Despite limitations, elevated scores on these indices generally correlated with higher mortality risk, suggesting some utility in risk stratification.