Comparison between drug therapy-based comorbidity indices and the Charlson Comorbidity Index for the detection of severe multimorbidity in older subjects

Background: To know burden disease of a patient is a key point for clinical practice and research, especially in the elderly. Charlson’s Comorbidity Index (CCI) is the most widely used rating system, but when diagnoses are not available therapy-based comorbidity indices (TBCI) are an alternative. However, their performance is debated. This study compares the relations between Drug Derived Complexity Index (DDCI), Medicines Comorbidity Index (MCI), Chronic Disease Score (CDS), and severe multimorbidity, according to the CCI classification, in the elderly. Methods: Logistic regression and Receiver Operating Characteristic (ROC) analysis were conducted on two samples from Italy: 2579 nursing home residents (Korian sample) and 7505 older adults admitted acutely to geriatric or internal medicine wards (REPOSI sample). Results: The proportion of subjects with severe comorbidity rose with TBCI score increment, but the Area Under the Curve (AUC) for the CDS (Korian: 0.70, REPOSI: 0.79) and MCI (Korian: 0.69, REPOSI: 0.81) were definitely better than the DDCI (Korian: 0.66, REPOSI: 0.74). All TBCIs showed low Positive Predictive Values (maximum: 0.066 in REPOSI and 0.317 in Korian) for the detection of severe multimorbidity. Conclusion: CDS and MCI were better predictors of severe multimorbidity in older adults than DDCI, according to the CCI classification. A high CCI score was related to a high TBCI. However, the opposite is not necessarily true probably because of non-evidence-based prescriptions or physicians’ prescribing attitudes. TBCIs did not appear selective for detecting of severe multimorbidity, though they could be used as a measure of disease burden, in the absence of other solutions.