Modified Charlson Comorbidity Index to Improve Management of Patients with Hepatocellular Carcinoma: A Step Towards Multiparametric Approach.

Hepatocellular carcinoma (HCC) patients frequently present with comorbidities that limit therapeutic options and increase mortality. This study evaluated the performance of the Charlson Comorbidity Index (CCI) and a modified CCI (mCCI) in stratifying patients with HCC to predict treatment allocation and survival. A retrospective single-center cohort study analyzed 401 patients with de novo HCC (74% male, median age 68 years, 80% Child-Pugh-Turcotte (CPT) A, 65% viral etiology, 70% Barcelona Clinic Liver Cancer stage (BCLC) 0/A). CCI and mCCI (with points related to HCC and chronic liver disease excluded), were calculated at diagnosis for each patient. The primary endpoint was overall survival (OS) estimated by Kaplan-Meier method and compared across mCCI classes; Cox uni/multivariable models were applied to identify predictors of mortality. The secondary aim was evaluating the association between mCCI and treatment allocation. While CCI classified 94% of patients as "high-risk", mCCI reclassified patients into "high-risk" (21%), "intermediate-risk" (48%), and "low-risk" (31%), demonstrating better stratification whilst maintaining a strong correlation with CCI (Kendall's tau-b = 0.57, < 0.001). BCLC B patients with "high-risk" mCCI exhibited significantly lower access to first-line curative treatment (14% vs. 47%, = 0.03). Moreover, "high" or "intermediate-risk" patients according to mCCI experienced significantly shorter OS compared to "low-risk" (median OS 36 vs. 49 vs. 74 months, < 0.001). "High-risk" and "intermediate-risk" mCCI classes were independent predictors of mortality, alongside alpha-fetoprotein, CPT and BCLC stage. Considering the items composing mCCI, age and cardiovascular diseases were independent predictors of mortality. mCCI provides a more accurate assessment of comorbidities than the standard CCI and is associated with survival, hence it can contribute to designing patient-tailored therapeutic strategies.