Predictive impact of the inflammation-based indices in uveal melanoma liver metastases treated with transarterial hepatic chemoperfusion

Background The aim of the study was to evaluate pretreatment inflammatory markers as prognostic factors in patients with unresectable uveal melanoma liver metastases treated with transarterial hepatic chemoperfusion. Patients and methods 54 patients (44% male, median age: 61 years) were retrospectively assessed. A median of 3 (range: 1–11) treatment sessions were performed with melphalan (92%) or fotemustin (8%). Inflammatory indices were calculated as follows: neutrophils/nl to lymphocytes/nl ratio (NLR), systemic immune-inflammation index ([platelets/nl × neutrophils/nl]/[lymphocytes/nl]; SII), and platelets/nl to lymphocytes/nl ratio (PLR). The cut-off for dichotomization purposes was set at the median (inflammatory indices, hepatic tumor burden) or the upper level of normal. Kaplan Meier analysis was performed for median overall survival (OS) in months, and Cox proportional hazard model for uni(UVA) and multivariate (MVA) hazard ratio (HR, 95%CI) analyses were performed. Results Median OS of the study cohort was 7.7 (6.3–10.9) months. In UVA OS was prolonged for low C reactive protein (CRP) (13.5 vs. 5.2; p = 0.0005), low SII (10.8 vs. 5.6; p = 0.0005), low NLR (11.1 vs. 6.3; p = 0.0045), low aspartate aminotransferase (AST) (11.5 vs. 5.6; p = 0.015), alanine aminotransferases (ALT) (11.5 vs. 5.6; p = 0.01), and tumor burden ≦ 50% (8.2 vs. 4.8; p = 0.007). MVA confirmed low CRP (HR: 0.29, 0.11–0.7; p = 0.005), low SII (HR: 0.19, 0.11–0.7; p = 0.008), and low ALT (HR: 0.13, 0.02–0.63; p = 0.011) as independent predictors for prolonged OS. Patients with ≦ 1, 2, 3 elevated significant MVA-factors survived a median of 14.9, 7.7, and 3.9 months, respectively (p = 0.0001). Conclusions Pretreatment inflammatory markers (CRP, SII) and AST were independent prognostic survival markers in patients with uveal melanoma liver metastases treated with transarterial hepatic chemoperfusion. A combination of factors may help to identify patients potentially benefitting from treatment.