Systemic inflammatory response markers improve the discrimination for prognostic model in hepatocellular carcinoma

We aimed to evaluate the performance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and their combination (combined NLR-PLR, CNP) in predicting overall survival (OS) and recurrence-free survival (RFS) in a large cohort of unselected hepatocellular carcinoma (HCC) patients.

Training and validation cohort data were retrieved from the Italian Liver Cancer (ITA.LI.CA) database. The optimal cut-offs of NLR and PLR were calculated according to the multivariable fractional polynomial and the minimum p value method. The continuous effect and best cut-off categories of NLR and PLR were analyzed using multivariable Cox regression analysis. A shrinkage procedure adjusted over-fitting hazard ratio (HR) estimates of best cut-off categories. C-statistic and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination properties of the biomarkers when added to clinical survival models.

2,286 patients were split into training (n = 1,043) and validation (n = 1,243) cohorts. The optimal cut-offs for NLR and PLR were 1.45 and 188, respectively. NLR (HR 1.58, 95% CI 1.11-2.28, p = 0.014) and PLR (HR 1.79, 95% CI 1.11-2.90, p = 0.018) were independent predictors of OS. When incorporated into a clinical prognostic model that includes age, alpha-fetoprotein (AFP), the CHILD-Pugh score, and the Barcelona Clinic Liver Cancer (BCLC) staging system, CNP had a significant incremental value in predicting OS (IDI 1.3%, p = 0.04). Data were confirmed in the validation cohort. Neither NLR nor PLR significantly predicted RFS in the training cohort.

NLR, PLR, and CNP independently predicted shorter OS in HCC patients. The addition of CNP to the survival prediction model significantly improved the model's accuracy in predicting OS.