Novel models for predicting individualized outcomes in patients with advanced hepatocellular carcinoma receiving immunotherapy.
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BACKGROUND: We aim to develop a nomogram that can effectively differentiate target hepatocellular carcinoma (HCC) patients to receive immunotherapy and categorize their risk levels. METHODS: This retrospective study analyzed 328 patients with HCC who had received anti-programmed cell death-1 (PD-1) drugs between January 2019 and December 2022. Univariate and multivariate Cox regression analyses were used to identify potential prognostic factors. The novel nomograms were then established based on the above independent predictors and assessed by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA). Kaplan-Meier curves were performed to estimate the progression-free survival (PFS) and overall survival (OS) based on risk scores. RESULTS: Survival analyses identified the treatment sequence, disease progression with bone or lymph node, and Child-Pugh classification as prognostic factors for PFS and Barcelona Clinic Liver Cancer (BCLC) stage, Child-Pugh stage, ascites, Eastern Cooperative Oncology Group Performance Status (ECOG PS), surgery, disease progression with lymph node, and neutrophil-to-lymphocyte ratio (NLR) for OS. The PFS model had a C-index of 0.657 (0.609-0.705), matching validation set performance [0.657 (0.582-0.733)]. OS model C-indices were 0.787 (0.748-0.826) and 0.671 (0.606-0.736) for training and validation cohorts. Calibration plots and DCA curves indicated high accuracy and applicability. Significant differences in OS and PFS times were observed between low- and high-risk groups based on current nomogram points (P < 0.0001). CONCLUSIONS: The prognostic nomogram based on patients' demographics and clinicopathological factors showed reliable efficacy in predicting survival benefits in intermediate and advanced-stage HCC patients following immunotherapy, aiding in individual decision-making.