Development of a post-treatment prognostic model for hepatocellular carcinoma based on nutritional, immune, and inflammatory scoring systems and REDCap-enabled follow-up.

Background: This study examined the association between pre-treatment inflammation, immune cell- and nutrition/metabolism-related scores, and prognosis of patients with hepatocellular carcinoma (HCC) post-treatment. Methods: This study collected clinical data on demographics, pretreatment blood tests, pathology, and follow-up. Key markers included C-reactive protein, albumin, neutrophil and lymphocyte counts, creatinine, bilirubin, international normalized ratio, tumor size and number, alpha-fetoprotein, platelet count, and CD4+/CD8+ T-cell levels. Disease-free survival (DFS) was calculated from treatment to recurrence. Twelve scores were derived. Kaplan-Meier and univariate Cox analyses identified significant predictors, followed by multivariate Cox models to determine independent risk factors. Logistic regression and receiver operating characteristic (ROC) analyses assessed predictive performance. Scores were grouped as inflammation-, metabolism-, or immune-related to construct nomograms and evaluate C-index values using R software. Results: Except for Gender ( Conclusion: Pre-treatment PALBI and CRAFITY scores are independent prognostic factors for post-treatment survival among patients with HCC, with inflammation-related scores providing superior predictive value for DFS compared to metabolism- and immune-related scores.