Background: Patients with alpha-fetoprotein (AFP)-positive hepatocellular carcinoma (HCC) have aggressive biological behavior and poor prognosis. Therefore, survival time is one of the greatest concerns for patients with AFP-positive HCC. This study aimed to demonstrate the utilization of six machine learning (ML)-based prognostic models to predict overall survival of patients with AFP-positive HCC. Methods: Data on patients with AFP-positive HCC were extracted from the Surveillance, Epidemiology, and End Results database. Six ML algorithms (extreme gradient boosting [XGBoost], logistic regression [LR], support vector machine [SVM], random forest [RF], K-nearest neighbor [KNN], and decision tree [ID3]) were used to develop the prognostic models of patients with AFP-positive HCC at one year, three years, and five years. Area under the receiver operating characteristic curve (AUC), confusion matrix, calibration curves, and decision curve analysis (DCA) were used to evaluate the model. Results: A total of 2,038 patients with AFP-positive HCC were included for analysis. The 1-, 3-, and 5-year overall survival rates were 60.7%, 28.9%, and 14.3%, respectively. Seventeen features regarding demographics and clinicopathology were included in six ML algorithms to generate a prognostic model. The XGBoost model showed the best performance in predicting survival at 1-year (train set: AUC = 0.771; test set: AUC = 0.782), 3-year (train set: AUC = 0.763; test set: AUC = 0.749) and 5-year (train set: AUC = 0.807; test set: AUC = 0.740). Furthermore, for 1-, 3-, and 5-year survival prediction, the accuracy in the training and test sets was 0.709 and 0.726, 0.721 and 0.726, and 0.778 and 0.784 for the XGBoost model, respectively. Calibration curves and DCA exhibited good predictive performance as well. Conclusions: The XGBoost model exhibited good predictive performance, which may provide physicians with an effective tool for early medical intervention and improve the survival of patients.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with increased cardiovascular disease (CVD) risk. Lipoprotein(a) [Lp(a)] and insulin resistance (IR) are established cardiovascular risk factors, yet their joint associations with cardiovascular outcomes in MASLD remain poorly understood. We analyzed data from the UK Biobank and included 101,348 adults with MASLD for CVD mortality analyses and 94,089 individuals without baseline CVD for incident CVD analyses. IR was assessed using the triglyceride-glucose (TyG) index. Participants were categorized according to Lp(a) levels (< 125 vs. ≥ 125 nmol/L) and TyG index (low vs. high, defined by the 75th percentile) and further classified into four joint Lp(a)/IR groups, with low Lp(a)/low IR serving as the reference group. Cox proportional hazards models were used to evaluate associations of Lp(a), TyG, and their combined categories with incident CVD and CVD mortality. During a median follow-up of 15.7 years, elevated Lp(a) and higher TyG levels were each independently associated with increased risks of incident CVD and CVD mortality, regardless of each other's status. In the fully adjusted model, each SD increase in Lp(a) was associated with a 14% higher risk of CVD mortality (HR, 1.14; 95% CI 1.10-1.19; P < 0.001) and a 9% higher risk of incident CVD (HR, 1.09; 95% CI, 1.07-1.11; P < 0.001). Similarly, each SD increase in TyG was associated with a 27% higher risk of CVD mortality (HR, 1.27; 95% CI 1.21-1.34; P < 0.001) and a 9% higher risk of incident CVD (HR, 1.09; 95% CI 1.07-1.12; P < 0.001). Compared with participants in the reference group with Lp(a) < 125 nmol/L and low IR, those with concomitantly elevated Lp(a) and high IR exhibited the highest cardiovascular risk, with adjusted HRs of 2.04 (95% CI 1.63-2.55) for CVD mortality and 1.49 (95% CI 1.35-1.64) for incident CVD (both P < 0.001), with a significant dose-response trend across groups (P for trend < 0.001). These associations remained consistent across subgroups stratified by age, sex, obesity, diabetes, and hypertension. Elevated Lp(a) and IR were independently associated with adverse cardiovascular outcomes in MASLD, with the highest risk observed among individuals with concomitant elevations in both markers.