ABSTRACT
Objective:To investigate the predictive value of preoperative aspartate aminotransferase to alanine aminotransferase ratio (AAR) for early recurrence after radical resection of single small hepatocellular carcinoma.Methods:A retrospective cohort study was conducted to analyze the clinical data of 137 patients who underwent radical resection of liver cancer at the General Hospital of Ningxia Medical University from January 2017 to July 2021. These patients were categorized into a recurrence group ( n = 72) and a non-recurrence group ( n = 65) based on early postoperative recurrence. Univariate and multivariate logistic regression analyses were conducted in the training cohort to identify independent risk factors for early recurrence of small hepatocellular carcinomas. Subsequently, the AARs were grouped, and patients with similar propensity scores estimated by the logistic model were matched 1:1 using the Propensity Score Match method with a caliper value of 0.02 to eliminate confounders. Logistic regression analysis was then repeated to assess the predictive value of the matched AAR for postoperative recurrence in patients with single small hepatocellular carcinoma. Results:Univariate analysis revealed that age ( χ2 = 4.22, P = 0.040), the ratio of fibrinogen to albumin ( χ2 = 8.26, P = 0.004), and the AAR ( χ2 = 5.83, P = 0.016) were significantly associated with early recurrence of small liver cancer after radical resection. Multivariate logistic regression analysis further identified age ( P = 0.042), the ratio of fibrinogen to albumin ( P = 0.024), and the AAR ( P = 0.018) as independent risk factors for early recurrence of single small hepatocellular carcinoma following radical surgery. After excluding confounding factors using the Propensity Score Match method, 25 patient pairs were successfully matched. Post-matching logistic regression analysis revealed that an AAR > 0.74 ( P = 0.005) and age > 60 years ( P = 0.024) were independent risk factors for early recurrence in patients with single small hepatocellular carcinoma following radical resection. Conclusion:Preoperative AAR is an independent risk factor for early recurrence in patients with single small hepatocellular carcinoma following surgery, demonstrating excellent predictive value.
ABSTRACT
Objective:To screen preoperative microvascular invasion (MVI)-related indicators in patients with hepatocellular carcinoma by machine learning, and to construct a predictive model for predicting MVI and evaluate it.Methods:The clinical data of hepatocellular carcinoma patients who underwent radical resection from January 2018 to March 2023 in General Hospital of Ningxia Medical University were retrospectively analyzed. A total of 437 patients were enrolled, including 325 males and 112 females, aged (56.3±13.6) years. The 437 patients were divided into a training set ( n=305) and a test set ( n=132) by computer-generated random numbers on a 7∶3 basis; the training set was used to construct the predictive model as well as to internally validate it by the five-fold cross-validation method, and the test set was used to externally validate the model. Two machine learning Boruta algorithm and LASSO regression, were used to screen MVI characteristic variables and construct multifactorial logistic regression prediction models. Receiver operating characteristic (ROC) curve, calibration curves, and decision curve were evaluated for predictive modeling, applying Shapley's additive explanatory analysis (SHAP) of the significance of key variables. Results:The intersection (5 variables) of 8 characteristic variables selected by Boruta algorithm and 8 variables selected by LASSO regression were selected: aspartate aminotransferase/lymphocyte ratio (ALR), tumor margin, intratumbral necrosis, tumor number and tumor maximum diameter, and the logistic regression model was constructed. The area under ROC curve for predicting the MVI were 0.77 (95% CI: 0.70-0.82) (training set), 0.76 (95% CI: 0.63-0.87) (validation set), and 0.84 (95% CI: 0.78-0.91) (test set). The prediction results of calibration curve logistic regression model were close to those of reagent, and the analysis of decision curve indicates that the model had good clinical application value. According to the mean absolute SHAP value, the order of importance was tumor margin, tumor maximum diameter, tumor number, ALR, and intratumoral necrosis. Conclusion:Tumor margin, tumor maximum diameter, tumor number, ALR and intratumoral necrosis were independent influencing factors for hepatocellular carcinoma associated with MVI, and the logistic regression model based on these factors was effective in predicting MVI.
