Abstract
BACKGROUND: In patients with hepatic alveolar echinococcosis (HAE), germinal cells of Echinococcus multilocularis (EM) might invade regional lymph nodes (LNs) causing LN metastasis. If infected LNs are not removed during surgery, the risk of postoperative recurrence significantly increases. We aimed to develop a preoperative prediction model for HAE hepatic hilar LN metastasis using clinical and imaging data, summarize our center's surgical experience, and analyze the long-term prognosis. MATERIALS AND METHODS: We retrospectively reviewed patients with HAE who underwent radical hepatectomy combined with systematic hepatic hilar LN dissection and targeted LN resection (SHD-TR) at our center from January 2016 to April 2025. We collected patients' clinical data, imaging characteristics, surgical outcomes, and recurrence rates. Univariate and multivariate analyses were conducted to identify independent predictive factors for HAE hepatic hilar LN metastasis to construct a prediction model. Receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate the predictive performance of the model. RESULTS: The independent predictive factors included LN diameter, nodular calcification, and nonenhancement. Recurrent disease was seen in four patients without LN metastasis and two patients with LN metastasis. Kaplan-Meier curves revealed no significant difference in disease-free survival (DFS) between the two groups (P = 0.920). The classification performance of the training and validation sets was consistent, with an area under the curve (AUC) of 0.895 [95% CI: 0.827-0.963] and 0.817 [95% CI: 0.669-0.964], respectively, for the ROC curve and 0.81 [95% CI: 0.685-0.904] and 0.721 [95% CI: 0.625-0.974], respectively, for the PR curve. CONCLUSION: The prognosis of hepatic hilar LN metastasis is similar to that of HAE without metastasis. Radical hepatectomy combined with SHD-TR is safe and effective for HAE patients with LN metastasis. The prediction model based on LN diameter, nodular calcification, and nonenhancement has a strong and stable discrimination ability for HAE LN metastasis.