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Abstract Background & aims Complications after laparoscopic liver resection (LLR) are important factors affecting the prognosis of patients, especially for complex hepatobiliary diseases. The present study aimed to evaluate the value of a three-dimensional (3D) printed dry-laboratory model in the precise planning of LLR for complex hepatobiliary diseases. Methods Patients with complex hepatobiliary diseases who underwent LLR were preoperatively enrolled, and divided into two groups according to whether using a 3D-printed dry-laboratory model (3D vs. control group). Clinical variables were assessed and complications were graded by the Clavien-Dindo classification. The Comprehensive Complication Index (CCI) scores were calculated and compared for each patient. Multivariable analysis was performed to determine the risk factors of postoperative complications. Results Sixty-two patients with complex hepatobiliary diseases underwent the precise planning of LLR. Among them, thirty-one patients acquired the guidance of a 3D-printed dry-laboratory model, and others were only guided by traditional enhanced CT or MRI. The results showed no significant differences between the two groups in baseline characters. However, compared to the control group, the 3D group had a lower incidence of intraoperative blood loss, as well as postoperative 30-day and major complications, especially bile leakage (all P

Abstract Background Platelet distribution width (PDW), but not platelet count, was found to more comprehensively reflect platelet activity. The present study, thus, aimed to evaluate the prognostic value of PDW to lymphocyte ratio (PDWLR) in patients with hepatocellular carcinoma (HCC) following hepatectomy. Methods Patients following hepatectomy were analyzed retrospectively. The Kaplan-Meier survival curves and Cox regression model were used to determine the prognostic value of PDWLR. Results 241 patients were analyzed eventually, and stratified into low and high PDWLR groups (≤ 9.66 vs. > 9.66). Results of comparing the baseline characteristics showed that high PDWLR was significantly associated with cirrhosis, and intraoperative blood loss (all P

Abstract Background and aims Preoperative prediction of microvascular invasion (MVI) using a noninvasive method remain unresolved, especially in HBV-related in intrahepatic cholangiocarcinoma (ICC). This study aimed to build and validate a preoperative prediction model for MVI in HBV-related ICC. Methods Patients with HBV-associated ICC undergoing curative surgical resection were identified. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors of MVI in the training cohort. Then, a prediction model was built by enrolling the independent risk factors. The predictive performance was validated by receiver operator characteristic curve (ROC) and calibration in the validation cohort. Results Consecutive 626 patients were identified and randomly divided into the training (418, 67%) and validation (208, 33%) cohorts. Multivariate analysis showed that TBIL, CA19-9, tumor size, tumor number, and preoperative image lymph node metastasis were independently associated with MVI. Then, a model was built by enrolling former fiver risk factors. In the validation cohort, the performance of this model showed good calibration. The area under the curve was 0.874 (95% CI: 0.765–0.894) and 0.729 (95%CI: 0.706–0.751) in the training and validation cohort, respectively. Decision curve analysis showed an obvious net benefit from the model. Conclusion Based on clinical data, an easy model was built for the preoperative prediction of MVI, which can assist clinicians in surgical decision-making and adjuvant therapy.

Background: The long-term prognosis of patients with hepatocellular carcinoma (HCC) after surgery remains far from satisfactory, especially in patients with microvascular invasion (MVI). This study aimed to evaluate the potential survival benefit from adjuvant lenvatinib for patients with HCC and MVI. Methods: Patients with HCC after curative hepatectomy were reviewed. All patients were divided into 2 groups according to adjuvant lenvatinib. Propensity score matching (PSM) analysis was used to reduce selection bias and make the results more robust. Survival curves are shown by the Kaplan-Meier (K-M) analysis and compared by the Log-rank test. Univariate and multivariate Cox regression analyses were performed to determine the independent risk factors. Results: Of 179 patients enrolled in this study, 43 (24%) patients received adjuvant lenvatinib. After PSM analysis, 31 pairs of patients were enrolled for further analysis. Survival analysis before and after PSM analysis showed a better prognosis in the adjuvant lenvatinib group (all P < .05). The adverse events associated with oral lenvatinib were acceptable. Multivariate Cox regression analysis showed that adjuvant lenvatinib was an independent protective factor for improving overall survival (OS) (hazard ratio [HR] = 0.455, 95% confidence interval [CI] = 0.249-0.831, P = .001) and recurrence-free survival (RFS) (HR = 0.523, 95% CI = 0.308-0.886, P = .016). Conclusions: Postoperative adjuvant targeted therapy can improve the long-term prognosis of patients with HCC and MVI. Therefore, in clinical practice, oral lenvatinib should be recommended for patients with HCC and MVI to decrease tumor recurrence and improve long-term survival.