BACKGROUND Postoperative morbidity after curative resection for hilar cholangiocarcinoma (HCCA) is common; however, whether it has an impact on oncological prognosis is unknown. AIM To evaluate the influence of postoperative morbidity on tumor recurrence and mortality after curative resection for HCCA. METHODS Patients with recently diagnosed HCCA who had undergone curative resection between January 2010 and December 2017 at The First Affiliated Hospital of Army Medical University in China were enrolled. The independent risk factors for morbidity in the 30 d after surgery were investigated, and links between postoperative morbidity and patient characteristics and outcomes were assessed. Postoperative morbidities were divided into five grades based on the Clavien-Dindo classification, and major morbidities were defined as Clavien-Dindo ≥ 3. Univariate and multivariate Cox regression analyses were used to evaluate the risk factors for recurrence-free survival (RFS) and overall survival (OS). RESULTS Postoperative morbidity occurred in 146 out of 239 patients (61.1%). Multivariate logistic regression revealed that cirrhosis, intraoperative blood loss > 500 mL, diabetes mellitus, and obesity were independent risk factors. Postoperative morbidity was associated with decreased OS and RFS (OS: 18.0 mo vs 31.0 mo, respectively, P = 0.003; RFS: 16.0 mo vs 26.0 mo, respectively, P = 0.002). Multivariate Cox regression analysis indicated that postoperative morbidity was independently associated with decreased OS [hazard ratios (HR): 1.557, 95% confidence interval (CI): 1.119-2.167, P = 0.009] and RFS (HR: 1.535, 95%CI: 1.117-2.108, P = 0.008). Moreover, major morbidity was independently associated with decreased OS (HR: 2.175; 95%CI: 1.470-3.216, P < 0.001) and RFS (HR: 2.054; 95%CI: 1.400-3.014, P < 0.001) after curative resection for HCCA. CONCLUSION Postoperative morbidity (especially major morbidity) may be an independent risk factor for unfavorable prognosis in HCCA patients following curative resection.

Background An important prognostic indicator of hilar cholangiocarcinoma (HCCA) in patients after surgery is metastasis of lymph nodes (LN). However, there are many types of LN staging systems to the issue of a better determination of the prognosis of patients through the lymphatic staging system which needs research. Based on the above, we tried to re-evaluate the staging system of HCCA LNs. We compared the American Joint Committee on Cancer (AJCC), number of metastatic LNs (MLN), ratio of LN (LNR), and log odds of MLNs (LODDS) in individuals undergoing curative resection to determine the best LN staging system. Methods In the current study, we retrospectively analyzed 229 patients undergoing curative resection. We evaluated the impact of the stage of AJCC pN, LNR, LODDS, and MLN on OS (overall survival) and RFS (recurrence-free survival). According to the curve of receiver operating characteristic (ROC), we compared the predictive capacity of different staging systems of LN for survival and recurrence. Results Multivariate analysis results revealed that LODDS >  − 0.45 (95% CI = 1.115–2.709, P = 0.015; 95% CI = 1.187–2.780, P = 0.006) are independent risk factors affecting OS and RFS, respectively. Compared with LN status, AJCC pN stage, MLN, and LNR, the variable having the highest area under the ROC curve (AUC) was LODDS when predicting 1-year, 3-year, and 5-year OS and RFS. Conclusion This study shows that metastasis of LNs is a key indicator for predicting patient death and recurrence. Among them, LODDS is the best LN staging system for the prognostic evaluation of HCCA patients after surgery. Clinicians can incorporate LODDS into HCCA patient lymphatic staging system for a more accurate prognosis of HCCA patients post-surgery.

BackgroundRecurrence is the main cause of death in perihilar cholangiocarcinoma (pCCA) patients after surgery. Identifying patients with a high risk of recurrence is important for decision-making regarding neoadjuvant therapy to improve long-term outcomes.AimThe objective of this study was to develop and validate a prognostic model to predict recurrence-free survival (RFS) after curative resection of pCCA.MethodsPatients following curative resection for pCCA from January 2008 to January 2016 were identified from a multicenter database. Using random assignment, 70% of patients were assigned to the training cohort, and the remaining 30% were assigned to the validation cohort. Independent predictors of RFS after curative resection for pCCA were identified and used to construct a prognostic model. The predictive performance of the model was assessed using calibration curves and the C-index.ResultsA total of 341 patients were included. The median overall survival (OS) was 22 months, and the median RFS was 14 months. Independent predictors associated with RFS included lymph node involvement, macrovascular invasion, microvascular invasion, maximum tumor size, tumor differentiation, and carbohydrate antigen 19-9. The model incorporating these factors to predict 1-year RFS demonstrated better calibration and better performance than the 8th American Joint Committee on Cancer (AJCC) staging system in both the training and validation cohorts (C-indexes: 0.723 vs. 0.641; 0.743 vs. 0.607).ConclusionsThe prognostic model could identify patients at high risk of recurrence for pCCA to inform patients and surgeons, help guide decision-making for postoperative adjuvant therapy, and improve survival.

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