Locoregional therapies in patients with recurrent intrahepatic cholangiocarcinoma after curative resection

Cox model risk score to predict survival of intrahepatic cholangiocarcinoma after ultrasound-guided ablation

PURPOSE

To explore factors associated with overall survival (OS) and progression-free survival (PFS) of intrahepatic cholangiocarcinoma (iCCA) after ultrasound-guided ablation and establish a model for survival risk evaluation.

METHODS

Data from 54 patients with 86 iCCAs between August 2008 and October 2022 were retrospectively analyzed. Cox regression were used to analyze the effects of clinical features on OS and PFS. Based on the variables screened by multivariable analysis, a model was established to predict the survival of the patients. Time-dependent receiver operating characteristic (timeROC) curve was constructed to evaluate the performance of this model. The model was further verified by bootstrap validation. The clinical usefulness of the model was evaluated by the decision curve analysis (DCA).

RESULTS

During follow up, 39 patients died and 49 patients developed recurrence. Pre-ablation CA199 level > 140 U/ml was the only independent predictor of poor PFS. Age > 70 years, early recurrence, maximal diameter of tumor size > 1.5 cm and pre-ablation CA199 level > 140 U/ml were significantly associated with poor OS. Then a model was established based on the above four variables. The areas under the timeROC curve (AUC) for 1-year, 2-year, 3-year, 5-year were 0.767, 0.854, 0.791 and 0.848, respectively. After bootstrapping for 1000 repetitions, the AUCs were similar to the initial model. DCA also demonstrated that the model had good positive net benefits.

CONCLUSION

The established model in this study could predict the survival outcomes of the patients with iCCA after thermal ablation, but further research was needed to validate the results.

Preoperative Differentiation of Combined Hepatocellular-Cholangiocarcinoma From Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: A Nomogram Based on Ultrasonographic Features and Clinical Indicators

OBJECTIVE

To establish a predictive nomogram to distinguish combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) based on preoperative clinical and ultrasound findings.

METHODS

A total of 261 patients with pathologically confirmed primary liver cancers (PLCs) were enrolled in this retrospective study, comprising 87 CHCs, 87 HCCs, and 87 ICCs matched by propensity score matching. Patients were randomly assigned to a training cohort and a validation one at the ratio of 7:3. A nomogram integrating ultrasound imaging characteristics and clinical features was established based on the independent risk factors selected by least absolute shrinkage and selection operator (LASSO) regression. The performance of the nomogram was evaluated in the training and validation cohorts in terms of discrimination, calibration, and clinical usefulness.

RESULTS

The nomogram, consisting of ultrasound imaging features (shape and margin on B-mode ultrasound, enhanced pattern on contrast-enhanced ultrasound) and clinical information [elevated alpha fetoprotein (AFP) level and serum protein electrophoresis (SPE) α1 level], showed promising performance in differentiating CHC from HCC and ICC, with the concordance index (C-index) of 0.8275 and 0.8530 in the training cohort and the validation cohort, respectively. Hosmer-Lemeshow test and the calibration curves suggested good consistency between predictions and observations. High clinical practicability was confirmed by the decision curve analysis.

CONCLUSIONS

The nomogram based on clinical and ultrasound imaging characteristics showed good performance in the discrimination of CHC from other subtypes of PLC and would be valuable in clinical decision-making.