# Preoperative prognostic model combining tumor burden score and tumor markers to predict long-term outcomes following hepatectomy for intrahepatic cholangiocarcinoma: a multi-institutional analysis

## TL;DR

This study creates a new model to predict survival and recurrence after surgery for a type of liver cancer using tumor burden and markers.

## Contribution

A novel preoperative model combining tumor burden and markers improves outcome prediction for intrahepatic cholangiocarcinoma patients.

## Key findings

- Lower TCCA scores correlated with significantly better overall and recurrence-free survival in ICC patients.
- The TCCA model outperformed existing systems with higher C-index and lower AIC in both training and validation cohorts.
- The model maintained strong performance even in patients with negative CEA or CA19-9 levels.

## Abstract

Intrahepatic cholangiocarcinoma (ICC) is an aggressive liver malignancy with limited prognostic tools to guide treatment strategies. This study aimed to develop and validate a preoperative prognostic model combining tumor burden score (TBS), carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA19-9), termed the TCCA model, to predict outcomes in patients with ICC undergoing hepatectomy.

Patients who underwent curative resection for ICC between 2014 and 2020 were retrospectively identified from a multi-institutional database. The impact of the TCCA model on overall survival (OS) and recurrence-free survival (RFS) was evaluated in training and validation cohorts. Predictive performance was evaluated using the area under the Receiver Operating Characteristic curve (AUC), the Akaike Information Criterion (AIC), and the C-index.

A total of 849 patients were included. Lower TCCA scores were associated with better median OS (score 0: 59.7 months; score 1: 31.3 months; score 2: 19.4 months; score 3: 11.5 months, respectively) and median RFS (28.8; 15.4; 9.7; 8.1 months, respectively). The TCCA model performed well in both the training cohort (AUC: 0.697 for OS and 0.649 for RFS) and the validation cohort (AUC: 0.672 for OS and 0.632 for RFS), outperforming the 8th edition TNM system and other models, with the highest C-index (0.734) and lowest AIC (3840). Subgroup analyses demonstrated that the TCCA model maintained good discriminative ability among patients with negative CEA or CA19–9 levels.

The TCCA model accurately stratifies ICC patients for OS and RFS after resection. It provides a simple and practical tool for preoperative risk assessment, supporting individualized surgical decision-making and individualized patient counseling.