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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

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Published on: September 27, 2024

The complication-overall survival (CompOS) risk tool predicts risk of a severe postoperative complications relative

Yutaka Endo¹, Diamantis I Tsilimigras¹, Selamawit Woldesenbet¹

¹Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, Ohio, United States.

Journal of Gastrointestinal Surgery : Official Journal of the Society for Surgery of the Alimentary Tract

|March 6, 2024

Summary

A new risk model predicts complications and survival after liver resection for primary liver cancer. This tool helps identify high-risk patients for better outcomes.

Keywords:

Comprehensive Complication Index Hepatocellular carcinoma Intrahepatic cholangiocarcinoma Multi-institutional database

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Area of Science:

Hepatobiliary surgery
Surgical oncology
Predictive modeling

Background:

Liver resection is a primary treatment for liver cancer.
Perioperative complications and long-term survival are critical outcomes.
Predictive tools for these outcomes are needed.

Purpose of the Study:

To develop a predictive tool for perioperative complications using the Comprehensive Complication Index (CCI).
To predict long-term survival outcomes after liver resection for primary liver cancer.
To integrate these predictions into a single risk model.

Main Methods:

Utilized a multi-institutional international database of patients undergoing liver resection for hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICC) between 1990 and 2020.
Developed a risk model based on preoperative factors.
Validated the model using test and validation cohorts.

Main Results:

1411 patients included; 49.5% experienced complications, 7.9% had major complications.
A complication-overall survival (CompOS) profile was established, with 55.1% in a favorable risk group.
The model demonstrated good predictive accuracy with areas under the curve of 0.73 (test) and 0.76 (validation).

Conclusions:

The developed CompOS risk model accurately stratifies patients based on short- and long-term risks.
Identifies a subset of patients at high risk for major complications and poor overall survival.
This tool can aid in surgical decision-making and patient management for liver cancer resection.