NCT06008548

A New Conception About Individualized Treatment Allocation for HCC

A New Conception About Individualized Treatment Allocation for HCC-Using Machine Learning

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 4,991 (actual)
• Sponsor: Tang-Du Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 100 Years
• Healthy volunteers: Not accepted

Summary

The current guidelines on hepatocellular carcinoma (HCC) aimed to build effective prognostic stratification strategies to guide therapeutic allocation; however, the current guidelines did not consider the simultaneous comparison of distinct therapies in similar populations. Here, the investigators aimed to develop and validate a new, integrated prognostic scheme for HCC patients using artificial intelligence (AI) to simulate the survival outcomes of patients allocated to different treatments.

Detailed description

Given that liver resection (LR) and transarterial chemoembolization (TACE) are the mainstay curative and palliative therapies for HCC, respectively, patients who underwent LR or TACE were included in the study. Various prognostic AI algorithms were modeled using data from a large multi-institutional cohort, where LR and TACE were considered independent factors. The C-index, Brier score (BS), and area under the receiver operating characteristic curve (auROC) were calculated to estimate the AI models.

Conditions

• HCC
• Transarterial Chemoembolization
• Resection

Interventions

Type	Name	Description
PROCEDURE	TACE

Timeline

• Start date: 2010-01-01
• Primary completion: 2021-01-30
• Completion: 2021-10-01
• First posted: 2023-08-23
• Last updated: 2023-08-23