Downstaging Prediction Model for HCC

N/ANot Yet RecruitingNCT07058649

Beijing Tsinghua Chang Gung Hospital369 enrolled

Overview

This study is a real-world, single-center study that collects imaging and clinical data from patients with HCC who are downstaged beyond the UCSF criteria.

This study is a real-world, single-center study that collects imaging and clinical data from patients with HCC who are downstaged beyond the UCSF criteria. It constructs a predictive model for downstaging treatment of liver cancer beyond the UCSF standards and completes external validation. This model will assist in clinical decision-making for the downstaging treatment of liver cancer beyond the UCSF criteria. Further downstaging methods are stratified to guide the selection of individualized downstaging treatment options for liver cancer beyond the UCSF standards.

Study Type

OBSERVATIONAL

Enrollment

369

Conditions

HCC - Hepatocellular Carcinoma

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * (A) Adult patients with HCC over the age of 18 (clinically diagnosed or pathologically diagnosed); (B) Liver function Child-Pugh score of Class A, or Class B with a score of 7 or below (including 7); (C) A single solid tumor with a diameter of ≥6.5 cm; three or more lesions, among which at least one tumor has a diameter \>4.5 cm or the sum of the diameters is ≥8 cm; invasion of major blood vessels regardless of tumor size and number. Exclusion Criteria: * (A) Presence of distant metastasis outside the liver; (B) General performance status score (PS score) greater than 2 points.

Outcomes

Primary Outcomes

Downstagingoutcomes

Successful downstaging is defined by meeting the UCSF criteria after downstaging; no invasion of the main trunk of the portal vein or the main trunk of the hepatic vein; and no lymph node invasion. The evaluation criteria used for interpretation are the mRECIST (modified Response Evaluation Criteria in Solid Tumors) standards.

Time frame: 3 months after downstaging

Data from ClinicalTrials.gov

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