Related Experiment Video
Updated: Jun 4, 2025
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
Published on: April 12, 2024
Alpha-fetoprotein-to-PIVKA-II ratio as a potential biomarker for hepatocellular carcinoma differentiation, imaging
Menene Nkonika Dieu-Merci1, Jihong Hu1, Xinyi Fang1
1Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Background:
Alpha-fetoprotein-to-PIVKA-II ratio (APR) may serve as a new marker to predict the grade of differentiation, imaging characteristics, and prognosis of hepatocellular carcinoma (HCC). This study aimed to demonstrate the prognostic significance of high APR for poorly differentiated HCC (PD-HCC), imaging characteristics and overall survival (OS) in patients after intra-arterial therapies.
Methods:
Receiver operating characteristic (ROC) curves were constructed and areas under the curve (AUCs) were calculated to evaluate the predictive ability of APR to discriminate subgroup(s) of HCC with good or poor prognosis. Kaplan-Meier survival analysis was performed to evaluate the effect of tumor differentiation and change in APR on overall patient survival.
Results:
The cut-off value of APR used in the diagnostic setting was 0.175. Almost all patients in the PD-HCC group (90.9%) had a high APR value, while 100% and 84.2% of well-differentiated and moderately differentiated HCC (WD-HCC and MD-HCC) patients, respectively, had a low APR value (P<0.001). APR had a high sensitivity (91%) and specificity (90%) in differentiating PD-HCCs from WD-HCCs/MD-HCCs (P<0.001). Patients with high APR tended to have large and multiple tumors, vascular invasion and high percentage signal ratio (PSR). OS was slightly shorter in the PD-HCC group and in the high (>0.175) APR group.
Conclusions:
This study showed that patients with high APR and those with PD-HCC had a worse prognosis, and APR could be an important non-invasive biomarker for predicting the degree of tumor differentiation, imaging characteristics and patient prognosis.
