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Multicenter Study
. 2018 Aug;42(8):2579-2591.
doi: 10.1007/s00268-018-4468-2.

Prognostic Prediction Models for Resection of Large Hepatocellular Carcinoma: A Korean Multicenter Study

Affiliations
Multicenter Study

Prognostic Prediction Models for Resection of Large Hepatocellular Carcinoma: A Korean Multicenter Study

Shin Hwang et al. World J Surg. 2018 Aug.

Abstract

Background: We developed a prognostic prediction model (PPM) using 4 factors for hepatic resection (HR) of large hepatic cellular carcinoma (HCC). Multiplication of α-fetoprotein (AFP), des-γ-carboxy prothrombin, and tumor volume (TV) (ADV score) is a surrogate marker for post-resection prognosis. This study intended to validate the predictive power of 4-factor PPM and to develop new ADV score-based PPM.

Methods: A total of 526 patients who underwent HR for solitary HCC ≥ 8 cm were selected from 9 Korean institutions between 2008 and 2014.

Results: Median tumor diameter and TV were 11.0 cm and 398 mL, respectively. Tumor recurrence and patient survival rates were 53.0 and 78.4% at 1 year and 70.2 and 49.3% at 5 years, respectively. Independent risk factors for both tumor recurrence and patient survival included AFP ≥ 100 ng/mL, hypermetabolic FDG-positron emission tomography (PET), microvascular invasion and satellite nodules, which comprised 4 factors of the PPM. Five subgroups based on the number of involved risk factors exhibited significant differences in tumor recurrence and patient survival. ADV score cutoff was set at 7log (ADV7log) after cluster prognostic analysis. Patient grouping according to combination of ADV7log and FDG-PET findings (ADV7log-PET) exhibited significant differences in tumor recurrence and patient survival, comparable to those of the 4-factor PPM.

Conclusions: Two PPMs using 4 risk factors and ADV7log-PET could reliably predict the risk of early HCC recurrence and long-term survival outcomes in patients who underwent HR for large HCC. We believe that these PPMs can guide surgical treatment for large HCCs from preoperative HR planning to post-resection follow-up.

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