Abstract
This study attempted to validate the prognostic performance of the proposed Pre- and Post-TACE (transarterial chemoembolization)-Predict models, in comparison with other models for prognostication. One-hundred-and-eighty-seven patients with HCC who underwent TACE were recruited. Regarding overall survival (OS), the predictive performance of the Pre-TACE-Predict model (one-year integrated area under the curve (iAUC) 0.685 (95% confidence interval (CI) 0.593– 0.772)) was better than that of the Post-TACE-Predict model (iAUC 0.659 (95% CI 0.580–0.742)). However, there was no significant statistical difference between two models at any time point. For comparison between models using pre-treatment factors, the modified hepatoma arterial emboliza-tion prognostic (mHAP)-II model demonstrated significantly better predictive performance at one year (iAUC 0.767 (95% CI 0.683–0.847)) compared with Pre-TACE-Predict. For comparison between models using first TACE response, the SNACOR model was significantly more predictive at one year (iAUC 0.778 (95% CI 0.687–0.866) vs. 0.659 (95% CI 0.580–0.742), respectively) and three years (iAUC 0.707 (95% CI 0.646–0.770) vs. 0.624 (95% CI 0.564–0.688), respectively) than the Post-TACE- Predict model. mHAP-II and SNACOR may be preferred over the Pre- and Post-TACE-Predict mod-els, respectively, considering their similar or better performance and the ease of application.
Original language | English |
---|---|
Article number | 67 |
Journal | Cancers |
Volume | 14 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2022 Jan 1 |
Bibliographical note
Funding Information:Funding: This study was supported by Basic Science Research Program through the National Re‐ search Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2019R1A2C4070136). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
All Science Journal Classification (ASJC) codes
- Oncology
- Cancer Research