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Tumor burden with AFP improves survival prediction for TACE-treated patients with HCC: An international observational study

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dc.contributor.author김승업-
dc.date.accessioned2025-02-03T09:27:17Z-
dc.date.available2025-02-03T09:27:17Z-
dc.date.issued2025-01-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/202481-
dc.description.abstractBackground & aims: Current prognostic models for patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) are not extensively validated and widely accepted. We aimed to develop and validate a continuous model incorporating tumor burden and biology for individual survival prediction and risk stratification. Methods: Overall, 4,377 treatment-naive candidates for whom TACE was recommended, from 39 centers in five countries, were enrolled and divided into training, internal validation, and two external validation datasets. The novel model was developed using a Cox multivariable regression analysis and compared with our original 6-and-12 model (the largest tumor size [ts, centimetres] + tumor number [tn]) and other available models in terms of predictive accuracy. Results: The proposed model, named the '6-and-12 model 2.0', was generated as 'ts + tn + 1.5×log10 alpha-fetoprotein (AFP)', showed good discrimination (C-index 0.674) and calibration (Hosmer-Lemeshow test p = 0.147), and outperformed current existing models. An easy-to-use stratification was proposed according to the different AFP levels (≤100, 100-400, 400-2,000, 2,000-10,000, 10,000-40,000, and >40,000 ng/ml) along with the corresponding tumor burden cutoffs (8/14, 7/13, 6/12, 5/11, 4/10, and any tumor burden); that is, if the AFP level was 400-2,000 ng/ml, the stratification should be low-(≤6)/intermediate-(6-12)/high-risk (>12) strata. Hence, it could divide the patients into three distinct risk categories with a median overall survival of 45.0 (95% CI, 40.1-49.9), 30.0 (95% CI, 26.1-33.9), and 15.4 (95% CI, 13.4-17.4) months (p <0.001) from low-risk to high-risk strata, respectively. These findings were confirmed in validation and subgroup analyses. Conclusions: The 6-and-12 model 2.0 significantly improved individual outcome predictions and better stratified the candidates recommended for TACE; thus, this model could be used in both clinical practice and trial design. Impact and implications: In this international multicentre study, we developed and internally and externally validated a novel outcome prediction model for candidates with HCC who would be ideal for TACE. The model, called the 6-and-12 model 2.0, was based on 4,377 patients from 39 centers in five countries. The model offers individualized outcome prediction, outperforming the original 6-and-12 model score and other existing metrics across all datasets and subsets. Based on different levels of alpha-fetoprotein (AFP) and corresponding cut-offs of tumor burden, patients could be stratified into three risk strata with significantly different survival prognoses, which could provide a referential framework to control study heterogeneity and define the target population in future trial designs.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherElsevier B.V.-
dc.relation.isPartOfJHEP REPORTS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleTumor burden with AFP improves survival prediction for TACE-treated patients with HCC: An international observational study-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorDongdong Xia-
dc.contributor.googleauthorWei Bai-
dc.contributor.googleauthorQiuhe Wang-
dc.contributor.googleauthorJin Wook Chung-
dc.contributor.googleauthorXavier Adhoute-
dc.contributor.googleauthorRoman Kloeckner-
dc.contributor.googleauthorHui Zhang-
dc.contributor.googleauthorYong Zeng-
dc.contributor.googleauthorPimsiri Sripongpun-
dc.contributor.googleauthorChunhui Nie-
dc.contributor.googleauthorSeung Up Kim-
dc.contributor.googleauthorMing Huang-
dc.contributor.googleauthorWenhao Hu-
dc.contributor.googleauthorXiangchun Ding-
dc.contributor.googleauthorGuowen Yin-
dc.contributor.googleauthorHailiang Li-
dc.contributor.googleauthorHui Zhao-
dc.contributor.googleauthorJean-Pierre Bronowicki-
dc.contributor.googleauthorJing Li-
dc.contributor.googleauthorJiaping Li-
dc.contributor.googleauthorXiaoli Zhu-
dc.contributor.googleauthorJianbing Wu-
dc.contributor.googleauthorChunqing Zhang-
dc.contributor.googleauthorWeidong Gong-
dc.contributor.googleauthorZixiang Li-
dc.contributor.googleauthorZhengyu Lin-
dc.contributor.googleauthorTao Xu-
dc.contributor.googleauthorTao Yin-
dc.contributor.googleauthorRodolphe Anty-
dc.contributor.googleauthorJinlong Song-
dc.contributor.googleauthorHaibin Shi-
dc.contributor.googleauthorGuoliang Shao-
dc.contributor.googleauthorWeixin Ren-
dc.contributor.googleauthorYongjin Zhang-
dc.contributor.googleauthorShufa Yang-
dc.contributor.googleauthorYanbo Zheng-
dc.contributor.googleauthorJian Xu-
dc.contributor.googleauthorWenhui Wang-
dc.contributor.googleauthorXu Zhu-
dc.contributor.googleauthorYing Fu-
dc.contributor.googleauthorChang Liu-
dc.contributor.googleauthorApichat Kaewdech-
dc.contributor.googleauthorRong Ding-
dc.contributor.googleauthorJie Zheng-
dc.contributor.googleauthorShuaiwei Liu-
dc.contributor.googleauthorHui Yu-
dc.contributor.googleauthorLin Zheng-
dc.contributor.googleauthorNan You-
dc.contributor.googleauthorWenzhe Fan-
dc.contributor.googleauthorShuai Zhang-
dc.contributor.googleauthorLong Feng-
dc.contributor.googleauthorGuangchuan Wang-
dc.contributor.googleauthorPeng Zhang 26-
dc.contributor.googleauthorXueda Li-
dc.contributor.googleauthorJian Chen-
dc.contributor.googleauthorFeng Zhang-
dc.contributor.googleauthorWenbo Shao-
dc.contributor.googleauthorWeizhong Zhou-
dc.contributor.googleauthorHui Zeng-
dc.contributor.googleauthorGengfei Cao-
dc.contributor.googleauthorWukui Huang-
dc.contributor.googleauthorWenjin Jiang-
dc.contributor.googleauthorWen Zhang-
dc.contributor.googleauthorLei Li-
dc.contributor.googleauthorAiwei Feng-
dc.contributor.googleauthorEnxin Wang-
dc.contributor.googleauthorZhexuan Wang-
dc.contributor.googleauthorDandan Han-
dc.contributor.googleauthorYong Lv-
dc.contributor.googleauthorJun Sun-
dc.contributor.googleauthorBincheng Ren-
dc.contributor.googleauthorLinying Xia-
dc.contributor.googleauthorXiaomei Li-
dc.contributor.googleauthorJie Yuan-
dc.contributor.googleauthorZhengyu Wang-
dc.contributor.googleauthorBohan Luo-
dc.contributor.googleauthorKai Li-
dc.contributor.googleauthorWengang Guo-
dc.contributor.googleauthorZhanxin Yin-
dc.contributor.googleauthorYan Zhao-
dc.contributor.googleauthorJielai Xia-
dc.contributor.googleauthorDaiming Fan-
dc.contributor.googleauthorKaichun Wu-
dc.contributor.googleauthorDominik Bettinger-
dc.contributor.googleauthorArndt Vogel-
dc.contributor.googleauthorGuohong Han-
dc.contributor.googleauthorChina HCC-TACE study group-
dc.identifier.doi10.1016/j.jhepr.2024.101216-
dc.contributor.localIdA00654-
dc.relation.journalcodeJ04267-
dc.identifier.eissn2589-5559-
dc.identifier.pmid39758510-
dc.subject.keywordAlpha-fetoprotein-
dc.subject.keywordHepatocellular carcinoma-
dc.subject.keywordRisk stratification-
dc.subject.keywordTransarterial chemoembolization-
dc.subject.keywordTumor burden-
dc.contributor.alternativeNameKim, Seung Up-
dc.contributor.affiliatedAuthor김승업-
dc.citation.volume7-
dc.citation.number1-
dc.citation.startPage101216-
dc.identifier.bibliographicCitationJHEP REPORTS, Vol.7(1) : 101216, 2025-01-
dc.identifier.rimsid87997-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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