Open AccessA novel nomogram to predict the local tumor progression after microwave ablation in patients with early‐stage hepatocellular carcinoma: A tool in prediction of successful ablation
Author(s) -
An Chao,
Wu Songsong,
Huang Zhimei,
Ni Jiayan,
Zuo Mengxuan,
Gu Yangkui,
Zhang Tianqi,
Huang Jinhua
Publication year - 2020
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.2606
Subject(s) - nomogram , medicine , hepatocellular carcinoma , microwave ablation , confidence interval , stage (stratigraphy) , proportional hazards model , milan criteria , oncology , ablation , multivariate analysis , tumor progression , radiology , nuclear medicine , cancer , liver transplantation , paleontology , transplantation , biology
Objectives To develop a nomogram for the local tumor progression (LTP) in patients with early‐stage hepatocellular carcinoma (HCC) after computed tomography‐guided percutaneous microwave ablation (CT‐PMWA) and to assess clinical‐pathologic risk factors for individual LTP estimation. Furthermore, we compared the prognostic predictive ability for LTP between the nomogram and the traditional staging systems. Methods This retrospective study was approved by the institutional review board. Five hundred and forty treatment‐naïve patients with HCC according to the Milan criteria, who subsequently underwent CT‐PMWA were reviewed from 2009 to 2019. Baseline characteristics were collected to identify the risk factors for the determination of LTP after CT‐PMWA. The multivariate Cox proportional‐hazards model based on significant prognostic factors of LTP was used to construct the nomogram, which was then assessed for its predictive accuracy using mainly the Harrell's C‐index and time‐dependent area under the curve (tAUC). Results After a median follow‐up time of 28.7 months, 6.5% (35/540) patients had LTP. The nomogram was developed based on the tumor size, tumor number, Child‐Turcotte‐Pugh (CTP) grade, platelet, and alanine aminotransferase (ALT). The nomogram had good calibration and discriminatory abilities in the training set, with C‐indexes of 0.799 (95% confidence interval (CI): 0.738, 0.860), and tAUCs of 0.844 (CI: 0.728, 0.895), that were greater than those of traditional staging systems. Internal validation with 1000 bootstrap resamples had a good C‐index of 0.735 (CI: 0.648, 0.816). Conclusions The nomogram model can be used to predict accurately LTP after CT‐PMWA for early‐stage HCC, as well as to assist physicians during the therapeutic decision‐making process.