Open AccessDevelopment and validation of a clinicopathological‐based nomogram to predict seeding risk after percutaneous thermal ablation of primary liver carcinoma
Author(s) -
An Chao,
Huang Zhimei,
Ni Jiayan,
Zuo Mengxuan,
Jiang Yiquan,
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/cam4.3250
Subject(s) - nomogram , medicine , confidence interval , receiver operating characteristic , proportional hazards model , thermal ablation , percutaneous , multivariate analysis , multivariate statistics , ablation , surgery , statistics , mathematics
Abstract Objectives To develop a clinicopathological‐based nomogram to improve the prediction of the seeding risk of after percutaneous thermal ablation (PTA) in primary liver carcinoma (PLC). Methods A total of 2030 patients with PLC who underwent PTA were included between April 2009 and December 2018. The patients were grouped into a training dataset (n = 1024) and an external validation dataset (n = 1006). Baseline characteristics were collected to identify the risk factors of seeding after PTA. The multivariate Cox proportional hazards model based on the risk factors was used to develop the nomogram, which was used for assessment for its predictive accuracy using mainly the Harrell's C‐index and receiver operating characteristic curve (AUC). Results The median follow‐up time was 30.3 months (range, 3.2‐115.7 months). The seeding risk was 0.89% per tumor and 1.5% per patient in the training set. The nomogram was developed based on tumor size, subcapsular, α‐fetoprotein (AFP), and international normalized ratio (INR). The 1‐, 2‐, and 3‐year cumulative seeding rates were 0.1%, 0.7% and 1.2% in the low‐risk group, and 1.7%, 6.3% and 6.3% in the high‐risk group, respectively, showing significant statistical difference ( P < .001). The nomogram had good calibration and discriminatory abilities in the training set, with C‐indexes of 0.722 (95% confidence interval [CI]: 0.661, 0.883) and AUC of 0.850 (95% CI: 0.767, 0.934). External validation with 1000 bootstrapped sample sets showed a good C‐index of 0.706 (95% CI: 0.546, 0.866) and AUC of 0.736 (95% CI: 0. 646, 0.827). Conclusions The clinicopathological‐based nomogram could be used to quantify the probability of seeding risk after PTA in PLC.