Development of machine learning-based clinical decision support system for hepatocellular carcinoma

被引:26
作者
Choi, Gwang Hyeon [1 ]
Yun, Jihye [2 ]
Choi, Jonggi [1 ]
Lee, Danbi [1 ]
Shim, Ju Hyun [1 ]
Lee, Han Chu [1 ]
Chung, Young-Hwa [1 ]
Lee, Yung Sang [1 ]
Park, Beomhee [2 ]
Kim, Namkug [2 ]
Kim, Kang Mo [1 ]
机构
[1] Univ Ulsan, Dept Gastroenterol, Asan Liver Ctr, Coll Med,Asan Med Ctr, 88 Olymp Ro 43-Gil, Seoul 05505, South Korea
[2] Univ Ulsan, Dept Convergence Med & Radiol, Asan Med Ctr, Coll Med, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
PREDICTION; MANAGEMENT;
D O I
10.1038/s41598-020-71796-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
There is a significant discrepancy between the actual choice for initial treatment option for hepatocellular carcinoma (HCC) and recommendations from the currently used BCLC staging system. We develop a machine learning-based clinical decision support system (CDSS) for recommending initial treatment option in HCC and predicting overall survival (OS). From hospital records of 1,021 consecutive patients with HCC treated at a single centre in Korea between January 2010 and October 2010, we collected information on 61 pretreatment variables, initial treatment, and survival status. Twenty pretreatment key variables were finally selected. We developed the CDSS from the derivation set (N=813) using random forest method and validated it in the validation set (N=208). Among the 1,021 patients (mean age: 56.9 years), 81.8% were male and 77.0% had positive hepatitis B BCLC stages 0, A, B, C, and D were observed in 13.4%, 26.0%, 18.0%, 36.6%, and 6.3% of patients, respectively. The six multi-step classifier model was developed for treatment decision in a hierarchical manner, and showed good performance with 81.0% of accuracy for radiofrequency ablation (RFA) or resection versus not, 88.4% for RFA versus resection, and 76.8% for TACE or not. We also developed seven survival prediction models for each treatment option. Our newly developed HCC-CDSS model showed good performance in terms of treatment recommendation and OS prediction and may be used as a guidance in deciding the initial treatment option for HCC.
引用
收藏
页数:10
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