Abstract
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.
Highlights
There is a significant discrepancy between the actual choice for initial treatment option for hepatocellular carcinoma (HCC) and recommendations from the currently used Barcelona Clinic Liver Cancer (BCLC) staging system
Transplantation was performed in 4.5%, resection in 32.9%, radiofrequency ablation (RFA) or percutaneous ethanol injection therapy (PEIT) in 7.5%, transarterial chemoembolisation (TACE) in 31.5%, TACE combined with external beam radiotherapy (EBRT) in 6.6%, sorafenib treatment in 3.0%, supportive care in 10.1%, and other therapies in 3.8% of patients
Nine patients underwent resection combined with intraoperative RFA, nine underwent palliative resection, eight underwent EBRT to liver, six underwent TACE combined with sorafenib or cytotoxic chemotherapy, and four underwent intra-arterial cytotoxic chemotherapy
Summary
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. There is a significant discrepancy in the initial treatment choice for HCC between the recommendations from the BCLC system and real clinical p ractice[4,5] This is partially because treatment decision for HCC is highly multifactorial, in which physicians need to take into consideration the HCC stage, baseline liver function, and performance status. Other factors such as location and distribution of tumour, presence of intermediate nodule, comorbidities, socio-economic status, availability of potential living related-donors, and the invasiveness and feasibility of each treatment option play critical roles in determining the clinical outcomes of patients with HCC. We gathered a team of well experienced hepatologists and AI scientists at our centre and developed a CDSS algorithm that can recommend optimal initial treatment for patients with HCC and predict the overall survival (OS) of patients after treatment, based on our centre’s experiences
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