Predictive factors for survival following stereotactic body radiotherapy for hepatocellular carcinoma with portal vein tumour thrombosis and construction of a nomogram

Abstract

Background We evaluated the treatment response and predictive factors for overall survival (OS) in patients with hepatocellular carcinoma (HCC) and portal vein tumour thrombosis (PVTT), who underwent stereotactic body radiotherapy (SBRT). Additionally, we developed and validated a personalised prediction model for patient survival. Methods Clinical information was retrospectively collected for 80 patients with HCC and PVTT, who were treated with SBRT at the Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital) between December 2015 and June 2019. A multivariate Cox proportional hazard regression model was used to identify the independent predictive factors for survival. Clinical factors were subsequently presented in a nomogram. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the accuracy of the model and the net clinical benefit. Results All patients completed the planned radiotherapy treatment, and the median follow-up duration was 10 months (range, 1–35.3 months). The median survival duration was 11.5 months, with 3-, 6-, and 12-month survival rates of 92.5, 74.5, and 47.5%, respectively. The multivariable Cox regression model indicated that the following were significant independent predictors of OS: clinical T stage (p = 0.001, hazard ratio [HR] = 3.085, 95% confidence interval [CI]: 1.514–6.286), cirrhosis (p = 0.014, HR = 2.988, 95% CI: 1.246–7.168), age (p = 0.005, HR = 1.043, 95% CI: 1.013–1.075), alpha-fetoprotein level (p = 0.022, HR = 1.000, 95% CI: 1.000–1.000), and haemoglobin level (p = 0.008, HR = 0.979, 95% CI: 0.963–0.994). A nomogram based on five independent risk factors and DCA demonstrated a favourable predictive accuracy of patient survival (AUC = 0.74, 95% CI: 0.63–0.85) and the clinical usefulness of the model. Conclusions SBRT is an effective treatment for patients with HCC with PVTT. Notably, clinical T stage, presence of cirrhosis, age, alpha-fetoprotein levels, and haemoglobin levels are independent prognostic factors for survival. The presented nomogram can be used to predict the survival of patients with HCC and PVTT, who underwent SBRT.

Prognostic Value of a CT Radiomics-Based Nomogram for the Overall Survival of Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

“…Te nomogram had the highest AUCs for 6-, 12-, and 18-month OS predictions among these models (Figure 4). Te AUC of our nomogram for 12-month OS was 0.79, which was better than the reported clinical risk factor-based nomogram for predicting 12-month OS (AUC 0.74) [28]. It is encouraging that our research is the frst to explore the application of radiomics for the prediction of post-SBRT OS in patients with nondistant metastatic BCLC-C HCC.…”

A web-based nomogram model for predicting the overall survival of hepatocellular carcinoma patients with external beam radiation therapy: A population study based on SEER database and a Chinese cohort

“…There is currently few complete and valid nomogram model to predict the prognosis of HCC patients treated with EBRT (12)(13)(14). Based on the sample data obtained from the SEER database, through univariate and multivariate analysis, a total of seven independent risk factors associated with prognosis were included: T stage, N stage, M stage, AFP status, tumor size, surgery, and chemotherapy; an intuitive prognostic prediction model was constructed, internal and external validation cohorts verified its accuracy.…”

“…In recent years, nomogram has been widely used as a prediction method in oncology, which is convenient for clinicians to use for prognosis prediction and has played an important role in promoting personalized medicine (11). As far as we know so far, there are few studies that have developed nomograms to predict prognosis in HCC patients with EBRT, and these were small studies due to the small number of HCC patients treated with EBRT (12)(13)(14). For the first time, based on the SEER database and a Chinese cohort, we established and validated such a nomogram to predict OS in HCC patients treated with EBRT.…”

The α-RECIST (RECIST 1.1 Combined With Alpha Fetoprotein): A Novel Tool for Identifying Tumor Response of Conversion-Radiotherapy for Unresectable Hepatocellular Carcinoma Before Hepatectomy

“…Since proposed in 2009 ( 25 ), mRECIST has been widely utilized in response evaluation of HCC after various treatment, including chemotherapy, targeted therapy, and immunotherapy ( 26 – 28 ). Currently, mRECIST has also been used in several clinical trials for tumor response in HCC treated with radiation ( 29 – 31 ). In our study, mRECIST failed to identify responders from non-responders with RFS benefit ( p = 0.201).…”