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Development and evaluation of a predictive model for primary liver cancer recurrence after radiofrequency ablation
CHEN Zhiwei, WU Feixiang, CHEN Jie, WANG Xiaobo, TANG Zhihong, MENG Weida, WEI Meng, ZHANG Lianda, MAI Rongyun, WEI Tao, SU Hengfeng, LI Lequn, BAI Tao
2020, 12 (1):
63-69.
doi: 10.3969/j.issn.1674-5671.2020.01.11
Objective To develop and evaluate a nomogram model for predicting the disease-free survival rate of primary liver cancer(PLC) patients after radiofrequency ablation(RFA). Methods The clinical data of 213 PLC patients receiving RFA in Guangxi Medical University Cancer Hospital from June 2009 to May 2017 were analyzed retrospectively. The PLC patients were randomly divided into a training group(n=133) and a validation group(n=80). The Cox regression model was used to analyze the factors of recurrence after RFA,and a nomogram model was developed. The model agreement was evaluated by the calibration curve,the applicability of the model was validated by the Kaplan-Meier curve,and the accuracy of the model prediction was evaluated by the C-index. Results The 1-year,3-year,and 5-year disease-free survival rates in the training group were 65.25%,40.91%,and 26.99%,respectively,and those in the validation group were 66.29%,48.10%,and 24.59%,respectively. No significant difference in survival curves was found between the two groups(P=0.785). The Cox regression analysis showed that the key influential factors of disease-free survival rate included the tumor number(HR=1.921,95%CI:1.136-3.251),hepatitis C antibody positive(HR=4.545,95%CI:1.700-12.149),HBV-DNA≥102 IU/mL(HR=1.993,95%CI:1.209-3.284),and serum prealbumin(HR=0.996,95%CI:0.993-0.999). Based on the tumor number,HBV-DNA,serum prealbumin,and so on,a nomogram model was developed. The C-indexes of the training group and the validation group were 0.649(95%CI:0.588-0.710) and 0.641(95%CI:0.556-0.724),respectively,and the calibration curve fitted well with the predicted calibration curve in the calibration graph. The patients were divided into the high-risk group and low-risk group by the nomogram,the disease-free survival rate in the high-risk group was lower than that in the low-risk group(P<0.05). Conclusions The nomogram model based on the tumor number,HBV-DNA,and serum prealbumin can predict well the disease-free survival rate of liver cancer patients after RFA,providing guidance for patient adjuvant treatment.
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