Title:Prediction Model and Nomogram of Early Recurrence of Hepatocellular
Carcinoma after Ultrasound-guided Microwave Ablation
Volume: 20
Author(s): Xinyao Wang, Dongyue Gu, Haiying Qin, Xiao Lu, Jingxi Hu, Huan Zhang, Xiaoqi Wan and Guangbin He*
Affiliation:
- Department of Ultrasound Diagnosis, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
Keywords:
Hepatocellular carcinoma, Microwave ablation, Early recurrence, Prediction model, Nomogram, Patients.
Abstract:
Background:
Ultrasound-guided microwave ablation (MWA) is recommended as a first-line treatment for early liver cancer due to its minimally invasive,
efficient, and cost-effective nature. It utilizes microwave radiation to heat and destroy tumor cells as a local thermal therapy and offers the benefits
of being minimally invasive, repeatable, and applicable to tumors of various sizes and locations. However, despite the efficacy of MWA, early
recurrence after treatment remains a challenge, particularly when it occurs within a year and has a significant impact on the prognosis of the
patient.
Objective:
This study aimed to identify the risk factors for early recurrence after MWA in patients with hepatocellular carcinoma (HCC) and establish a
predictive model.
Methods:
A total of 119 patients with hepatocellular carcinoma (HCC) treated in the Department of Ultrasound at the First Affiliated Hospital of the Air
Force Medical University from January, 2020 to April, 2022 were included in this study. Patients were categorized into the early recurrence group
and the non-early recurrence group based on whether recurrence occurred within 1 year. We conducted univariate analysis on 29 variables. A
predictive model was developed using multiple-factor logistic regression analysis, and a risk column graph was created.
Results:
A total of 28 patients were included in the early recurrence group, with an early recurrence rate of 23%. Tumor size ≥ 3cm, multiple tumors, AST >
35 U/L, low pathological differentiation, CD34 positive, Ki67 level, quantitative parameters mean transit time (mTT), and rise time (RT) were
confirmed as risk factors affecting early recurrence after ablation (P < 0.05). Furthermore, the model constructed based on these 5 predictive
factors, including tumor size, tumor number, pathological differentiation, CD34, and quantitative analysis parameter mTT, demonstrated good
predictive ability, with an AUC of 0.93 in the training set and 0.86 in the validation set.
Conclusion:
Our research indicates that the risk column graph can be utilized to predict the risk of early postoperative recurrence in patients after MWA. This
contributes to guiding personalized clinical treatment decisions and provides important references for improving the prognosis of patients.
