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COST-EFFECTIVENESS OF NAVIGATED RADIOFREQUENCY ABLATION FOR HEPATOCELLULAR CARCINOMA IN CHINA

Published online by Cambridge University Press:  16 February 2015

Yizhen Lai
Affiliation:
Harvard School of Public Health
Kai Li
Affiliation:
The Third Affiliated Hospital of Sun Yat-sen University.
Junbo Li
Affiliation:
Philips Research Asia
Sheena Xin Liu
Affiliation:
Philips Research North America, Briarcliff Manor xl2104@gmail.com
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Abstract

Objectives: Real-time virtual sonography (RVS) is a promising navigation technique for percutaneous radiofrequency ablation (RFA) treatment, especially in ablating nodules poorly visualized on conventional ultrasonography (US). However, its cost-effectiveness has not been established. The purpose of this study is to evaluate the cost-effectiveness of RVS navigated RFA (RVS-RFA) relative to US guided RFA (US-RFA) in patients with small hepatocellular carcinoma (HCC) in China, from the modified societal perspective.

Methods: A state-transition Markov model was created using TreeAge Pro™ 2012. The parameters used in the model, including natural history of HCC patients, procedure efficacy and related costs, were obtained from a systematic search of literature through PubMed, EMBASE, and Science Citation Index databases. The simulated cohort was patients with solitary, small HCC (<3 cm in diameter) and Child-Pugh class A or B, whose tumors are poorly visualized in B-mode US but clearly detectable by CT or MRI.

Results: In this cohort of difficult cases, RVS-RFA was a preferred strategy saving 2,467 CNY ($392) throughout the patient's life while gaining additional 1.4 QALYs compared with conventional US guidance. The results were sensitive to the efficacy of US-RFA and RVS-RFA including complete ablation rate and local recurrence rate, the median survival for patients with progressive HCC, the probability of performing RFA for recurrent HCC, and the cost of RVS navigation, disposable needle or hospitalization.

Conclusions: RVS-RFA is a dominant strategy for patients with small HCC unidentifiable in B-mode US, in terms of cost savings and QALYs gained, relative to the conventional US-guided method.

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Copyright © Cambridge University Press 2015 
Figure 0

Figure 1. A schematic diagram of the Markov decision model

Figure 1

Table 1. Estimated Values of the Variables Used in the Model

Figure 2

Table 2. Cost Parameter Estimation

Figure 3

Table 3. Results of Model Verification Simulation

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