Comparative Effectiveness of Computed Tomography Versus Ultrasound-Guided Percutaneous Radiofrequency Ablation Among Medicare Patients 65 Years of Age or Older With Hepatocellular Carcinoma [Editor's Choice]



For patients with hepatocellular carcinoma (HCC) not eligible for surgical resection, radiofrequency ablation (RFA) is a promising technique that reduces the risk of disease progression.


To evaluate whether the trend of image guidance for RFA is moving toward the more expensive computed tomography (CT) technology and to determine the clinical benefits of CT guidance over the ultrasound (US) guidance.


A cohort of 463 patients was identified from the Surveillance, Epidemiology, and End Results and Medicare–linked database. The temporal trends in use of image guidance were assessed using the Cochrane–Armitage test. The associations between modality of image guidance and survival, complications, and costs were assessed using the Cox regression model, the logistic regression model, and the generalized linear model, respectively.


The use of CT-guided RFA increased sharply, from 20.7% in 2002 to 75.9% in 2011. Compared with CT-guided RFA, those who received US-guided RFA had comparable risk of periprocedural and delayed postprocedural complications. Stratified analyses by tumor size also showed no statistically significant difference. In adjusted survival analysis, no statistically significant difference was observed in overall and cancer-specific survival. Nevertheless, the cost of CT-guided RFA ($2847) was higher than that of US-guided RFA ($1862).


Despite its rapid adoption over time, CT-guided RFA incurred higher procedural costs than US-guided RFA but did not significantly improve postprocedural complications and survival. Echoing the American Board of Internal Medicine’s Choosing Wisely campaign and the American Society of Clinical Oncology’s Value of Cancer Care initiative, findings from our study call for critical evaluation of whether CT-guided RFA provides high-value care for patients with HCC.


Jinhai Huo Thomas A. Aloia Ying Xu Tong Han Chung Tommy Sheu Ya-Chen Tina Shih

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