ObjectiveTo summarize the research progress of four mainstream drug-eluting beads (DEB) in transcathete arterial chemoembolization (TACE) for hepatocellular carcinoma in recent years.MethodThrough retrieving relevant literatures at home and abroad, the physicochemical properties, pharmacokinetics, effectiveness, and safety of four mainstream DEBs were reviewed.ResultsThe current mainstream DEBs on the market had the characteristics of high drug loading rate and sustained release of drugs, which could reduce the adverse reactions after the embolization to a certain extent. The safety and tolerance of patients receiving DEB-TACE were slightly higher than those receiving traditional TACE (c-TACE). There were no serious complications after the DEB-TACE, but the short-term and long-term efficacies between the two methods were not significantly different.ConclusionsAt present, most studies believe that the safety and tolerance of DEB are slightly higher than that of c-TACE, but whether the former is more effective than the latter is still controversial at home and abroad, and more high-quality multicenter randomized controlled trials are needed to confirm it.
Randomized controlled trials (RCTs) are considered the “gold standard” for evaluating the causal effects of interventions on outcome measures. However, due to high research costs and ethical constraints, conducting RCTs in clinical practice, especially in the surgical field, faces numerous challenges such as difficulties in subject recruitment, implementation of blinding, and standardization of interventions. In such cases, using real-world data to perform causal inference under the framework of target trial emulation (TTE), based on the principles of RCT design, helps to identify and reduce biases arising from design flaws in traditional observational studies, such as immortal time bias, confounding, selection bias, or collider bias. This approach can produce high-quality evidence comparable to that of RCTs, thereby enhancing the clinical guidance value of real-world data studies. However, TTE has limitations, such as the inability to completely eliminate confounding, high quality requirements for source data, and the current lack of reporting standards. Therefore, researchers should be fully aware of these limitations to avoid making incorrect causal inferences. This article intends to provide an overview of the TTE framework, implementation points, application scope, application cases, and advantages and disadvantages of the framework.