Through summarizing the definition, concept, and development of patient registry, and also retrieving ClinicalTrials.gov, we introduce its application areas, application range, disease, research number. Based on the application situation, we present the challenges faced now and future development of direction.
Traditional Chinese Medicine (TCM) standardization is an important carrier for TCM inheriting and innovating. As an important content of TCM standardization system, TCM clinical practice guidelines' designation and revision play an important role for medical staff to regulate medical behavior, and improve the quality of health services. This paper expounds the significance and function of the TCM guidelines, analyzes the present situation, opportunities and challenges, and puts forward the strategies and suggestions to promote the development of evidence-based TCM guidelines.
Accurately assessing the risk of bias is a critical challenge in network meta-analysis (NMA). By integrating direct and indirect evidence, NMA enables the comparison of multiple interventions, but its outcomes are often influenced by bias risks, particularly the propagation of bias within complex evidence networks. This paper systematically reviews commonly used bias risk assessment tools in NMA, highlighting their applications, limitations, and challenges across interventional trials, observational studies, diagnostic tests, and animal experiments. Addressing the issues of tool misapplication, mixed usage, and the lack of comprehensive tools for overall bias assessment in NMA, we propose strategies such as simplifying tool operation, enhancing usability, and standardizing evaluation processes. Furthermore, advancements in artificial intelligence (AI) and large language models (LLMs) offer promising opportunities to streamline bias risk assessments and reduce human interference. The development of specialized tools and the integration of intelligent technologies will enhance the rigor and reliability of NMA studies, providing robust evidence to support medical research and clinical decision-making.
This paper explores the methodological characteristics and key considerations of umbrella trials. By allocating different treatment strategies based on patients' molecular features, umbrella trials significantly enhance screening efficiency and can quickly identify ineffective therapies. Through the analysis of patient allocation strategies, statistical model selection, and error control methods, we can better utilize this design to accelerate drug development and achieve more efficient personalized treatment. However, despite significant progress in methodology and practice, umbrella trials still face multiple challenges during implementation, including trial design, sample size calculation, patient recruitment, informed consent, and resource allocation. Addressing these challenges in the future will help further optimize the application of umbrella trials. This study aims to provide thoughts and inspirations for researchers conducting umbrella trials and promote the steady development of this field.