This article briefly introduces the management of clinical trials of investigational new drugs, hospital-made preparations, post-marketing drugs and other types of clinical trials. The WHO International Clinical Trial Register Platform (WHO ICTRP), Chinese Clinical Trial Register (ChiCTR) and Chinese Clinical Trial Registration and Publishing Collaboration (ChiCTRPC) are also described. People conducting trials are advised to apply the basic philosophy of evidence-based medicine in their implementation, which is considered to be one of the guarantees of the validity of clinical trials.
Objective To compare the balance of simple randomization, stratified blocked randomization and minimization. Methods Monte Carlo technique was employed to simulate the treatment allocation of simple randomization, stratified blocked randomization and minimization respectively, then the balance of treatment allocation in each group and the balance for every prognostic factor were compared. Results The simulation demonstrated that minimization provides the best performance to ensure balance in the number of patients between groups and prognostic factors. Balance in prognostic factors achieved with stratified blocked randomization was similar to that achieved with simple randomization. Conclusion Minimization offers the best balance in the number of patients and prognostic factors between groups.
Objective To analyze the current research status, characteristics and development trends of traditional medicine-related clinical trials registration, and to provide ideas and directions for further development of traditional medicine clinical trials. Methods The International Traditional Medicine Clinical Trial Registry (ITMCTR) database was searched by computer from inception to June 30, 2024, with unlimited trial registration status, to collect all the clinical trials on traditional medicine, and analyze the basic information of the trials, the diseases studied and the interventions. Results A total of 4 349 clinical trials related to traditional medicine were included, with the number of registrations peaking in the second half of 2020, and showing a steady upward trend after 2023. The trial sponsors of the study covered 9 countries and a total of 34 provinces/autonomous regions/municipalities in China, led by Beijing, Shanghai, Guangdong, Sichuan, and Zhejiang provinces, accounting for 69.72% of the total. The financial support for the studies was dominated by local government funds in various provinces and cities, accounting for 29.66%. Disease types studied were mainly circulatory system diseases, musculoskeletal system or connective tissue diseases, and tumor diseases, accounting for 29.91% of the total. A total of 3 751 (86.3%) clinical trials were interventional studies, of which randomized parallel control was predominant, and 213 large-sample studies with a sample size of more than 1 000 cases were included. A total of 20 types of interventions were involved, of which 1 114 (29.86%) clinical trials utilized oral prescription of herbal medicine interventions. Conclusion Clinical trial enrollment in traditional medicine has increased overall, but with significant geographic unevenness. Oral herbal soup/granule intervention studies are the mainstream hotspots. It is recommended to strengthen international cooperation, enrich the types of interventions, refine the trial design, and raise the awareness of researchers about the registration of high-quality traditional medicine clinical trials.
The complete, transparent, and standardized reporting of the outcome of a clinical trial is a key factor in ensuring the practicality, reproducibility, and transparency of the trial, and reducing bias in selective reporting. The consolidated standards of reporting trials (CONSORT) 2010 statement provides normative guidelines for reporting clinical trials. In December 2022, JAMA released the guidelines for reporting outcomes in trial reports (CONSORT-Outcomes) 2022 extension, aiming to explain the entries related to trial outcomes, sample size, statistical methods, and auxiliary analysis in the CONSORT 2010 statement, to further improve the standards for outcome reporting in clinical trial reports. This article combines research examples to interpret the CONSORT-Outcomes 2022 extension, in order to provide normative references for domestic scholars to report clinical research results.
The calculation of sample size is a critical component in the design phase of clinical trials incorporating health economic evaluations. A reasonable sample size is essential to ensure the scientific validity and accuracy of trial results. This paper summarizes the sample size calculation methods in the frequentist framework based on two health economic evaluation indicators: incremental cost-effectiveness ratio (ICER) and net benefit and examines these methods in terms of their applicable conditions, advantages, and limitations. The ICER method derives the sample size calculation formula by computing the ratio of incremental cost to incremental effect, while the net benefit method determines the economic viability of interventions by calculating incremental net benefit, subsequently leading to the formulation of the sample size calculation. Furthermore, this paper briefly discusses other sample size calculation methods, such as the classical Bayesian approach and the value of information analysis, providing a reference for calculating sample size in clinical trials with integrated health economic evaluations.
Objective To introduce the use of Central Randomization System in clinical trials. Methods We discussed the application of Central Randomization System in clinical trials from object management, drug management and user management, and made a brief description of minimization method. Results Central Randomization Systems can guarantee the nnplementation of the scheme of randomization, and can be used in clinical trials with minimization. Conclusion Central Randomization Systems are feasible in clinical trials especially in traditional Chinese medicine and open clinical trials.
Controversy exists regarding the ethics of using placebo control groups in clinical trials when effective treatments exist. The debate was fueled by the announcement of the 5th revision of the Declaration of Helsinki (2000). This study reviews the history and scientific background surrounding the controversy and investigates the prevailing attitudes of Hong Kong researchers regarding this issue. The controversy has centered on a few issues. The first involves the methodological superiority of placebo-controlled trials in discerning treatment effects. Secondly, it is unclear if the treatment effects encompass absolute treatment effects (including placebo effects) or are confined to treatment-specific effects (excluding placebo effects). Thirdly, there are worries that subjects in the placebo group could be exposed to higher risk for developing serious adverse events. Fourthly, it is debated whether the standard of best available treatment should be a local one, or an international one. Preliminary research findings suggest that the opinions of the Hong Kong researchers seemed to be divided on the use of placebo control groups in clinical trials when effective treatment exists. Further researcher on the topic is therefore warranted, training and consensus meeting may be necessary to minimize the confusion related to this issue.
When there is a lack of head-to-head randomized controlled trials between two interventions of interest, indirect comparison methods can be employed to estimate their relative treatment effects. Matching-adjusted indirect comparison (MAIC) is a population-adjusted indirect comparison method that utilizes a weighting approach. Unanchored MAIC is particularly applicable in scenarios where a common control group between the two interventions is not available. This article introduces the background and mathematical theory of unanchored MAIC, along with a demonstration of the operational steps and interpretation of results through an application example.
Approximately 70 million people worldwide suffer from epilepsy, with about 9 million in China. About one-third of patients demonstrating resistance to traditional antiseizure medications (ASMs), Focal Cortical Stimulation (FCS) emerges as a novel neuromodulation therapy based on neural stimulation, showing potential in treating drug-resistant focal epilepsy. FCS reduces seizure frequency by diminishing abnormal excitability in cortical areas. Compared to traditional surgery, it carries lower risks and is particularly suited for patients whose epileptogenic foci are difficult to surgically localize. Its adjustability provides physicians with treatment flexibility, allowing them to tailor therapy based on patient conditions. Recent studies highlight the practical clinical application of FCS, underscoring its advantages in reducing the frequency of drug-resistant epilepsy seizures. The article concludes by exploring the future prospects of FCS, emphasizing the need for research in long-term efficacy assessment and patient adaptability, thus demonstrating its significant potential and direction for development in the field of epilepsy treatment.
