Objective To systematically review the effectiveness of endoscopic dacryocystorhinostomy (En-DCR) with versus without Mitomycin C (MMC) for nasolacrimal obstruction. Methods Databases such as PubMed, EMbase, CENTRAL (Issue 12, 2012), VIP, WanFang Data, CBM and CNKI were electronically searched to collect the randomized controlled trials (RCTs) which investigated the comparison between En-DCR with and without MMC for nasolacrimal obstruction. The searched data was updated to December 31st, 2012. According to the inclusion and exclusion criteria, literature was screened, data were extracted, and the methodological quality of the included studies was also assessed. Then, meta-analysis was performed using RevMan 5.2.0 software and the quality of evidences was graded using GRADEpro 3.6 software. Results A total of 9 RCTs were included in the meta-analysis. The results of meta-analysis showed that, the recovery rate in the MMC group was significantly elevated (RR=1.13, 95%CI 1.04 to 1.22, P=0.003), the area of ostium in the MMC group was bigger at 1, 6 and 12 months than in the control group, postoperatively (MD=6.68 mm2, 95% 5.43 to 7.94, Plt;0.000 01; MD=11.61 mm2, 95%CI 4.67 to 18.55, P=0.001; MD=15.65 mm2, 95%CI 2.95 to 28.34, P=0.02), respectively, but the area of ostium in the MMC group at the third month was bigger than that in the control group (MD=8.20 mm2, 95%CI –6.67 to 23.08, P=0.28). The operative time was significantly prolonged in the MMC group (MD=10.1 min, 95%CI 8.00 to 12.20, Plt;0.000 01). Conclusion En-DCR combined with MMC could improve the recovery rate and prevent the over shrinkage of ostium area effectively due to nasolacrimal obstruction.
Randomization was the basis for the design and conduct of clinical trials. However, the traditional randomized controlled trials (RCTs) were often randomized in a fixed manner with unbalanced potential covariates, which spured researchers to develop a more flexible and practical randomization method. Thus, the adaptive randomization emerged as the time needed. In this paper, the application of adaptive randomization in clinical trials was introduced, and its key points of implementation, advantages and disadvantages were summarized. The development space of the adaptive randomization in clinical applications was also discussed, and it provided evidence for the development of the drug clinical trials in China.
The modern clinical research evaluation systems have increasingly emphasized the evaluation of individual patients' clinical characteristics, diagnosis and treatment plans, and complex intervention measures. Traditional randomized controlled trials evaluate fixed interventions and non-adaptive treatment plans, which cannot meet the needs of evaluating adaptive interventions. This has made researchers more inclined to explore an individualized and adaptive clinical trial design, and sequential multiple assignment randomized trial (SMART) has emerged as needed. This article introduces the principles, key elements, and implementation points of SMART design, further explores the limitations of the mismatch between traditional Chinese medicine clinical trial design and syndrome differentiation treatment, and proposes that SMART design can meet the needs of traditional Chinese medicine clinical trials to inspire researchers in designing their plans.
In recent years, investment in new drug development in China has surged; however, challenges such as difficulties in efficacy validation, high failure rates, and lengthy, costly clinical trials have been faced. The traditional model is insufficient for addressing these issues, necessitating innovation. Adaptive design (AD), particularly sequential multiple assignment randomized trials (SMART), has emerged as a flexible and efficient new pathway for drug development. This study focused on the two-stage design of SMART, analyzed its principles, and contrasted it with randomized controlled trials, group sequential designs, and crossover designs. The advantages of SMART are highlighted in terms of its precision in evaluating treatment strategies, minimizing sample waste, and enhancing the exploration of complex treatment pathways. Through case analyses, we demonstrated that SMART significantly improved clinical trial efficiency and the quality of treatment decisions, representing an innovative solution to the challenges of new drug development. This study aims to provide strategic references for clinical researchers and promote the adoption of adaptive designs in China, facilitating the efficient advancement of new drug development.
Response-adaptive randomization (RAR) dynamically adjusts the probability of assigning patients to different groups, optimizing treatment efficacy and participant welfare. It is particularly suitable for clinical studies involving multiple interventions or dose-finding and seamless phase II/III trials. This paper systematically introduces the concept, principles, and types of RAR, as well as its application in clinical trials (including traditional Chinese medicine research). It also provides R implementation code, offering researchers practical tools aimed at promoting the adoption of RAR in clinical practice.
The 14th Five-Year Plan for National Health explicitly proposes elevating the comprehensive prevention and control strategy for chronic diseases to a national strategy, aiming to address the growing demand for long-term management and individualized treatment of chronic diseases. In this context, the adaptive treatment strategy (ATS), as an innovative treatment model, offers new ideas and methods for the management and treatment of chronic diseases through its flexible, personalized, and scientific characteristics. To construct ATS, the sequential multiple assignment randomized trial (SMART) has emerged as a research method for multi-stage randomized controlled trials. The SMART design has been widely used in international clinical research, but there is a lack of systematic reports and studies in China. This paper first introduces the basic principles of ATS and SMART design, and then focuses on two key elements of the SMART design: re-randomization and intermediate outcomes. Based on these two elements, four major types of SMART designs are summarized, including: (1) SMART designs in which the intermediate outcome corresponds to a single re-randomization scheme (the classical type), (2) SMART designs in which no intermediate outcome is embedded, (3) SMART designs in which the intermediate outcome corresponds to a different re-randomization scheme, and (4) SMART designs in which the intermediate outcome and the previous interventions jointly determine the re-randomization. These different types of SMART designs are suited for solving different types of scientific problems. Using specific examples, this paper also analyzes the conditions under which SMART designs are applicable in clinical trials and predicts that the mainstream analysis methods for SMART designs in the future will combine frequentist statistics and Bayesian statistics. It is expected that the introduction and analysis in this paper will provide valuable references for researchers and promote the widespread application and innovative development of SMART design in the field of chronic disease prevention, control, and treatment strategies in China.