ObjectiveTo investigate the domestic and abroad hypertension-related clinical trial registration and to analyze the registration of hypertension-related clinical researches in China.MethodsUsing hypertension as the keyword, we searched ClinicalTrials.gov and Chinese Clinical Trial Registry (ChiCTR) from January 2008 to December 2018. We analyzed the collected data on the distribution of registered clinical researches, annual trends, sample sizes, trial progress, research types, study designs, blind methods, clinical stages, the number of participating institutions, the leading institutions, etc.ResultsThe total number of registered hypertension-related clinical trails was 4 991 all over the world, and 551 items were conducted in China. Most of the sample sizes of Chinese hypertension-related clinical trials were 100 to 999. The main types of trials were interventional studies (393 items, 71.32%), followed by observational studies (126 items, 22.87%). Randomized parallel control studies (300 items, 76.34%) were the key component of interventional studies, while cohort studies (61 items, 48.41%) were the chief component of observational studies. The main stages of clinical trials were stage Ⅲ (80 items) and stage Ⅳ (122 items). There were 369 domestic single-center clinical trials (66.97%), 89 domestic multi-center clinical trials (16.15%), and 93 international multi-center clinical trials (16.88%). Among the 93 international multi-center trials of hypertension, only 25 were led by China.ConclusionsThe number of Chinese hypertension-related clinical trial registrations increased year by year and then decreased slightly, but the amount of registrations is limited. The quantity and scale of multicenter clinical studies were not as good as America. China should strengthen the awareness of clinical research registration, strengthen the publicity and supervision of the registration of clinical researches by the department of science and management, improve the number of clinical trial registrations, make Chinese clinical researches more transparent, and strive to lead more international multi-center clinical trials.
Trial sequential analysis (TSA) could be performed in both TSA software and Stata software. The implementation process of TSA in Stata needs the command of "metacumbounds" of Stata combines with the packages of "foreign" and "ldbounds" of R software. This paper briefly introduces how to implement TSA using Stata software.
Objective To evaluate the quality of the registration information for trials sponsored by China registered in the WHO International Clinical Trial Registration Platform (ICTRP) primary registries or other registries that meet the requirements of the International Committee Medical Journal Editor (ICMJE). Methods We assessed the registration information for trials registered in the 9 WHO primary registries and one other registry that met the requirements of ICJME as of 15 October 2008. We analyzed the trial registration data set in each registry and assessed the registration quality against the WHO Trial Registration Data Set (TRDS). We also evaluated the quality of the information in the Source(s) of Monetary or Material Support section, using a specially prepared scale. Results The entries in four registries met the 20 items of the WHO TRDS. These were the Chinese Clinical Trial Registration Center (ChiCR), Australian New Zealand Clinical Trials Registry (NZCTR), Clinical Trials Registry – India (CTRI), and Sri Lanka Clinical Trials Registry (SLCTR). Registration quality varied among the different registries. For example, using the Scale of TRDS, the NZCTR scoreda median of 19 points, ChiCTR (median = 18 points), ISRCTN.org (median = 17 points), and Clinical trials.org (median = 12 points). The data on monetary or material support for ChiCTR and ISRCTN.org were relatively complete and the score on our Scale for the Completeness of Funding Registration Quality ranged from ChiCTR (median = 7 points), ISRCTN.org (median = 6 points), NZCTR (median = 3 points) to clinicaltrials.gov (median = 2 points). Conclusion Further improvements are needed in both the quantity and quality of trial registration. This could be achieved by full completion of the 20 items of the WHO TRDS. Future research should assess ways to ensure the quality and scope of research registration and the role of mandatory registration of funded research.
ObjectiveTo systematically review the association between angiotension-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism and osteoarthritis (OA) by using meta-analysis and trial sequential analysis (TSA). MethodsThe PubMed, EMbase, CNKI, CBM, VIP, and WanFang Data were searched up to October 12th, 2016 for case-control or cohort studies on the correlation between ACE I/D polymorphism and OA risk. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then, meta-analysis and TSA analysis were performed using Stata 13.1 software and TSA v0.9 soft ware. ResultsA total of six case-control studies involving 1 165 OA patients and 1 029 controls were included. The results of meta-analysis showed that the ACE I/D was associated with OA risk (DD+DI vs. II: OR=1.72, 95%CI 1.02 to 2.90, P=0.04; DI vs. II: OR=1.65, 95%CI 1.06 to 2.56, P=0.03). Subgroup analysis of ethnicity showed that, in Caucasians, the ACE I/D was associated with OA risk (DD vs. DI+II: OR=2.10, 95%CI 1.54 to 2.85, P<0.01; DD+DI vs. II: OR=3.11, 95%CI 2.20 to 4.39, P<0.01; DD vs. II: OR=4.01, 95%CI 2.68 to 6.00, P<0.01; DI vs. II: OR=2.65, 95%CI 1.06 to 2.56, P<0.01; D vs. I: OR=2.11, 95%CI 1.72 to 2.58, P=0.73). And TSA showed that all of the cumulative Z-curve strode the conventional and TSA threshold value which suggested the result of the association between ACE I/D polymorphism and OA in Caucasians was very reliable. However, the association did not exist in Asians (DD vs. DI+II: OR=0.80, 95%CI 0.60 to 1.07, P=0.13; DD+DI vs. II: OR=1.08, 95%CI 0.87 to 1.35, P=0.49; DD vs. II: OR=0.86, 95%CI 0.62 to 1.20, P=0.38; DI vs. II: OR=1.18, 95%CI 0.93 to 1.50, P=0.19; D vs. I: OR=0.93, 95%CI 0.83 to 1.14, P=0.73). And the results of TSA displayed that all of the cumulative Z-curve did not strode both TSA threshold value and required information size line excepting for DD vs. DI+II genetic model which suggested that the sample-size in Asians was insufficient. ConclusionsThe ACE D allele maybe a risk factor for OA in Caucasians. However, the association between ACE I/D polymorphism and OA risk in Asians still need more studies to prove.
In 2007, the findings from clinical trials on stroke treatment have been both encouraging and disappointing. In order to interpret the challenges and opportunity in evidence-based stroke practice, we reviewed several major clinical trials in stroke that were published last year. It revealed that we should strengthen the evidence base for acute stroke care by conducting more high-quality randomized controlled trials and by increasing the energy, resources and manpower available for these trials.
Trial sequential analysis (TSA) can identify inclusive results of apparently conclusive of meta-analyses by providing require information size and monitoring boundary. Certain methods of calculating information size are existed. Our objective was to give a brief introduction of four methods to help readers to better perform TSA in making meta-analyses.
The sample size of a meta-analysis should not be less than a single randomized controlled trial. Trial sequential analysis (TSA) can provide required information size and monitoring boundary to justify the conclusion of meta-analysis. However, the TSA software is only suitable for binary and continuous data, and it cannot analyze the time-to-event data. This paper aimed to introduce how to analyze the time-to-event data using TSA approach.
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.
Based on evidence-based medicine (EBM) and from the viewpoint of providing scientific evidence for clinical application, we found that Traditional Chinese Medicine (TCM) was short of adequate evidence to support its therapeutic effects due to lack of high quality clinical research. Data management plays a very important role in clinical research. Lack of adequate data management may lead to low quality clinical research. Thus, it is of great importance to establish a set of standards for data management so as to improve the quality of clinical research. Based on the real practice in Myocardial Infarction Secondary Prevention Study in TCM (MISPS-TCM), this article introduces methods on data audit in clinical trials of TCM.
The quality of reporting of randomized clinical trials could be significantly improved by the application of CONSORT （Consolidated Standards of Reporting Trials） statement. We compared and analyzed the difference of acceptance of CONSORT statement between Chinese medical journals and Western medical journals, and proposed to disseminate and apply CONSORT statement to improve the quality of reporting of randomized clinical trials and medical journals.