Preliminary Discussion On Vaccine Clinical Trial Data Standardization And Network Project Management

ObjectiveThe use of the vaccine has greatly improved the health level of the modern people, the results of vaccine clinical trial decide whether the vaccine can promote application, in this case, standardizing the process of data management and statistical analysis is as crucial as standardizing the process of experiment and test to the development of vaccines. Manage this part of the project management in the whole study to standardize the process of data management and statistical analysis, from the beginning of the creation of variables to the end of the statistical analysis, all the information can be traced back and all the corresponding specifications and documentations have been preserved, on the basis of this, design the electronic project management system to meet the modern network era.MethodsBased on the standard of Clinical Data Interchange Standards Consortium (CDISC), the variables in the electronic Case Report Form (CRF) database are named according to Clinical Data Acquisition Standards Harmonization (CDASH). On the basis of CDASH and the list of variable names, CRF annotation (aCRF) is made. Analysis Dataset Model (ADaM) is used in statistical analysis of vaccine clinical trials to make standardized analysis dataset. Use the SAS software to write macro program to complete data management in the process of data processing. Based on Epidemiological Dynamic Data Collection platform (EDDC) which is developed by the Chinese Centre for Disease Control and Prevention, use its functions to set up the project management system for data management and statistical analysis of the vaccine clinical trial. The whole process of data management to statistical analysis is made according to the data management plan of vaccine clinical trial and then ported to the system. Use system administrator permissions to set different user different permissions, the network of the server terminal and the data saving function of the database to realize the network of the platform. After exported the data from the system and processed by SAS software, use SAS AF to establish human-computer interaction interface so that we can realize vaccine clinical trial progress query, all program is written in SAS software.ResultsBased on Epidemiological Dynamic Data Collection platform (EDDC) which is developed by the Chinese Centre for Disease Control and Prevention, use its functions to set up the project management system for data management and statistical analysis of the vaccine clinical trial. The whole process of data management to statistical analysis is made according to the data management plan of vaccine clinical trial and then ported to the system. Use system administrator permissions to set different user different permissions, the network of the server terminal and the data saving function of the database to realize the network of the platform. After exported the data from the system and processed by SAS software, use SAS AF to establish human-computer interaction interface so that we can realize vaccine clinical trial progress query, all program is written in SAS software.Vaccine clinical trial project management system can be accessed through the network and multi terminal was established. The system can save the file in the process of data management and statistical analysis for each clinical trial project and automatically record the operation time and the information of the person in charge. The System can set up account permissions and regularly automatic backup to YunFile. Use SAS AF to product the progress query plug-in, and in two ways to configure its:use the data which is exported by system and processed by SAS program or directly input the information into the plug-in.DiscussionApplication of CDICS in Chinese vaccine clinical trials is still at the starting stage, there is no clear description of the difference between vaccines and drugs in CDICS so the CDash variable name list needs to be expanded and improved in continuous practical applications. aCRF defines each variable’s name, format, length, unit and other necessary information to standardize data management and statistical analysis so that the clinical trials can be more transparent and standard, and the team work can be more efficient and accurate. The use of ADam make the original dataset connect to the data analysis.Clinical trials in China is relatively a long period, in this process, it is possible to carry out a number of different project, data management and statistical analysis are often processed by different people, so file classification save is particularly important. The project management system is necessary for different clinical trial projects, it can plan and deal with completed projects or projects that have not been completed, the system can continuous improve as the project proceeds. Multi-client and AF SAS progress query plug-in meet the requirements of the use of the system under various environments. But there are some problems too, the connection between off-line client and network terminal is one-way, data cannot be imported directly from the network to off-line client, further optimization is still needed.ConclusionUse CDash to collect data and variable naming, and define variable attributes can standardize data management and statistical analysis, the variable name list will extend with the project. Before running a data management program, SAS is used to converts non-standard variable name to standard. The mapping between the standardized CDash variable names and Study Data Tabulation Model (SDTM) and ADam analysis dataset is helpful for structure conversion, variable name can be understand even it is out of the dataset. ADam analysis datasets help to reproduce the results of statistical analysis, laying the foundation for the realization of statistical analysis automation. Network based project management system can effectively improve team efficiency and file preservation can save the records and files of all the projects, using search function can immediately find the required files. The setting of the permissions and automatic backup on the server guarantee the security of the data and the possible accidents. The system can be accessed as long as there is a network, which is conducive to the development of clinical trials.