The State Food and Drug Administration issued two clinical trial data submission requirements and registration review guidelines

On November 25, in order to strengthen the supervision and guidance of medical device product registration and further improve the quality of registration review, the State Food and Drug Administration issued the "Guidelines for the submission of medical device clinical trial data registration review requirements" and "In vitro diagnostic reagent clinical trial data submission requirements Guidelines for Registration Examination
.
Appendix 1 Guiding Principles for Registration and Review of Medical Device Clinical Trial Data Submission Requirements 1.
Foreword Medical device clinical trial data is one of the important supporting materials for evaluating the safety and effectiveness of medical devices
.
The standardized collection, sorting, analysis, and submission of medical device clinical trial data will help improve the quality of clinical trial implementation and management.
At the same time, it will help regulatory agencies to quickly and efficiently grasp the development of clinical trials and improve review efficiency
.
In order to guide registration applicants to submit clinical trial data and related materials in a standardized manner, so as to better carry out the work related to the review of clinical evaluation materials, this guideline is formulated
.
This guiding principle is formulated under the current system of regulations and standards and the current level of awareness.
With the continuous improvement of regulations and standards, as well as the continuous development of science and technology, the relevant content of this guiding principle will also be adjusted accordingly
.
2.
Scope of application This guideline applies to clinical trials of medical devices for the purpose of product registration, including clinical trials of medical devices carried out overseas, and does not apply to clinical trials of in vitro diagnostic reagents managed by medical devices
.
In vitro diagnostic equipment and software that are used in conjunction with in vitro diagnostic reagents to carry out clinical trials.
If the clinical test is used for the registration of the Clinical trial data submission requirements "Guidelines for Registration Review" to submit clinical trial data
.
This guideline only relates to the relevant content of clinical trial data submission, and does not involve relevant requirements for data management in the clinical trial process
.
3.
Basic Principles (1) Principle of Truth: The submitted clinical trial data should be consistent with the original clinical trial records
.
(2) The principle of traceability.
According to the data, explanatory documents and program codes submitted by the registration applicant, the analysis database and the statistical analysis results in the clinical trial report can be reproduced from the original database, and the formed analysis database and statistical analysis results are consistent with The content submitted by the registration applicant is consistent
.
(3) Principles of Readability The submitted database has a clear structure and detailed comments for easy review
.
Submitting clinical trial data in accordance with the relevant specifications of this guideline will help improve readability
.
4.
Relevant materials and descriptions of clinical trial data.
The relevant materials of clinical trial data for medical devices usually include the original database, analytical database, descriptive documents and program codes.
The following sets forth requirements for the specific format and content of each application document
.
Encourage registration applicants to submit data in accordance with the Clinical Data Interchange Standards Consortium (CDISC) standards
.
When providing Chinese translations for foreign materials, for the original and analytical data sets, at least the descriptive text in the data sets, variable labels, and observations (such as adverse event descriptions) should be translated
.
(1) Original database The original database submitted usually contains the original data collected directly from the case report form and external documents, and the missing data should not be filled in here
.
The original database usually consists of multiple different original data sets.
A single original data set is a collection of multiple variables under the same subject.
The observation values ​​of these variables together form the original data set.
For example, a demographic data set may include age, gender, body mass index (body mass index, BMI) and so on
.
The original databases involved in different clinical trials are not exactly the same
.
A single original data set should collect variables under the same subject.
Different subject variables are recommended to form the original data set.
For example, it is recommended that the knee joint Lysholm score and IKDC2000 score related variables form two original data sets.

.
Each data set needs to include the subject's unique identification variable to achieve the correlation of observations from different data sets of the same subject
.
If it involves data observed at different visit time points, the visit time variable should be used for identification
.
For example, for 3 months and 6 months after the operation of cardiac ultrasound-related observations, the visit time identification variables can be named Visit_3, Visit_6, etc.
to distinguish them
.
If two or more clinical trials are involved, the data set must include clinical research identification variables
.
If randomization is used in clinical trials, the original database should contain variables such as random numbers
.
The naming of data sets and variables should follow the principle of "readability".
It is recommended to refer to the English or Pinyin of the data sets or variables when naming them, so that the actual meaning of the naming can be easily associated with the name
.
For example, refer to "Medical History" to name the medical history data set "MH", refer to "Concomitant Medication" to name the combined medication data set "CM", the variable "gender" to "sex", and the variable "subject" The initials" are named "sub_abbr" and so on
.
(2) Analysis database The analysis database is a database formed using original data sets for statistical analysis, and used to generate statistical results in clinical trial reports (including statistical analysis of baseline, efficacy and safety indicators, etc.
)
.
The analysis database mainly includes the variable data in the original database and the data derived from the variable data in the original database according to the methods determined in advance in the clinical trial protocol and statistical analysis plan (if any) (such as missing value filling, scale sub-item score addition, etc.
) Data
.
The analysis database usually consists of a number of different data sets, which generally correspond to the statistical results in the clinical trial report
.
For example, the score statistics of the National Institutes of Health Stroke Scale (NIHSS) in the clinical trial report can correspond to a special analysis data set, which is specially created to generate the NIHSS score statistics, including the statistical results generated All variable data, other unrelated variable data are not included in the data set
.
In order to facilitate the re-examination of statistical analysis, the variables in the analysis data set should be traceable, and the variable structure should be clear.
Statistical analysis can be carried out without tedious data pre-processing
.
The analysis data set can be named based on the corresponding statistical results it produces.
For example, the data set that generates the comparison results of adverse events can be named "ADAE" (adverse event analysis data set)
.
It is recommended to add the prefix "AD" (analysis data) to the name of the analysis data set to identify the data set as an analysis data set
.
The naming of the analysis data set variables is the same as that of the original database
.
Note that different analyzes clearly sets (e.
g.
, full analysis set FAS, per protocol set (PPS) and safety analysis set SS, etc.
) identification variables, and forming a system variable (if any), such as serial number, time and the like generated during database
.
(3) Program code The code to be submitted mainly includes: the code used for the original database to generate the analysis database, the code for the analysis database to generate the statistical analysis result, etc.
The relevant code for adjusting the format or generating the form may not be submitted
.
The submitted code should conform to the usual programming format and programming specification, with a clear structure and easy to read
.
The program code should include sufficient comments to describe the purpose of different program codes and other content that needs to be explained to help reviewers better understand the code logic
.
If the submitted program code refers to a macro program, the corresponding macro program code shall be provided, and the software version and system environment of the program shall be specified.

.
(4) Explanatory documents 1.
Data explanatory documents Data explanatory documents are used to describe the content and structure of the original database and the analysis database, and help reviewers quickly understand the data sets, variables and their mutual structural relationships in the database, and are accurate Understand the content of the submitted data
.
It is recommended to use an Excel file to list the data sets, variables, variable types (such as character, numeric), labels, assignments and their corresponding relationships contained in the original database and the analysis database in the form of a table.
Please refer to Appendix 1 for details.
"Examples of Data Sets and Variable Relationship Lists"
.
In order to facilitate review, data sets and variables should have corresponding Chinese labels, and the label length should not be too long
.
If an external dictionary (such as MedDRA) is used, the name and version number of the external dictionary used should be specified
.
The description file of the analysis database needs to specify the generation rules of the derived variables, and the variables and calculation methods involved
.
For example, for the filling of missing values, the filling method should be clarified and the corresponding program code should be provided
.
It is recommended to list the program code files used to generate each analysis data set and the name of the original data set in the form of a table
.
2.
Program code use instruction file The program code use instruction file is used to explain the use method, system and software environment of the program code file, including whether to modify the code file and how to modify the program code
.
At the same time, the program code file and data set file name used to generate each statistical result chart are listed one by one in the form of a table
.
The registration applicant should explain the encoding used in the original data set and analysis data set (such as UTF-8, EUC-CN, etc.
) to avoid garbled codes in the submitted data set
.
3.
Annotated Case Report Form Compared with a blank CRF, annotated CRF adds annotated content, which reflects the corresponding relationship between the variables in the database and the collection of CRF information
.
For example, comment the variable name sex in the gender blank
.
Using the comment CRF, the reviewer can intuitively check the position of each variable in the CRF
.
There may be some redundant data collected in the CRF that is not related to the analysis of clinical trial results.
These data may not be included in the submitted database, but it should be clearly marked as "not submitted" on the comment CRF, and the reason should be stated
.
4.
Other explanatory documents In addition to the above explanatory documents, registration applicants are encouraged to submit other explanatory documents (such as overview documents, other special circumstances explanatory documents, etc.
) that help reviewers quickly understand the content and structure of the clinical trial database
.
V.
Form of submission The original database, analysis database, descriptive documents and program codes are placed in four folders respectively
.
It is recommended to use XPT for the original database and analysis database.
[XPT (XPORT) is a file format used for data exchange.
Commonly used statistical software usually has the function of creating files in XPT format
.
] For data transmission format submission, it is recommended that all the original data sets form an XPT file, and all the analysis data sets form an XPT file
.
It is recommended to use XPT version 5 (XPT V5 for short) or above as the data submission format
.
The data description file can be in PDF, Word, Excel and other file formats.
Among them, Excel files are recommended for variable dictionaries, and PDF files are recommended for annotated case report forms
.
It is recommended to use TXT file format for the program code
.
6.
Drafting Unit The Medical Device Technical Evaluation Center of the State Drug Administration
.
Appendix 2 Guiding Principles for Registration and Review of In-vitro Diagnostic Reagent Clinical Trial Data Submission Requirements I.
Preface The in-vitro diagnostic reagent clinical trial data is one of the important supporting materials for evaluating the safety and effectiveness of products
.
The standardized collection, sorting, analysis, and submission of clinical trial data will help improve the quality of clinical trial implementation and management, and at the same time help regulatory agencies to quickly and efficiently grasp the development of clinical trials and improve review efficiency
.
In order to guide registration applicants to submit in vitro diagnostic reagent clinical trial data and related materials in order to better carry out the relevant work of clinical trial data review, this guideline is formulated
.
This guiding principle is formulated under the current system of regulations and standards and the current level of awareness.
With the continuous improvement of regulations and standards, as well as the continuous development of science and technology, the relevant content of this guiding principle will also be adjusted accordingly
.
2.
Scope of application This guideline applies to clinical trials of in vitro diagnostic reagents carried out for the purpose of product registration, including clinical trials of in vitro diagnostic reagents carried out overseas
.
This guideline only relates to the relevant content of clinical trial data submission, and does not involve the relevant requirements of data management in the clinical trial process
.
3.
Basic principles (1) Principle of truth The submitted clinical trial data should be consistent with all original records in the clinical trial
.
(2) The traceability principle should be able to reproduce the statistical results in the analysis database and clinical trial reports from the original database based on the data, descriptive documents and program codes (if any) submitted by the registration applicant, and the analysis formed The database and statistical analysis results are consistent with the content submitted by the registration applicant
.
The clinical trial database submitted by the registration applicant should be traceable to the original trial record and case report form in the clinical trial, and the clinical background information should be traceable to the case-related information management system or original record of the clinical trial institution
.
The original test record may include the sample selection form, sample blinding form, test record form, etc.
If the declared product requires supporting equipment for testing, it should also include the electronic records on the supporting equipment
.
The above original test records are not required to be submitted and should be kept in a safe place for future reference
.
(3) The principle of comprehensive and readable data The submitted clinical trial data should be comprehensive, readable, and easy to count according to the characteristics of the declared product and the difference in clinical trial design
.
The database has a clear structure and detailed comments for easy review
.
4.
Requirements for the relevant content of the clinical trial database Generally speaking, the relevant content of the clinical trial database should include the relevant information of the subjects and the detection information of the clinical trial samples
.
Different types of clinical trial design should contain different data and information
.
According to product characteristics and product performance evaluation needs, in vitro diagnostic reagent clinical trials include different clinical trial design types.
According to the impact of the test results of in vitro diagnostic reagents on subjects during the clinical trial process, they are generally divided into observational studies and interventional studies.
Research
.
Among them, observational studies can be divided into cross-sectional studies and longitudinal studies according to different time points detected in clinical trials
.
Cross-sectional research is the most common design type for clinical trials of in vitro diagnostic reagents, and the requirements for the content of the clinical trial database are also the general requirements for the content of clinical trials of in vitro diagnostic reagents
.
For longitudinal studies and interventional studies, corresponding data should be supplemented on the basis of general requirements
.
(1) Data from cross-sectional studies The enrolled population and sample types in clinical trials should be consistent with the declared intended use of the declared product
.
Therefore, the data information should include relevant information about the subject, including clinical diagnosis background information, sample type, demographic information (gender, age, etc.
)
.
The clinical diagnosis background information includes clinical diagnosis results, related symptoms and signs, and diagnosis and treatment information (if necessary)
.
If subgroup statistics are needed in the statistical analysis of the declared product, information related to the division of subgroups should be included, such as information on different stages and different processes of the disease
.
The test information on clinical samples in clinical trials mainly includes: test results of in vitro diagnostic reagents, test results of comparison methods, etc.

.
For products whose test results are determined based on the determined positive judgment value, the data information should also include the detailed test values ​​(such as Ct value, S/CO value, etc.
) of the test in vitro diagnostic reagent and the comparison method
.
If nucleic acid detection products involve different detection channels, the detection value of each channel should be provided, including the detection value of the internal standard
.
Clinical trial data should be real and traceable data set should have a unique traceable identification of the sample number to the number of samples can be traced back to all the background information of the case, such as the number of cases, diagnosis and treatment information
.
If the clinical trial involves retesting, the corresponding data set should contain the initial test and retest data, and the reason for the retest should be noted
.
If there is other information that needs to be explained, you can add a column of "Remarks" and add the information to the "Remarks"
.
(2) Data from longitudinal research In addition to cross-sectional research, some products require longitudinal research.
For longitudinal research data, the data set should include the specific data of each case at each time point.
The data summary at each time point, the sampling time point and the test results should be listed correspondingly
.
For this kind of clinical trial design, where multiple samples come from the same subject, the de-identified subject number and sample number should be provided at the same time
.
(3) Data from interventional research For the data of interventional research, in addition to the above basic information, the data set also includes the clinical trial grouping of the case, specific diagnosis and treatment information, and the clinical evaluation endpoint of the case
.
V.
Form of submission The application materials related to clinical trial data of in vitro diagnostic reagents usually include the original database, analytical database, descriptive documents and program codes (if any).
The following sets forth requirements for the specific format and content of each application material
.
Encourage registration applicants to submit data in accordance with the Clinical Data Interchange Standards Consortium (CDISC) standards
.
It is recommended that the registration applicants comprehensively consider the advantages of the clinical trial electronic data capture system/data management system (Electronic data Capture System, EDC) in data collection and management, and gradually promote the use of the EDC system, especially for large amounts of data and high product risks.
High clinical trials
.
When providing Chinese translations for foreign materials, please note that for the original and analytical data sets, at least the descriptive texts in the data sets, variable labels, and observations should be translated
.
(1) Original database The original database usually contains the original data collected directly from the case report form and external documents, and should include all the cases and sample information of the clinical trial enrolled in accordance with the requirements of the plan.
The missing data in the original database should not be filled.

.
Cases eliminated according to the elimination criteria of the clinical trial protocol should also be included, and the reason for the elimination should be noted at the same time
.
For clinical trials with a large amount of data, the original database usually consists of multiple different original data sets
.
A single original data set is a collection of multiple variables under the same subject, and the observation values ​​of these variables together form the original data set
.
For example, demographic information may include de-identified data set of the subject number, age, sex, clinical diagnosis
.
The original databases involved in different clinical trials are not exactly the same
.
A single original data set should collect variables under the same subject
.
Each data set needs to include the subject's unique identification variable to achieve the correlation between the values ​​of different data sets of the same subject
.
If randomization is used in clinical trials, the original database should contain variables such as random numbers
.
The naming of data sets and variables should follow the principle of "readability".
It is recommended to refer to the English or pinyin of the data sets or variables when naming them.
The actual meaning of the naming can be easily associated with the name.

.
In the code data set is typically two-letter names, such as the subject demographic data set (DM), the detected data sample set (LB), a sample collection and processing data set (Cl), adverse events (ae) and the like
.
Name the variable "Sex", "Age" as "Age", "Subject Number" as "SUBJID", "Sample Number" as "SAMID", and "Clinical Diagnosis" as "DIAG" "Wait
.
(2) Analysis database The analysis database is a database formed by using the original data set for the convenience of statistical analysis, and is used to generate the statistical results in the clinical trial report
.
The analysis database mainly includes variable data in the original database and data derived from the variable data in the original database according to the method determined in advance in the clinical trial protocol or statistical analysis plan (if any)
.
The analysis database usually consists of multiple different data sets, and the formation of the data sets should correspond to the statistical results in the clinical trial report
.
When subgroup analysis is needed, different analysis data sets can be constructed for subgroup analysis
.
For quantitative detection reagents, samples with detection data within the linear range need to be included in quantitative correlation analysis, and then an analysis data set should be generated for all samples within the linear range
.
In order to facilitate the re-examination of statistical analysis, the variables in the analysis data set should be traceable, and the variable structure should be clear.
Statistical analysis can be carried out without tedious data pre-processing
.
The analysis data set can be named based on the corresponding statistical results it produces.
It is recommended to add the "AD" (analysis data) prefix to the analysis data set name to identify the data set as an analysis data set
.
(3) Explanatory documents 1.
Data explanatory documents Data explanatory documents are used to describe the content and structure of the original database and the analytical database.
It helps reviewers quickly understand the data sets, variables and their mutual structural relationships in the database, and are accurate Understand the content of the submitted data
.
It is recommended to use an Excel file to list the data sets, variables, variable types (such as character, numeric), labels, assignments and their corresponding relationships contained in the original database and the analysis database in the form of a table
.
In order to facilitate review, data sets and variables should have corresponding Chinese labels, and the label length should not be too long
.
If an external dictionary (such as MedDRA) is used, the name and version number of the external dictionary used should be specified
.
The description file of the analysis database needs to specify the generation rules of the derived variables, and the variables and calculation methods involved
.
If the registration applicant uses the program code to generate the analysis database, it is recommended to list the program code file and the original data set name used to generate each analysis data set in the form of a table
.
2.
Statistical analysis documentation The registration applicant should specify the process or calculation method from analyzing the database to the final generation of the statistical results in the clinical trial report
.
If the process of statistical analysis is directly implemented in Excel, the function formula used should be listed in the descriptive file
.
If a statistical tool is used for statistical analysis but the program code is not used, the statistical analysis steps can be explained in detail in the form of text and graphics, and the version number of the statistical tool used should be indicated
.
If the program code is used in statistical analysis, the method, system, and software environment of the program code file should be explained in the statistical analysis description file, including whether or not it needs to be modified when using the code file and how to modify the program code
.
At the same time, the program code file and data set file name used to generate each statistical result chart are listed one by one in the form of a table
.
The registration applicant should explain the encoding used in the original data set and analysis data set (such as UTF-8, EUC-CN, etc.
) to avoid garbled codes in the submitted data set
.
At the same time, the corresponding program code should be provided with reference to the following item (4)
.
3.
Annotate the case report form (if any) Compared with the blank CRF, the annotation CRF adds the annotation content, which reflects the corresponding relationship between the variables in the database and the information collected in the CRF table
.
For example, comment the variable name Sex in the gender blank
.
Using the comment CRF, the reviewer can visually check the position of each variable in the CRF table.
The CRF may collect some redundant data that has nothing to do with the analysis of clinical trial results.
These data may not be included in the submitted database, but should be in the comment The CRF is clearly marked as "not to submit" and the reasons are stated
.
4.
Other explanatory documents In addition to the above explanatory documents, registration applicants are encouraged to submit other explanatory documents (such as overview documents, other special circumstances explanatory documents, etc.
) that help reviewers quickly understand the content and structure of the clinical trial database
.
(4) Program code (if any) If the program code is used in database management or statistical analysis, the program code should be provided.
The code to be submitted mainly includes: the code used for the original database to generate the analysis database, and the analysis database to generate the statistical results.
Codes, etc.
, related codes used to adjust the format or generate forms do not need to be submitted
.
The submitted code should conform to the usual programming format and programming specification, with a clear structure and easy to read
.
The code describes the purpose of different program modules and other content that needs to be explained in the form of Chinese comments
.
If a macro program is quoted in the submitted code, you need to provide the corresponding macro program code and indicate the software version and system environment that can run the program
.
(5) Form requirements The original database, analysis database, descriptive documents and program code (if any) are placed in four folders respectively
.
The clinical trial database can be submitted in the form of Excel.
For example, if the EDC system is used for data collection and management, the original database and analysis database are recommended to be submitted in the XPT1 data transmission format.
It is recommended that all the original data sets form an XPT file, and all the analysis data sets form one.
XPT file
.
It is recommended to use XPT version 5 (XPT V5 for short) or above as the data submission format
.
Data description files and statistical analysis description files use PDF, Word, and Excel files.
Among them, Excel files are recommended for variable dictionaries, and PDF files are recommended for annotated case report forms
.
The program code recommends using TXT files
.
6.
Drafting Units Medical Device Technical Evaluation Center of the National Medical Products Administration