With innovation leading the development of the pharmaceutical industry, the number of drug clinical trial applications in China has been increasing year by year. In 2019 alone, the Center for Drug Evaluation of the National Medical Products Administration accepted 302 new drug clinical trial applications for category 1 innovative drugs, an increase of 26.4 compared to 2018 %, the research and development of many innovative drugs is at the key node of clinical trials. A few days ago, the Center for Drug Evaluation issued the "Guiding Principles for the Multiplicity of Drug Clinical Trials (Trial)", "Guiding Principles for Covariate Adjustment of Drug Clinical Trials", "Guiding Principles for Subgroup Analysis of Drug Clinical Trials (Trial)" and "Enrichment of Drug Clinical Trials" "Strategy and Design Guidelines (Trial)" and many other drug clinical trial guidelines, provide guidance for solving related problems in drug clinical trials.

Multiplicity issues are common in clinical trials, which refer to related issues that require more than one statistical inference (multiple testing) to make decisions on research conclusions in a complete study, such as comparisons between multiple groups. For confirmatory clinical trials, controlling the total type I error rate (FWER) at a reasonable level is the basic principle of statistics, and some multiplicity problems can lead to FWER expansion. The "Guiding Principles for Multiplicity of Drug Clinical Trials (Trial)" released this time mainly elaborates on common multiplicity problems and corresponding decision-making strategies, and introduces commonly used multiplicity adjustment methods and multiplicity analysis methods. Provide guidance on how to control FWER in the trial, and the general principles discussed are also applicable to other types of clinical research.

In randomized controlled clinical trials, there are other covariates in addition to the processing factors. If the trial design is not effectively controlled, or the statistical analysis is not properly adjusted, the test power may be reduced or the efficacy estimate may be generated. Bias. Demographic indicators, disease characteristics, sociological factors, and research centers may all be covariates. The main purpose of covariate correction in randomized controlled trials is to reduce redundant variations in the endpoint variables that are not related to treatment factors, so as to make the efficacy estimates more accurate . The "Guiding Principles for Covariate Correction in Drug Clinical Trials" released this time includes the consideration of covariates in trial design and the statistical analysis methods for correction of covariates. It aims to clarify the principles of handling covariates in evidence-based randomized controlled clinical trials. And for trial design, statistical analysis, and how to deal with and interpret important covariates in clinical trial reports. Patients participating in clinical trials are often affected by genetics, drug combination and other factors, which often have different degrees of heterogeneity, which may lead to The efficacy of the trial drug is different in different patients. Grouping patients with different characteristics in clinical trials is an intuitive way to explore the difference in efficacy between different patient populations, and it is also an indispensable part of benefit-risk assessment. The "Guiding Principles for Subgroup Analysis of Drug Clinical Trials (Trial)" explains the identification and definition of subgroups, types of subgroup analysis, general considerations, and subgroup analysis in confirmatory clinical trials. It aims to provide sponsors in clinical trials. In the trial, the subgroup analysis is correctly designed, implemented and evaluated to provide guiding suggestions.

The "Guiding Principles for Enrichment Strategy and Design of Drug Clinical Trials (Trial)" was also released this time. Enrichment refers to the prospective and precise definition of the target population that will maximize the benefit from the trial drug in clinical trials based on certain characteristics of the subjects. There are many enrichment strategies for selecting subjects in clinical trials. For example, you can select subjects who are not effective in the treatment of existing drugs and may be sensitive to test drugs. "Pharmaceutical Clinical Trial Enrichment Strategy and Design Guidelines (Trial)" explains the principles and methods of commonly used enrichment strategies and designs, their respective advantages and disadvantages, and explains the key issues that need to be considered from the perspective of practical application and supervision.