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MindMap Gallery Guiding Principles for Comprehensive Analysis of Effectiveness in Drug Clinical Research

Guiding Principles for Comprehensive Analysis of Effectiveness in Drug Clinical Research

The "Guiding Principles for Comprehensive Analysis of Effectiveness in Drug Clinical Research" is an important document issued by the Center for Drug Evaluation (CDE) of the State Drug Administration. It aims to guide sponsors in accordance with the International Conference on Harmonization of Technology for the Registration of Drugs for Human Use (ICH) M4E ( R2) Section 5.3.5.3 of Common Technical Document (CTD) Module 5 requires a comprehensive effectiveness analysis of drug clinical studies to demonstrate the effectiveness characteristics of the drug as comprehensively and systematically as possible.

Edited at 2024-11-22 11:30:47

Mason·Carter

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Guiding Principles for Comprehensive Analysis of Effectiveness in Drug Clinical Research

Mason·Carter

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Outline

Guiding Principles for Comprehensive Analysis of Effectiveness in Drug Clinical Research

several concepts

1. Drug registration submission information

1. Evidence of efficacy and safety from all individual clinical studies related to the drug

2. Research data from different sources related to the drug

1. nonclinical research

2. Research on drug-device combinations related to human factors

3. In vitro studies of drug activity

4. Exploratory and confirmatory clinical studies conducted nationally and internationally

5. clinical pharmacology research

1. dose-response relationship

2. drug interactions

3. Drug-disease interactions (e.g. effects of renally metabolized drugs on the kidneys)

4. Food effects, etc.

2. Comprehensive analysis of clinical research data

1. Comprehensive Security Analysis

1. Systematic analysis of all clinical safety study data of drugs

2. Describe overall security characteristics

3. Determine the risk statements that should be included in the drug package insert

2. Comprehensive analysis of effectiveness

1. Systematically analyze all clinical effectiveness research data of the drug to be applied for registration for the same indication.

1. completed research

2. Research terminated prematurely in accordance with a pre-specified research plan (Such as early termination due to the effectiveness results reaching preset conditions during the interim analysis)

3. ongoing research

4. Research that has been terminated but not completed

5. Research on historical legacy

6. A brief summary of key design information and effectiveness results for all clinical studies in the list (regardless of whether the effectiveness results are statistically significant)

2. Compare the strengths and weaknesses of different research data

3. Describe overall effectiveness characteristics

4. Explain why some important research data were not included in the analysis

3. Effectiveness comprehensive analysis content

1. Compare key design information and statistical analysis methods across all clinical studies and discuss their impact on effectiveness results

2. Compare and meta-analyze effectiveness results from all clinical studies

3. Compare and meta-analyze effectiveness results for subgroups of all clinical studies (if necessary)

4. Comprehensive analysis of data from clinical pharmacology studies that assess the relationship between exposure (dose or plasma concentration) and effects, combined with effectiveness results from clinical studies, to support dosage and use in drug package inserts

5. Compare, summarize and discuss drug long-term effectiveness, tolerability and discontinuation data presented in all clinical studies

4. meta-analysis

Combined analysis of individual- or group-level data from independent studies

Overview of individual clinical studies

1. Presentation content (key research information), description, comparison, discussion of research design elements

1. For individual clinical studies that are not included in the comprehensive analysis of effectiveness, the reasons should be explained.

2. Drug indications

3. Key entry criteria

Subject selection methods such as disease status, demographic characteristics, previous concomitant medication, enrichment strategy and design, placebo lead-in period, etc.

4. Study number, study status (such as ongoing or completed), study area, research purpose, study stage (such as Phase II or Phase III)

5. Type of comparison (e.g. superiority or non-inferiority)

Type of comparison, such as superiority, equivalence, or noninferiority designs, etc. When using a non-inferiority design, special explanation should be given as to whether the non-inferiority margin is reasonable and whether the constancy assumption is established.

6. Trial group, control type (such as placebo or active drug control)

1. Same period control

The experimental group and the control group are selected from the same research population and treated with drugs at the same time, such as placebo control, no drug/blank control, positive drug control and dose-effect control, etc. When using a positive drug control, the rationale for selecting the positive drug should be specifically explained.

2. external control

Historical controls, parallel controls, target value controls or synthetic controls outside the study population, etc.

3. multiple controls

Using both a placebo control and an active control, or several doses of a trial drug and several doses of an active control, in one study

7. Sample size (such as the preset and actual number of enrolled groups and the number of group allocations)

Sample size estimation parameters, estimation methods, experimental group allocation ratio, etc.

8. Randomization methods and randomization stratification factors

Simple randomization, block randomization, stratified block randomization, etc., or adaptive randomization, such as minimization methods, etc.; and random allocation systems, such as interactive response systems

9. Blinding method (e.g. single-blind, double-blind or open design)

Single-blind, double-blind and open designs, etc., as well as simulation methods such as the smell or color of the test drug (such as the use of simulated agents)

10. Medication regimen

11. Standard definitions of efficacy endpoints and efficacy results, etc.

List at least the point estimate, interval estimate, and P value (if applicable) for its primary and key secondary efficacy endpoints

Selection of efficacy endpoints

If the efficacy endpoint is a surrogate endpoint, the rationale for selecting the endpoint and the rationale supporting its prediction of clinical outcome should be discussed. If the effectiveness endpoint is a clinical outcome evaluation indicator used for the first time (such as patient-reported outcomes, clinician-reported outcomes, etc.), the rationality of its use should be explained.

12. Replenish

1. Drug dose selection

Fixed dose, flexible dose, forced titration, etc.

2. Treatment duration and study duration

If the treatment duration is 1 month, the follow-up duration is 3 months

3. Use of independent committees in research

Such as data monitoring committee, endpoint adjudication committee, etc.

4. adaptive design features

Such as sample size re-estimation, group sequential design, abandonment or addition of treatment groups, changes in patient inclusion criteria, etc. Special attention should be paid to whether the changes in research measures are preset and whether the total Type I error rate is effectively controlled, etc.

2. Description, comparison, and discussion of statistical analysis methods

1. Compare the similarities and differences in statistical analysis methods for the primary and key secondary efficacy endpoints of each single clinical study, such as covariance analysis using different covariates, etc.

2. Compare the treatment methods of subject dropout and missing data in each single clinical study

3. If necessary, non-preset statistical analysis methods in each individual clinical study can also be discussed.

Overall analysis of effectiveness results

Comparisons between individual clinical studies

List showing the number of subjects, number of dropouts, demographic characteristics, baseline characteristics, etc. of each single clinical study

Lists or graphs (such as forest plots) to display and compare effectiveness results from individual studies

1. Focus on primary and key secondary efficacy endpoints

2. Combined with subject demographics and baseline characteristics (e.g., disease severity), inclusion or exclusion criteria, control type, Exposure dose, exposure duration and statistical analysis methods are discussed.

3. Analyze consistency of effectiveness results across subjects across regions (if available)

4. If a certain effectiveness endpoint has different but repeated importance in multiple single clinical studies, it can also be compared and analyzed (even if it is not statistically significant) as an important evaluation content of the drug's effectiveness.

5. Effectiveness results from individual clinical studies with the same or similar study design features (such as the same or similar control groups) should be compared and discussed together.

6. Clinical studies that confirm the effectiveness of the Chinese population based on foreign research data (such as bridging studies) should be specially noted during the discussion, and other supporting information for extrapolating the foreign research data to the Chinese population should be provided.

Meta-analysis of individual clinical studies

1. It is recommended to use individual-level data for meta-analysis

2. During meta-analysis, individual studies should be carefully selected to minimize selection bias and ensure the credibility of the analysis results.

3. Account for heterogeneity across individual studies

4. Single studies with different study design characteristics are generally not suitable for meta-analysis.

Single-arm studies and studies with parallel controls should not undergo meta-analysis

5. Explain the rationale for the methods used in meta-analysis of the effectiveness results of individual clinical studies

Subgroup analysis

Purpose

Comparison: Assess the consistency of effectiveness results across subgroups of people across individual studies

Meta-analysis: Precisely assesses differences in effectiveness results between subgroups of people, which can provide hypotheses for further clinical research.

form

The subgroups and their definitions in each individual study are presented in tabular form.

Subgroup population analysis can be displayed in tables or graphs (especially forest plots), and statistical inference is generally not required.

content

Evaluate the impact of key demographic characteristics (e.g., age, sex) and other relevant intrinsic and extrinsic factors (e.g., disease severity, prior treatments, concomitant medications, renal or hepatic impairment) on efficacy outcomes

Evaluate differences in effectiveness results across countries and regions

Analysis of clinical information related to recommended drug dosage

Analyze content

1. Recommended dose range, including starting dose and maximum dose

2. Lower dose limit at which increasing dose does not result in increased effectiveness

3. Dosage by indication and subgroup

4. Medication frequency

5. How to titrate doses

6. Medication recommendations based on clinical pharmacology data (e.g. food effects)

7. Dosage adjustments required due to drug interactions or special populations

Children, the elderly, groups defined by genetic characteristics, people with liver and kidney dysfunction

8. Important notes about medication regimen compliance

9. Any other advice related to personalized medicine

focus

1. Analyzes from individual studies supporting dose recommendations, as well as from any crossover studies, should be included in the combined analysis

2. If the preparation used in the study is inconsistent with the preparation to be commercialized, its comparability should be stated

3. Deviations caused by nonlinear characteristics of pharmacokinetics, possible causes, and their impact on clinical use should be described.

such as delayed effects, tolerance effects or enzyme induction

4. Limitations of the data should be described and assessed

If the study uses a titration design rather than a fixed-dose design

5. The method of administration for each study should be clearly described (e.g. once daily in the morning or before meals)

6. Dosage for each treatment group should be clearly described

7. Information on medication changes in the event of adverse events

8. Information on medication changes when any critical measures specified in the study protocol affect the medication regimen

such as dose level titration

9. The method used to assess differences in dose-response relationships should be described

1. Specific studies conducted in subgroups of people

2. Analyze effectiveness results by subgroups

3. Research methods for detecting drug concentration in blood

Long-term effectiveness, tolerability and discontinuation analysis

1. Collect as much as possible all available information from long-term observations

2. Describe long-term observational information such as dose usage, duration of exposure, and reasons for discontinuation

3. Analyze changes in effectiveness and tolerability over time and the impact of other concomitant medications on effectiveness

4. Summary and discussion of effectiveness, tolerability, and discontinuation

5. Analysis should focus on effectiveness results from controlled clinical studies

6. Make a clear distinction between well-controlled studies and studies that are less rigorously designed

regulatory considerations

1. Develop and submit statistical analysis plan for comprehensive analysis of effectiveness

1. Describe analysis strategies, analysis methods, and meta-analysis methods

2. Submit together with comprehensive effectiveness analysis report

3. Reports on the overall effectiveness information of clinical studies required by CTD or eCTD should comply with the format requirements of this document

4. Fully communicate with regulatory agencies before or during the formulation

2. Meta-analyses of effectiveness results should only be used as supporting evidence

It cannot replace the confirmatory role of individual studies.

3. Comprehensive analysis of discriminant effectiveness and summary of clinical effectiveness

1. A comprehensive analysis of effectiveness is a comprehensive analysis of the effectiveness results from all clinical studies

2. The comprehensive analysis of effectiveness should be placed in Section 5.3.5.3 "Multiple Study Data Analysis Report" of CTD/eCTD Module 5

3. The clinical effectiveness summary is a summary of the comprehensive effectiveness analysis report and should not contain any analysis or conclusion other than the comprehensive effectiveness analysis.

4. The clinical effectiveness summary should be placed in Module 2, Section 2.7.3 "Clinical Effectiveness Summary"

5. When very limited data are available from clinical studies

1. Orphan drug clinical studies, or only one clinical study, or only include some small clinical studies

2. The main body of the comprehensive effectiveness analysis report can be used as a summary of clinical effectiveness

3. The main part is placed in Section 2.7.3 of Module 2

4. Tables, figures and datasets are included as appendices in Module 5, Section 5.3.5.3

5. Provide clear explanations in the corresponding sections of Module 2 and Module 5

4. Impact of applying ICH E9(R1) on the implementation of this guidance

As practical experience accumulates, these guidelines will be further revised

Estimated goals and sensitivity analysis in clinical trials

subtopic