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December 15, 2023

ICH E9 and CDISC: The Master Formula for Excellence in Clinical Research and Data Management

Clinical studies play a key role in the development of new medicinal products and therapies, as well as in evaluating the efficacy and safety of existing medical treatments. To ensure the quality and reliability of the data collected in these studies, it is essential to follow robust guidelines and standards. One of the most important guidelines in this field is ICH E9, published by the International Council on Harmonization (ICH).

By Mercedes Ovejero and Jaime Ballesteros, Biostatistics and Data Management Unit at Sermes CRO

What is ICH E9?

ICH stands for “International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use“. This council brings together regulators and pharmaceutical industry representatives from different regions of the world to harmonize standards, regulations and practices in the development and registration of medicinal products.

ICH E9 specifically addresses statistics in clinical trials. It provides guidance on how to conduct an appropriate study design, what data must be collected, how to analyze the data, and how to submit the results clearly and accurately. This guideline is essential to ensure the validity and reliability of clinical trial results and to meet regulatory standards for submission of data for the approval of medicinal products.

Key elements of ICH E9

Clinical study design: ICH E9 pays considerable attention to the design of clinical studies, which is critical to ensuring the validity and efficacy of the trials. Some key aspects include:
- Patient selection: The guideline highlights the importance of defining specific inclusion and exclusion criteria to ensure that the study population is representative of the target population for the treatment.
- Randomization: Random assignment of patients to treatment groups is recommended to minimize bias and ensure fairness in the allocation of subjects.
- Analysis sets: ICH E9 emphasizes the analysis of data according to the intention-to-treat principle. This means that all patients assigned to a treatment group should be included in the analysis, regardless of whether they complete the study or not. This avoids potential biases caused by ignoring patients who do not adhere to treatment. However, the per protocol population (PP) is also mentioned as a relevant subpopulation in confirmatory studies and to increase the robustness of the results.
Statistical analysis: The guideline provides guidance on how to perform statistical analysis of clinical data. Some important aspects are:
- Sample size calculation: The sample size in clinical trials should be sufficient to answer questions reliably. It is mainly determined by the primary objective, but if it is based on other criteria, it must be justified. It is considered key variables, hypotheses, type I and type II errors are specified, and withdrawal from treatment.
- Appropriate statistical methods: ICH E9 urges investigators to use statistical methods appropriate to the type of data collected and the objectives of the study. This includes hypothesis testing, analysis of variance, regression analysis, and other approaches.
- Handling of missing data: The guideline addresses the handling of missing data and provides instructions for minimizing bias and ensuring that the results are representative of the study population.
- Adjustments by multiple comparisons: Multiplicity in clinical trial analysis requires adjustment for type I error. It can arise from multiple primary variables, comparisons of treatments, or repeated evaluations over time. Methods to reduce multiplicity, such as identification of key variables or critical contrasts, are preferred, and in confirmatory analyses, adjustment should be considered, with any procedures detailed or their omission explained in the analysis plan.
Interpretation of results: ICH E9 stresses the importance of proper interpretation of results, not just analysis. This includes:
- Clinical relevance: The guideline emphasizes the need to consider the clinical relevance of results. It is not sufficient to rely on statistical significance alone; results must be evaluated in the context of their clinical significance.
- Risk-benefit relationship: Investigators are encouraged to evaluate both benefits and risks of the treatment to make informed decisions about the approval of a medicinal product.
Safety and tolerability: ICH E9 is not limited to efficacy, but also addresses the safety and tolerability of treatments. This includes:
- Detection of adverse events: The guideline provides instructions on how to detect and document adverse events during clinical trials.
- Comparison of safety profiles: It is encouraged to compare safety profiles between treatment groups and consider the balance between therapeutic benefits and potential risks.
Documentation and submission: ICH E9 provides recommendations for the documentation and submission of clinical study results. This is essential in order to submit regulatory reports and ensure transparency in clinical research.

Is there a relationship between ICH E9 and the CDISC standards?

Yes, there is a relationship between ICH E9 and the CDISC (Clinical Data Interchange Standards Consortium) system. Both are concerned with standardizing and improving the collection, management, and submission of clinical data in pharmaceutical and medical research. This relationship is discussed in more detail below:

Clinical data standards: Both ICH E9 and CDISC focus on the standardization of clinical data in clinical trials and other studies related to medical research. ICH E9 focuses on the statistical and design aspects of clinical studies, while CDISC focuses on establishing standards for structuring data and metadata.
International harmonization: ICH is an organization that seeks to harmonize pharmaceutical regulations worldwide, and ICH E9 is an example of this collaboration. As for CDISC, it is dedicated to developing global, consensus-based standards for the collection, exchange, and submission of clinical data.
Data integration: The relationship between ICH E9 and CDISC lies in the need to ensure that data collected in clinical trials follow certain standards and structures. CDISC provides standardized data models, such as the Study Data Tabulation Model (SDTM), that enable consistent data collection and exchange.
Regulatory data submission: Data standardization in the context of CDISC can facilitate the submission of data to regulatory agencies, which is essential for the approval of new medicinal products and therapies. ICH E9 provides instructions for the analysis of clinical data in this process.
Efficiency and quality: Both approaches aim to improve the efficiency and quality of clinical data collection and analysis. The data standardization promoted by CDISC facilitates reporting and regulatory review, while ICH E9 focuses on the quality of statistical analysis and interpretation of results.

In conclusion…

ICH E9 and CDISC share the goal of improving the quality and efficiency of clinical research and medicinal product development. Although they focus on different aspects of clinical data management, they work together to promote standardization and transparency throughout the clinical research chain, from study design to data submission to regulatory authorities. The relationship between ICH E9 and CDISC is critical to ensuring data integrity and quality in medical and pharmaceutical research.