Draft guidance document on the collection and analysis of disaggregated data in clinical trials: Data collection and analysis
Important considerations for collecting and analyzing disaggregated data include key subgroups and parameters for analysis, interpretation and reporting.
Sponsors should pre-specify the strategy for enrolling and assessing subgroup data in the protocol before they enroll clinical trial participants.
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Key subgroups
The variables that should be considered when designing clinical trials are specific to the particular therapeutic area in which the study is being conducted. However, there are key considerations for including clinical trial participants who are diverse in sex, age and race/ethnicity. Of note, it is understood that representative enrollment of age, sex, and racial/ethnic subgroups may pose challenges.
Sponsors should consider potential reasons if they have difficulty recruiting certain populations. In this case, you should devise strategies to enhance enrollment and retention in the subgroups of interest, as needed.
Learn more by consulting the following guidance from the U.S. Food and Drug Administration (FDA):
Sex
Include a representative number of females and males in clinical trials, as applicable to the intended population that will use the drug.
To identify and account for potential sex-related differences when planning clinical trials, we recommend that females (such as those who are of child-bearing age or menopausal) be included as early as possible in the clinical trial research stage.
For details on what to consider when collecting and analyzing sex-related data, please consult the following guidance document:
Age
Age groups that reflect the clinical prevalence of disease should be adequately represented. This permits the analysis of various age groups, as needed.
We recommend that detailed disaggregation of age groups be provided. For example, to better inform treatment decisions for geriatric patients in clinical practice, older patients may be grouped into ages 65 to 74, 75 to 84 and over 85 rather than the combining all age groups into a 65+ category.
Learn more in the following guidance documents:
- ICH E7: Studies in support of special populations: Geriatrics
- FDA: Inclusion of older adults in cancer clinical trials
Detailed disaggregation of pediatric age subgroups corresponding to developmental biology specific to drug product pharmacology is also recommended, for example:
- preterm newborn infants
- term newborn infants (0 to 27 days)
- infants and toddlers (28 days to 23 months)
- children (2 to 11 years)
- adolescents (12 to 16/18 years)
Neurocognitive development, puberty, hormonal changes and weight are some examples of processes or characteristics that should be considered when planning, analyzing and reporting pediatric subgroup data.
Learn more:
Race/ethnicity
To assess potential race/ethnicity-related differences for the population who will use the drug, we recommend that representative proportions of subjects be enrolled in clinical trials. Note that the following will vary:
- specific race/ethnicity subgroups depending on the population that is expected to use the drug
- the geopolitical context where the clinical trials will be held and where the application for market authorization will be submitted
For trials conducted in Canada, self-reported race/ethnicity should follow Statistics Canada classifications. Current classifications for population groups include:
- Arab
- Black
- White
- Filipino
- Korean
- Chinese
- Japanese
- West Asian
- South Asian
- Latin American
- Southeast Asian
- other group (specify)
Indigenous Peoples comprising First Nations, Métis and Inuit populations are another key population group in Canada. Respondents should be able to select the categories that apply.
For trials conducted elsewhere, sponsors should follow the reporting categories of the respective national regulatory body, if available. More detailed racial/ethnic data may be required in certain conditions with specific hereditary patterns.
Reporting standards in different countries will vary, making it difficult to pool data for comparisons. Consequently, sponsors should clearly define subgroups in their protocols.
Analyzing, interpreting and reporting disaggregated data
Sponsors should stratify results for key efficacy and safety outcome(s) by age, sex and race/ethnicity, as applicable. These results should be interpreted with caution, given the potential for a limited number of participants in some subgroups and for confounding by other factors.
For guidance on analyzing and interpreting subgroup data, please refer to:
If the differences observed among various subgroups are interpretable and considered clinically relevant, sponsors should investigate if the results are biologically plausible or may have occurred by chance. Following a thorough assessment, sponsors should address those results that are biologically plausible and thus may impact the benefit-risk profile of the product in the relevant subgroup(s).
In such cases, Health Canada may:
- request additional data
- implement terms and conditions
- recommend specific labelling
- require additional post-market studies or surveillance
- require additional risk minimization measures
Sponsors should include:
- a description of methods and approach in the clinical trial protocol and statistical analysis plan (SAP), as applicable
- results, analyses and subsequent discussion in the clinical study report (CSR)
To assess the consistency of the efficacy and safety findings across relevant subgroups, sponsors should present results based on analyses described in the disaggregated data plan (DDP) (and captured in the appropriate sections of the clinical study protocol and SAP). These should be placed in the appropriate section of the CSR, if available.
In particular, sponsors should also include:
- a table that presents disaggregated demographic data by treatment group (ICH M4)
- subgroup results for key measures in the corresponding efficacy and safety sections, as applicable
- a discussion of differences that are considered clinically relevant and biologically plausible on the benefit-risk profile specific to age, sex or race/ethnicity, as applicable