Guidance on collecting and analyzing disaggregated data in clinical trials: Appendices

On this page 

• Appendix A: Disaggregated data plan and best practices
• Appendix B: Heterogeneity assessment
• Appendix C: Disaggregated data decision tree

Appendix A: Disaggregated data plan and best practices

The section outlines principles and best practices on collecting and analyzing disaggregated clinical trial data for drug submissions (NDSs and Level I SNDSs).

The collection and analysis of disaggregated data are key aspects throughout a drug product’s life cycle:

• clinical trial study and protocol design
• dose selection
• testing and evaluation
• clinical validation
• risk analysis and management
• transparency and reporting
• market authorization and post-market safety monitoring

If you have not submitted disaggregated data to the US FDA or EMA, we strongly encourage you to submit a Disaggregated Data Plan (DDP) to Health Canada where feasible.

Considerations in clinical trial protocol design

There are a number of things to consider when designing a protocol for a clinical trial of a drug product for human use, especially for a phase 3 and 4 trial. This information will help you recruit diverse clinical trial participants and plan for appropriate subgroup analyses.

Recruiting diverse clinical trial participants and conducting relevant subgroup analyses is important to explore if:

• there are differences between subgroups
• the clinical trial population reflects the full diversity of the population that will use the drug product being tested
• the drug requires further monitoring after it has been authorized and on the market

It is good standard practice to ensure that clinical trial participants reflect the populations who will be using the drug product. This is to ensure that the clinical trial results apply to the people who are likely to use the drug product.

Health Canada has also developed the Draft Guidance for Clinical Trial Sponsors: SGBA Plus Demographics Action Plan in Clinical Trial Applications. It explains how to submit a voluntary SGBA Plus Demographics Action Plan as part of clinical trial applications. The guidance outlines our expectations and recommended best practices for integrating SGBA Plus considerations throughout the clinical trial lifecycle, including:

• inclusive trial design
• participant recruitment
• collecting and analysing relevant demographic characteristics

The draft guidance aims to support adequate representation of diverse populations and promote equitable drug development in Canada. We encourage sponsors to consult it early in clinical trial planning and design.

Evidence that can help evaluate the benefits and risks of a drug product for specific subgroups includes:

• disaggregating clinical data based on the age, sex, race and ethnicity of participants and
• other baseline characteristics that are clinically relevant

Differences in age, sex, race and ethnicity may impact the safety or effectiveness of a drug product in certain subpopulations.

For example:

• sex differences in pharmacokinetics and pharmacodynamics may affect a drug’s safety or efficacy
• certain racial or ethnic groups may need different dosing recommendations, such as:
  • lower initial starting dose of statins to treat high cholesterol in Asian patients
  • higher doses of tacrolimus to prevent organ transplant rejection in Black patients

Racial, ethnic and sex differences in drug metabolism can be mostly attributed to genetic and genomic differences. These differences can affect drug absorption, distribution, metabolism and excretion.

Genetic and genomic factors influence the overall enzyme make-up of an individual, and certain mutations or gene variants are more common in some ethnic groups. This contributes to pharmacokinetic variability in these subgroups. For example, gene variants affecting transporter proteins can impact the safety and effectiveness of statins. Similarly, gene variants also affect how enzymes are expressed, which can influence the bioavailability and clearance of tacrolimus.

Learn more:

• Considerations for inclusion of women in clinical trials and analysis of sex differences
• Draft Guidance for Clinical Trial Sponsors: SGBA Plus Demographics Action Plan in Clinical Trial Applications

Disaggregated data plan

A disaggregated data plan (DDP) is used to determine the parameters for collecting and analyzing disaggregated data by age, sex, race, ethnicity and other associated covariates. We encourage sponsors to include a DDP to help establish if and how specific population subgroups may be affected by a treatment (the benefits and risks).

The content of the DDP is based on the findings of the heterogeneity assessment (HA). This evaluates the likelihood of differences in treatment efficacy or safety between subgroups in the study population (refer to Appendix B).

To support subgroup analysis, you can enrol representative proportions of participants based on age, sex, race and ethnicity that are consistent with those who will use the drug product or as indicated by the assessment.

Visit Appendix C for the Disaggregated data decision tree to guide considerations in protocol design.

Otherwise, you can either:

• justify how the enrolment criteria provide acceptable representation for the intended population or
• explain if the DDP is based on a factor other than age, sex, race or ethnicity as a primary driver of heterogeneity

While these recommendations apply to all clinical trials, they are targeted to phase 3 and 4 studies, which tend to enrol more patients than earlier phases.

In the DDP, you will describe:

• the number of participants planned for each study
  • outline how you will collect subgroup data over the life cycle of the product
• how age, sex, race, ethnicity and other related covariates will be assessed
• how potential differences will be considered

Including these details will help you develop a plan for considering diverse subgroups before your trial begins. For example:

• If it is known early on that the treatment is only effective in certain subgroups relevant to the intended patient population, then you could restrict enrolment to those groups.
• If a factor used to define affected subgroups is known to be prognostic in value, then you could use stratified randomization based on this factor to balance for this factor.

We recommend that you:

• enter details from the HA and DDP, including enrolment strategies, in the appropriate sections of the clinical study protocol and statistical analysis plan
• consult ICH E3 Structure and Content of Clinical Study Reports (CSR)

For information on how to submit, consult:

• Preparation of regulatory activities in the electronic common technical document (eCTD) format
• ICH M4E(R2): The CTD — Efficacy Guidance for Industry
  • Refer to sections 2.7.3.3.1, 2.7.3.3.3, 2.7.4.1.3 and 2.7.4.2 to include applicable results, analyses and discussions.

To prepare data submitted in the CSR:

• capture disaggregated data for enrolled and completed participants
  • population pharmacokinetic analyses often include age and sex as co-variates
  • include race and ethnicity data as these may affect the parameters of use due to potential differences in safety or effectiveness of a drug in certain populations
  • pharmacometric modelling and analyses are encouraged
• present key efficacy and safety data by age, sex, race and ethnicity and describe if treatment changes (for example, of dose or dosing regimen) are needed for subgroups
  • clinically relevant findings may be reflected in the product labelling
  • consult the product monograph guidance document

It’s best to discuss any issues with the relevant Health Canada directorate early on in the process. As a sponsor (or manufacturer), you are encouraged to also ask for feedback at a pre-clinical trial application meeting or pre-submission meeting for a new drug submission (NDS) or supplement to a new drug submission (SNDS).

For more information on pre-submission meetings for NDSs or SNDSs, consult:

• Management of drug submissions and applications

Key subgroups

Important considerations for collecting and analyzing disaggregated data include key subgroups and parameters for analysis, interpretation and reporting.

We encourage sponsors to indicate in the study protocol how you will be assessing subgroup data before you enrol clinical trial participants.

Consider all relevant variables when designing clinical trials that are specific to the therapeutic area being studied.

There are, however, important things to consider when including clinical trial participants who are diverse in sex, age, race and ethnicity. We understand that representative enrolment of these subgroups in clinical trials can be challenging.

If you are having trouble recruiting certain population groups, you may wish to devise a plan to help you increase participants from the groups you are interested in studying before representative enrolment begins.

Learn more by consulting the following guidance documents from the US Food and Drug Administration (FDA):

• Enhancing Participation in Clinical Trials — Eligibility Criteria, Enrollment Practices, and Trial Designs
• Collection of Race and Ethnicity Data in Clinical Trials | FDA

Sex

Include a representative number of females and males in the clinical trial, as applicable to the intended population who will use the drug.

To identify and account for potential sex-related differences, we recommend that females (such as those who are of child-bearing age or menopausal) be included as early as possible in the research stage (phase 1), when appropriate.

For details on what to consider when collecting and analyzing sex-related data, consult:

• Considerations for inclusion of women in clinical trials and analysis of sex differences

Age

Age groups should reflect the clinical prevalence of disease.

Provide a detailed disaggregation of age groups. For example, to better inform treatment decisions for geriatric patients, older patients may be grouped into ages:

• 65 to 74
• 75 to 84
• over 84

This is preferred more than grouping all age groups into a 65 and over category.

Learn more:

• ICH E7: Studies in support of special populations: Geriatrics
• FDA: Inclusion of older adults in cancer clinical trials

When considering pediatric age subgroups corresponding to developmental biology specific to a drug product, we recommend you group patients into:

• preterm newborn infants
• term newborn infants (0 to 27 days)
• infants and toddlers (28 days to 23 months)
• children (2 to 11 years)
• youth (12 to 16 or 18 years)

Neurocognitive development, puberty, hormonal changes and weight are some examples of characteristics to consider when planning, analyzing and reporting pediatric subgroup data.

Learn more:

• ICH E11: Clinical investigation of medicinal products in the pediatric population

Race and ethnicity

To assess potential race and ethnicity-related differences for the population who will use the drug, we recommend that you enrol representative proportions of subjects in your clinical trial. Note that the following will vary:

• specific race and ethnicity subgroups depending on the population that is expected to use the drug
• the geopolitical context where the clinical trials will be conducted and where the application for market authorization will be submitted

We encourage you to follow self-reported race and ethnicity classifications developed by Statistics Canada when conducting trials in Canada.

Current classifications for population groups include:

• Arab
• Black
• White
• Filipino
• Korean
• Chinese
• Japanese
• West Asian
• South Asian
• Latin American
• Southeast Asian
• other (specify)

Indigenous Peoples comprising of First Nations, Métis and Inuit populations are another key population group in Canada.

Make it easy for respondents to select the categories that apply to them.

For trials conducted elsewhere, follow the reporting categories of the respective national regulatory body, if available. More detailed racial and 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. To address this, consider clearly defined subgroups in your protocols.

Learn more:

• Examples of Indigenous, national, ethnic or cultural origins

Analyzing, interpreting and reporting disaggregated data

Results for key efficacy and safety outcomes should be based on the subgroups defined by age, sex, race or ethnicity. Interpret these results with caution, as there may be a limited number of participants in some subgroups.

For guidance on analyzing and interpreting subgroup data, consult:

• Section 5.7, "Subgroups, interactions and covariates" in ICHE9

If the differences observed among various subgroups can be interpreted and are clinically relevant:

• assess if the results are biologically plausible or occurred by chance and
• address those results that may impact the benefit-risk profile of the product in the relevant subgroup

In such cases, we may:

• request additional data
• implement terms and conditions
• recommend specific labelling
• require additional post-market studies or surveillance
• require additional risk minimization measures

You can include:

• a description of methods and approach in the clinical trial protocol and statistical analysis plan, 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, present these in the appropriate section of the CSR results based on analyses:

• described in the disaggregated data plan (DDP) and
• captured in the appropriate sections of the clinical study protocol and statistical analysis plan

In particular, you can also include:

• a table that presents disaggregated demographic data by treatment group
  • refer to ICH M4
• subgroup results for key measures in the applicable efficacy and safety sections
• a discussion of differences that are considered clinically relevant and biologically plausible on the benefit-risk profile specific to age, sex, race and ethnicity

Appendix B: Heterogeneity assessment

A heterogeneity assessment (HA) is an evaluation on whether differences in treatment efficacy or safety are anticipated between subgroups in the study population. An HA describes the measures taken to establish whether there are or could be clinically important age, sex, racial and ethnic differences in response to the drug product being tested.

The United States Food and Drug Administration (FDA) outlines a similar approach:

• Diversity action plans to improve enrollment of participants from underrepresented populations in clinical studies

To ensure diverse subgroups are meaningfully considered in the development and testing of a drug product, complete an HA at the start of the clinical development program (if possible). This HA will determine the best approach for developing and designing the clinical trial.

Update the HA throughout the development process as more information on sources of heterogeneity is learned from early-phase trials. These additional sources of heterogeneity may require further supporting data.

If the HA indicates that treatment differences are not anticipated among subgroups, enrolment would still be broad and reflect disease epidemiology. Broad enrolment of representative populations:

• permits analyses of subgroups
• helps to assess the consistency of a drug product’s effectiveness across trials

Learn more:

• ICH E9: Statistical principles for clinical trials

If the HA or evidence from previous or ongoing studies indicates there are potential differences in any of the subgroups studied, these differences should be considered when planning, designing and analyzing subsequent studies within the clinical development program. Aim to recruit enough representative patients so that the benefit-risk profile can be analyzed in the relevant subgroups.

Learn more:

• Guideline on the investigation of subgroups in confirmatory clinical trials (European Medicines Agency)

If different treatment responses between subgroups is a possibility, the potential reasons for the heterogeneity should be explored and described at the design stage. An analysis would consider these potential differences. (In some cases, this type of analysis may only be feasible when analyzing all of the clinical evidence or during post-market monitoring.)

Known factors may affect the safety and efficacy of the drug product between subgroups. These include:

• biological plausibility
• therapeutic drug class
• disease pathophysiology
• epidemiology of the condition
• previously identified predictive or prognostic factors

Information on certain diseases may be limited, making it difficult to assess potential subgroup-specific heterogeneity. Relevant data sources may be found in academic literature or real world evidence (RWE).

Non-clinical studies can also provide supportive data. For example, pharmacology and toxicology studies conducted in male and female animals can indicate potential sex-related differences in concentration response, safety or efficacy.

To understand how non-clinical studies can support and inform clinical trial evidence, consult ICH’s guidelines for clinical trials:

• ICH E8: General considerations for clinical studies
• ICH S9: Nonclinical evaluation for anticancer pharmaceuticals
• ICH S11: Nonclinical safety testing in support of development of paediatric pharmaceuticals
• ICH M3(R2): Nonclinical safety studies for the conduct of human clinical trials for pharmaceuticals

Include the HA in your submission material for clinical trial applications or market authorization.

Note: The information in this guidance applies to other documents, including the Guidance document for clinical trial sponsors: Clinical trial applications.

Appendix C: Disaggregated data decision tree

The disaggregated data decision tree outlines key questions to help you design a clinical trial based on the population that will use the drug being tested. The decision tree summarizes the content in the section on Considerations in protocol design. Also refer to Appendix A on Disaggregated Data Plan and Best Practices.

Figure 1. Decision tree: Clinical trial study design

Is the clinical use population heterogeneous by subgroup (age, sex, or race and ethnicity)?

No: Sponsors are to provide a justification explaining how the studied population reflects the target population that will use the health product.

Yes: Sponsors are encouraged to conduct a Heterogeneity Assessment that would include:

• Disease epidemiology by subgroup
• Diagnosis and treatment patterns by subgroup
• Known clinically meaningful outcome differences by subgroup (based on drug, disease pathophysiology, prognostic and predictive factors)
• Intermediate study data, or previous study data

The assessment should be updated throughout the clinical development program.

Next, make a Disaggregated Data Plan (can be part of Clinical Study Protocol and/or Statistical Analysis Plan). Provide a strategy and description for subgroup enrollment and assessment, alongside corresponding detailed methodology.

Then, create a Disaggregated Data Submission (can be part of the Clinical Study Report). Include:

• Data for “enrolled and completed” participants
• Data pertaining to key outcome measures (efficacy, safety), as applicable
• Corresponding results, analyses and discussion