Guidance on clinical evidence requirements for medical devices: Clinical data and evaluation

Clinical data are the safety or effectiveness information that is generated from the clinical use of a medical device. Sources of such data include device-specific clinical investigations, published clinical literature and post-market surveillance data.

Factors that may influence the need for clinical data include:

Note: Rare adverse events could include, for example, unintended events, disease or injury, or clinical signs that occur so infrequently that they cannot be evaluated in a pre-market study. The World Health Organization uses the term "rare" when describing an adverse event that occurs between 1 in 1,000 people and 1 in 10,000 people.

For example, an application may be subject to an increased need for device-specific clinical data (such as undergoing sufficient statistical analysis to justify study endpoints and sample size, demographics) if there is a lack of safety and effectiveness evidence for:

Where safety and effectiveness have been adequately demonstrated but clinical data collection is ongoing, results from ongoing tests may need to be submitted following licensing. This requirement is set out under terms and conditions at the time of licensing. Clinical data collection may be ongoing due to the emerging nature of the technology (for example, to gather information on long-term use or on use in rare patient populations in a real-world setting or to study a specific population). The results from this ongoing clinical data collection must demonstrate that the device's continued safety and effectiveness are maintained post-market.

When analyzing clinical data, it's important to consider the quality of the data in terms of sources of uncertainty, missing data or the degree of disaggregated population data. Manufacturers should provide estimates on the amount of under-reporting, for example:

The value of the clinical data is diminished and may result in a need for higher-quality device-specific clinical data if:

It's also important that any reports or collection of data represent robust evidence. There should be sufficient information to make an objective assessment of the device's safety and effectiveness. For example, randomized, controlled clinical trials provide a higher quality of evidence. By contrast, reports of clinical experience, such as anecdotal reports, individual case reports or expert clinical opinion, are of lower quality. This type of information is generally limited to cases where it's not feasible or practical to collect high-quality clinical data (for example, in rare disease states, under-represented patient populations and emergent interventions).

Health Canada expects that clinical data referred by manufacturers adequately represent the Canadian population and clinical practice. Any clinical data used by the manufacturer to demonstrate a device's safety and effectiveness should reflect the population for whom the device is intended.

Clinical data that is representative of the population

Sex- and Gender-based analysis plus (SGBA Plus) is an analytical process used to assess how diverse groups of people may be impacted by product or federal initiatives. Diverse groups of people include women, men, girls, boys, gender-diverse people, racial and ethnic minorities, persons with disabilities, and First Nations, Inuit and Métis people. Consideration is given to biological factors related to sex, race and ethnicity, socio-cultural factors related to gender and other identity factors.

The "Plus" recognizes that people have multiple identity factors that intersect and accumulate, that privilege or disempower, impacting their lived experiences and health. In other words, SGBA Plus considers many critical identity factors (for example, race and ethnicity, religion, age, mental and physical disability, geography, income, education). The ways they intersect inherently govern their social, economic and health outcomes.

Evidence demonstrates that biological, economic and social differences between diverse groups of women and men contribute to differences in health risks, health services use, health system interaction and health outcomes. The integration of SGBA Plus throughout the life cycle of a medical device will lead to sound science that addresses the different needs of people effectively.

Given the potential for different impacts of medical devices for diverse subpopulations, clinical studies should include adequate representation in a disaggregated manner:

As a guideline, manufacturers should consider the following key questions when integrating SGBA Plus in the design of clinical trials:

Device design should take into account the unique anatomical and physiological characteristics of all sexes and genders to the extent that this is practicable. When clinical studies are not sufficiently sized or powered to draw conclusions from these subgroups, manufacturers are encouraged to consider how certain types of other clinical data (in particular real world evidence (RWE) and post-market clinical experience) can be used to demonstrate the differential impacts of a device on different sexes and genders.

Further, where feasible, the differential impacts of a device on under-represented populations, including racial and ethnic groups, should be considered in clinical trials or investigations. This might be done through clinical trial design approaches such as stratification or by requiring a minimum number of patients from these subgroups within a larger clinical trial.

For more information and guidance, please consult the following items:

Clinical data for under-represented populations

When considering clinical data for under-represented populations, including children or pregnant individuals, manufacturers may have limited clinical data. Sometimes, this data gap can be mitigated by conducting small, well-designed clinical trials or by including a group of patients from the under-represented population within a larger clinical trial. Alternately, a device might be granted a licence with terms and conditions that stipulate more follow-up to demonstrate ongoing safety and effectiveness. Labelling limitations may also be required where there is not sufficient clinical data.

Manufacturers may also consider other ways to extract the needed clinical data from existing data. This can include leveraging RWE that may reflect the device's use in sub-population groups who don't usually participate in clinical investigations. Manufacturers should also consult existing institutional research practices or guidelines on including under-represented populations in clinical trials or investigations when it's safe to do so.

Pediatric devices (neonates, infants, children and adolescents)

Biologically, children (especially 6 years and younger) and adults are different. As infants and children have smaller organs, medical devices designed for adults may not be appropriate.

Pediatric populations are under-represented in clinical trials and investigations. This is an area of concern. As such, care must be taken to evaluate the limited datasets in the pre-market evaluation stage and in the assessment of post-market signals.

Manufacturers need to consider the following factors, including:

These pediatric-related factors should be considered when designing the product, as well as during the assessment, interpretation of data, indications for use, labelling and risk mitigation phases. Intended patient age and/or patient weight should be stated in the intended use if it will affect the device's performance or safety. Consideration should also be given to different sub-groups of the pediatric population (for example, neonates, adolescents), which have different needs and risk profiles.

Pre-market applications for a product used by the pediatric population should show how the design considers this group. For example, if a device will be used by adolescents down to neonates, then the pre-market application should show how these targeted populations were considered in the design. Product testing or theoretical justification, whichever is appropriate, may be used to demonstrate this. For example: