Cancer inequities
Active team: SAMBAI
Challenge: Understand the mechanisms through which genetics, biology, and social determinants affect cancer risk and outcomes in diverse populations, to motivate interventions to reduce cancer inequities.
We set this challenge in 2023, which team SAMBAI is currently tackling. We're not accepting new applications.
Please note that the description below reflects the challenge as set by our Scientific Committee in 2023; we understand that there may have been developments in the field between then and now.
If you're interested in a plain language summary of the challenge, you can find it at the bottom of the page.
The challenge
Professor Timothy Rebbeck talks about the cancer inequities challenge.Context
Inequities in cancer prevention, screening, and treatment lead to disparities in cancer incidence and mortality and are a major public health concern.
The causes of cancer inequities are complex yet often poorly elucidated. While most inequities are the consequences of social determinants and circumstances (e.g., late-stage diagnosis due to inadequate access to healthcare), there are emerging data that indicate that genetics and biology also play a role. Polygenic scores confer risks that vary by Self-identified Race and Ethnicity (SIRE); genetic ancestry is correlated with cancer risk or outcomes independently of SIRE; and tumour phenotypes and mutational signatures differ by SIRE. Because the relative contributions of genetic, biological, and social drivers of cancer aetiology remain unclear, approaches aimed at reducing inequities remain inadequate.
Barriers and opportunities
Research to address cancer inequities has suffered from a number of limitations:
Firstly, prior approaches have been siloed within disciplines and have not leveraged data addressing the multifactorial contributions of genetics, biology, demographics, social drivers and circumstances, contextual factors, and health care delivery.
Secondly, the definition of groups being compared in studies of cancer inequities have been largely based on SIRE. Thoughtful consideration of the groups of interest, including definitions based on genetic ancestry or multivariate features that include social position or circumstances, may be required.
Finally, most of the work that has informed our understanding of cancer aetiology has been undertaken in European ancestry populations. New modalities and technologies for prevention, early detection, screening, and treatment have largely not been developed or tested in diverse populations. As a result, these previous modalities and technologies may have created or exacerbated health inequities.
To optimise the generalisability and impact of approaches addressing inequities, this challenge requires diverse data and data collection infrastructures, transdisciplinary methods to address the complex, multifactorial nature of cancer inequities.
Examples of the types of questions that could be addressed in this challenge include but are not limited to:
- What is the relative contribution of genetics, biology, social determinants, and individual-level risk factors on inequities or disparities in cancer risk and outcome?
- Do genetic factors modify the effect of social inequities in determining cancer risk and outcomes?
- Among self-identified race and ethnicity, genetic ancestry, multifactor/multilevel indices, or other novel metrics of group membership, what is the optimal measure to assess differences, inequities, or disparities in cancer risk or outcome?
- Can combinations of genetics, genomics, exposures, risk factors, demographics, biological markers, tumour markers, tumour phenotypes, or other variables be used to define population subgroups that will optimally benefit from interventions that reduce inequities or disparities in cancer outcomes?
Teams may choose to develop and evaluate novel metrics for social determinants that can be translated into intervention and go beyond descriptive analyses.
Vision and Impact
This challenge seeks to generate functional and mechanistic insights into cancer inequities by generating new transdisciplinary approaches applied in diverse populations.
An interdisciplinary team that represents diverse sectors, including genetics, biology, social and population science, health care delivery, health economics, diagnostics, biostatistics, bioinformatics, artificial intelligence, and others will be required to address this challenge. Applicants are strongly encouraged to establish global collaborations to generate knowledge that will be applicable worldwide.
This challenge will lay the groundwork for the development, evaluation, and implementation of future prevention, early detection, and treatment strategies to achieve equity in cancer outcomes for all people.
Plain language summary: Why cancer inequities?
Inequities in cancer prevention, screening and treatment lead to differences in cancer incidence and mortality and are major public-health concerns.
Although most inequities are strongly influenced by social determinants and circumstances - for example when inadequate access to health care results in delayed diagnosis - data suggest that genetics and biology also have a role.
Prior research to address cancer inequities has several limitations. For example, approaches haven’t considered the different contributions of genetics, biology, demographics, social drivers and circumstances, and health care delivery. In addition, most of the work that has informed understanding of what causes cancer has been done in European-ancestry populations and therefore might not be applicable to non-European populations. Similarly, most new technologies for cancer prevention, early detection, screening and treatment have not been developed or tested in diverse populations.
This challenge seeks to understand the relative contributions of genetics, biology and social drivers on cancer causes, to provide foundational knowledge for developing novel approaches to achieve equity in cancer outcomes for all people.