Personalised prevention in breast cancer – the policy landscape
15 December 2017
Breast Cancer Stratification: understanding the determinants of risk and prognosis of molecular subtypes (B-CAST) is a multicentre European Commission project with the aim of gaining much more in-depth knowledge into the factors that influence breast cancer. The hope is to use this knowledge to produce tools that will allow more individual-specific information to be generated, which in turn could inform more accurate prevention and treatment strategies.
As part the B-CAST research consortium, PHG Foundation is examining capacity development for personalised breast cancer prevention and early detection.
Our new report, Personalised prevention in breast cancer: the policy landscape, submitted to the consortium at the beginning of December, sets out our analysis of current practice and policy based on a review of the literature and consultation with international experts. This includes an overview of breast cancer and what is currently known in relation to factors that cause the disease, and approaches for prevention and early detection.
Our new report, submitted to the consortium at the beginning of December, sets out our analysis of current practice and policy...This is just first step in our work on assessing the feasibility of developing personalised prevention strategies specifically for breast cancer.
Prevention strategies vary in different settings, as does the policy environment. Along with a global overview of breast cancer prevention policies, we conducted an in-depth analysis of the current policy environment and prevention pathway in three countries (United Kingdom, Netherlands and Australia). Finally, we examined the current discourse and debate surrounding personalised prevention in the context of the UK and Australia.
This is just first step in our work on assessing the feasibility of developing personalised prevention strategies specifically for breast cancer.
We know a considerable amount about risk factors associated with breast cancer, and on-going research is trying to understand which of these risk factors are important for different sub-types of the disease. Risk factors for breast cancer are often classified as either non-modifiable or modifiable. Non-modifiable risk factors are those that cannot be changed, inherent biological factors (e.g. sex, age and genetics) and life events, such as age of menarche, menopause, parity (number of children) and age at first pregnancy. Modifiable risk factors, mainly external influences that impact on biological factors, can be further divided into those that are related to reproduction and those that are related to general lifestyle. Still, relatively little is currently known about the relative contribution of different risk factors to development of breast cancer in individuals, and indeed their impact on different subtypes of the disease.
The ability to enable personalised prevention requires an understanding of which of these multiple risk factors are more important in particular sub-populations. In addition, moving away from the ‘one-size fits all’ approach requires that a suite of preventative options should be available for those at different levels of risk. In short, the provision of interventions to prevent breast cancer is to some extent linked with our ability to accurately estimate risk, and to link factors that increase risk in individuals to appropriate interventions.
Currently, in the absence of mechanisms that can be applied to the general population to estimate their risk and provide tailored prevention strategies, the main approach to risk reduction is through general health messages. Health promotion aims to inform all women of their risk and empower them to take action to reduce their own risk.
That said, preventative interventions are already targeted to some extent, for example offering screening to women between the ages of 50-70 years (the age group in which breast cancer incidence is highest) in order to identify the disease earlier. This is based on the rationale that early identification and treatment has a positive impact on survival. Also at higher risk are those women who have a family history of breast cancer or possess particular genetic mutations that confer significantly increased risk. Options for these high-risk women such as more frequent screening, chemoprevention and mastectomy are available. However, identifying these women is still a difficult task, especially as they form a relatively small proportion of the population.
These approaches, whilst making some distinction between known high risk and assumed population risk women, are still targeting only the extremes of the risk distribution and are not really personalised. For example, risk factors other than age are not considered in those who are offered screening. All women in this age bracket are offered the same screening pathway regardless of the fact that there may be differences in their risk profile as a result of genetic and/or lifestyle factors. Although women possessing mutations in BRCA gene are at higher risk of developing breast cancer, this risk is likely to be influenced by other factors (e.g. other genes or lifestyle) and knowledge about these might still allow better tailoring of their care.
Our research suggests there is little in the way of a coherent and consistent policy approach specifically focused on the personalised prevention of breast cancer.
Our analysis of the policy landscape shows that there is a desire to harness the shifting technological potential to drive more sustainable healthcare by improving personalised prevention for breast cancer. As such, personalised healthcare and personalised prevention are gaining prominence in policy debates. Yet our research suggests there is little in the way of a coherent and consistent policy approach specifically focused on the personalised prevention of breast cancer.
What role does technology have to play?
Recent advances in science and technology are contributing to our ability to characterise individuals as well as develop novel therapies. Detailed characterisation of individuals requires tools to accurately measure biomarkers (e.g. genes, proteins and metabolites) and phenotypes (e.g. height, weight, breast density) as well as external exposures (e.g. diet, level of physical activity etc.). Developments in genomics, imaging and wearable technologies are enabling much more accurate characterisation of individual behaviours and exposures. This, coupled with advances in mechanistic and machine learning models, can enable efficient analysis and modelling of this data for more accurate prediction of future development of disease.
So the question is: given all that we know now, and considering what the future may bring, what are the current and potential future opportunities to make breast cancer prevention more personalised? Genomics appears to offer possibilities, given the growing knowledge about the contribution of genes that confer increased risk. We are increasingly able to stratify women into different risk categories on the basis of genetic factors - but this is only part of the picture. Can we also harness novel technologies to inform us of the important lifestyle factors that are impacting on risk? Going further, is it feasible to imagine a future where we offer sub-groups of women tailored preventative strategies on the basis of this knowledge? This is a rapidly evolving area, and in a relatively short space of time it is possible that breast cancer prevention could become much more personalised.
The report is freely available to read here