Towards implementation of comprehensive breast cancer risk prediction tools in health care for personalised prevention.

Advances in knowledge about breast cancer risk factors have led to the development of more comprehensive risk models. These integrate information on a variety of risk factors such as lifestyle, genetics, family history, and breast density. These risk models have the potential to deliver more personalised breast cancer prevention. This is through improving accuracy of risk estimates, enabling more effective targeting of preventive options and creating novel prevention pathways through enabling risk estimation in a wider variety of populations than currently possible. The systematic use of risk tools as part of population screening programmes is one such example. A clear understanding of how such tools can contribute to the goal of personalised prevention can aid in understanding and addressing barriers to implementation. In this paper we describe how emerging models, and their associated tools can contribute to the goal of personalised healthcare for breast cancer through health promotion, early disease detection (screening) and improved management of women at higher risk of disease. We outline how addressing specific challenges on the level of communication, evidence, evaluation, regulation, and acceptance, can facilitate implementation and uptake.

Risk stratification, genomic data and the law.

Risk prediction models have a key role in stratified disease prevention, and the incorporation of genomic data into these models promises more effective personalisation. Although the clinical utility of incorporating genomic data into risk prediction tools is increasingly compelling, at least for some applications and disease types, the legal and regulatory implications have not been examined and have been overshadowed by discussions about clinical and scientific utility and feasibility. We held a workshop to explore relevant legal and regulatory perspectives from four EU Member States: France, Germany, the Netherlands and the UK. While we found no absolute prohibition on the use of such data in those tools, there are considerable challenges. Currently, these are modest and result from genomic data being classified as sensitive data under existing Data Protection regulation. However, these challenges will increase in the future following the implementation of EU Regulations on data protection which take effect in 2018, and reforms to the governance of the manufacture, development and use of in vitro diagnostic devices to be implemented in 2022. Collectively these will increase the regulatory burden placed on these products as risk stratification tools will be brought within the scope of these new Regulations. The failure to respond to the challenges posed by the use of genomic data in disease risk stratification tools could therefore prove costly to those developing and using such tools.

Implications of using whole genome sequencing to test unselected populations for high risk breast cancer genes: a modelling study.

BACKGROUND: The decision to test for high risk breast cancer gene mutations is traditionally based on risk scores derived from age, family and personal cancer history. Next generation sequencing technologies such as whole genome sequencing (WGS) make wider population testing more feasible. In the UK's 100,000 Genomes Project, mutations in 16 genes including BRCA1 and BRCA2 are to be actively sought regardless of clinical presentation. The implications of deploying this approach at scale for patients and clinical services are unclear. In this study we aimed to model the effect of using WGS to test an unselected UK population for high risk BRCA1 and BRCA2 gene variants to inform the debate around approaches to secondary genomic findings. METHODS: We modelled the test performance of WGS for identifying pathogenic BRCA1 and BRCA2 mutations in an unselected hypothetical population of 100,000 UK women, using published literature to derive model input parameters. We calculated analytic and clinical validity, described potential health outcomes and highlighted current areas of uncertainty. We also performed a sensitivity analysis in which we re-ran the model 100,000 times to investigate the effect of varying input parameters. RESULTS: In our models WGS was predicted to identify correctly 93 pathogenic BRCA1 mutations and 151 BRCA2 mutations in 120 and 200 women respectively, resulting in an analytic sensitivity of 75.5-77.5 %. Of 244 women with identified pathogenic mutations, we estimated that 132 (range 121-198) would develop breast cancer, so could potentially be helped by intervention. We also predicted that breast cancer would occur in 41 women (range 36-62) incorrectly identified with no pathogenic mutations and in 12,460 women without BRCA1 or BRCA2 mutations. There was considerable uncertainty about the penetrance of mutations in people without a family history of disease and the appropriate threshold of absolute disease risk for clinical action, which impacts on judgements about the clinical utility of intervention. CONCLUSIONS: This simple model demonstrates the need for robust processes to support the testing for secondary genomic findings in unselected populations that acknowledge levels of uncertainty about the clinical validity and clinical utility of testing positive for a cancer risk gene.

A framework for the prioritization of investment in the provision of genetic tests.

BACKGROUND: The UK Genetic Testing Network (UKGTN) established a process for the evaluation of genetic tests for entry onto the National Health Service (NHS) Directory of Molecular Genetic Testing. The Network requested the development and piloting of a prioritization framework that could be used for the commissioning of genetic tests by the NHS. METHODS: A selected working group developed and piloted a multi-criteria prioritization process using 10 genetic tests evaluated by the UKGTN. RESULTS: The framework was able to rank the 10 genetic tests used in the pilot. The rankings were also consistent with the commissioning recommendations for these genetic tests by the UKGTN. CONCLUSION: A set of criteria for the prioritization of genetic tests has been developed. The results from the pilot suggest that the methodology is valid and robust but requires considerable resources to implement. Further development of the process is needed before the framework could be used to influence commissioning decisions for clinical genetic services in the NHS.

HER2 status in breast cancer--an example of pharmacogenetic testing.

The development of new drugs and associated pharmacogenetic tests will provide an increasing number of challenges to health care systems. In particular, how to evaluate their benefits, prioritize for commissioning purposes and implement a service to provide them in a timely manner. This paper presents an overview of HER2 testing for trastuzumab (Herceptin) treatment in breast cancer cases. Immunohistochemistry and fluorescence in situ hybridization laboratory techniques are described and their HER2 testing performances are compared. Future options for the national provision of HER2 testing by the National Health Service in the UK are also discussed.

How can the evaluation of genetic tests be enhanced? Lessons learned from the ACCE framework and evaluating genetic tests in the United Kingdom.

Advances in genetic technology are increasing the availability of genetic tests, not only for rare single gene disorders, but also for common diseases such as breast and colo-rectal cancer. Before there can be widespread uptake of these tests, they must be evaluated to confirm the benefits of their use. But how should genetic tests be evaluated, given the speed at which new tests are emerging? One highly influential approach is the analytic validity, clinical validity, clinical utility and ethical, legal and social issues (ACCE) framework, which has provided a benchmark for the evaluation of genetic tests. The approach has been adopted and adapted by the United Kingdom Genetic Testing Network, with the help of the Public Health Genetics Unit in Cambridge, to evaluate new genetic tests for use in the National Health Service. We discuss a number of conceptual, methodological, and practical issues concerning the evaluation of genetic tests, based on lessons learned from applying the ACCE framework and from the UK experience, and make a number of recommendations to further strengthen the evaluation of genetic tests.