Stratified Cancer Screening: The Practicalities of Implementation

PHG Foundation, Cambridge, UK.
Public Health Genomics (Impact Factor: 2.46). 01/2013; 16(3). DOI: 10.1159/000345941
Source: PubMed

ABSTRACT Background: Improving understanding of the genetic basis of disease susceptibility enables us to estimate individuals' risk of developing cancer and offer them disease prevention, including screening, stratified to reflect that risk. Little attention has so far been given to the implementation of stratified screening. This article reviews the issues that would arise in delivering such tailored approaches to prevention in practice. Results: Issues analysed include the organisational context within which implementation of stratified prevention would occur, how the offer of screening would be made, making sure consent is adequately informed, how individuals' risk would be assessed, the age at which risk estimation should occur, and the potential use of genetic data for other purposes. The review also considers how management might differ depending on individuals' risk, how their results would be communicated and their follow-up arranged, and the different issues raised by modification of an existing screening programme, such as that for breast cancer, and the establishment of a new one, for example for prostate cancer. Conclusion: Stratified screening based on genetic testing is a radically new approach to prevention. Various organisational issues would need to be considered before it could be introduced, and a number of questions require further research.

1 Follower
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: There is an opportunity to improve outcomes for ovarian cancer (OC) through advances in risk stratification, early detection and diagnosis. A population-based OC genetic risk prediction and stratification program is being developed. A previous focus group study with individuals from the general population showed support for the proposed program. This qualitative interview study explores the attitudes of women at high risk of OC. Eight women participated in one-on-one, in-depth, semi-structured interviews to explore: experiences of learning of OC risk, risk perceptions, OC knowledge and awareness, and opinions on risk stratification approach. There was evidence of strong support for the proposed program. Benefits were seen as providing reassurance to women at low risk, and reducing worry in women at high risk through appropriate clinical management. Stratification into 'low' and 'high' risk groups was well-received. Participants were more hesitant about stratification to the 'intermediate' risk group. The data suggest formats to effectively communicate OC risk estimates will require careful thought. Interactions with GPs were highlighted as a barrier to OC risk assessment and diagnosis. These results are encouraging for the possible introduction and uptake of a risk prediction and stratification program for OC in the general population.
    Familial Cancer 11/2014; 14(1). DOI:10.1007/s10689-014-9769-5 · 1.62 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Using the principles of public health genomics, we examined the opportunities and challenges of implementing personalized prevention programmes for cancer at the population level. Our model-based estimates indicate that polygenic risk stratification can potentially improve the effectiveness and cost-effectiveness of screening programmes. However, compared with 'one-size-fits-all' screening programmes, personalized screening adds further layers of complexity to the organization of screening services and raises ethical, legal and social challenges. Before polygenic inheritance is translated into population screening strategy, evidence from empirical research and engagement with and education of the public and the health professionals are needed.
    Journal of Internal Medicine 11/2013; 274(5):451-456. DOI:10.1111/joim.12094 · 5.79 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Polygenic profiling and risk stratification for population-based screening for cancer improve the efficiency of the screening programs. Translation of genomics into personalized screening programs requires evidence from empirical research on the balance of benefits and harms of personalized screening, and engagement with the public, professionals and policy makers.
    Personalized Medicine 08/2013; 10(6). DOI:10.2217/pme.13.46 · 1.13 Impact Factor