Literature DB >> 22984365

Population-based screening in the era of genomics.

Nora Pashayan1, Paul Pharoah.   

Abstract

To date, risk profiles based on the known common susceptibility variants have limited value in predicting risk of disease but they could be used for risk stratification in prevention programmes at population level. We illustrate the potential utility of polygenic risk stratification using the case of population-based screening for prostate and breast cancer. We compared the number of individuals eligible for screening and the number of cases potentially detectable by screening in a population undergoing screening based on age alone with a population undergoing stratified screening based on age and polygenic risk profile. Stratified screening strategy based on age and genetic risk would potentially improve the efficiency of screening programmes and reduce their adverse consequences. Organisational, ethical, legal and social issues need to be addressed before stratified screening programmes could be implemented.

Entities:  

Year:  2012        PMID: 22984365      PMCID: PMC3442228          DOI: 10.2217/pme.12.40

Source DB:  PubMed          Journal:  Per Med        ISSN: 1741-0541            Impact factor:   2.512


  17 in total

1.  Performance of common genetic variants in breast-cancer risk models.

Authors:  Sholom Wacholder; Patricia Hartge; Ross Prentice; Montserrat Garcia-Closas; Heather Spencer Feigelson; W Ryan Diver; Michael J Thun; David G Cox; Susan E Hankinson; Peter Kraft; Bernard Rosner; Christine D Berg; Louise A Brinton; Jolanta Lissowska; Mark E Sherman; Rowan Chlebowski; Charles Kooperberg; Rebecca D Jackson; Dennis W Buckman; Peter Hui; Ruth Pfeiffer; Kevin B Jacobs; Gilles D Thomas; Robert N Hoover; Mitchell H Gail; Stephen J Chanock; David J Hunter
Journal:  N Engl J Med       Date:  2010-03-18       Impact factor: 91.245

Review 2.  The genetic epidemiology of cancer: interpreting family and twin studies and their implications for molecular genetic approaches.

Authors:  N Risch
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2001-07       Impact factor: 4.254

3.  Maximising benefit and minimising harm of screening.

Authors:  J A M Gray; J Patnick; R G Blanks
Journal:  BMJ       Date:  2008-03-01

Review 4.  Genome-based prediction of common diseases: advances and prospects.

Authors:  A Cecile J W Janssens; Cornelia M van Duijn
Journal:  Hum Mol Genet       Date:  2008-10-15       Impact factor: 6.150

5.  Polygenes, risk prediction, and targeted prevention of breast cancer.

Authors:  Paul D P Pharoah; Antonis C Antoniou; Douglas F Easton; Bruce A J Ponder
Journal:  N Engl J Med       Date:  2008-06-26       Impact factor: 91.245

6.  Translating genomics into improved population screening: hype or hope?

Authors:  Nora Pashayan; Paul Pharoah
Journal:  Hum Genet       Date:  2011-04-12       Impact factor: 4.132

7.  Clinical utility of five genetic variants for predicting prostate cancer risk and mortality.

Authors:  Claudia A Salinas; Joseph S Koopmeiners; Erika M Kwon; Liesel FitzGerald; Daniel W Lin; Elaine A Ostrander; Ziding Feng; Janet L Stanford
Journal:  Prostate       Date:  2009-03-01       Impact factor: 4.104

8.  Treatment and survival outcomes in young men diagnosed with prostate cancer: a Population-based Cohort Study.

Authors:  Daniel W Lin; Michael Porter; Bruce Montgomery
Journal:  Cancer       Date:  2009-07-01       Impact factor: 6.860

9.  Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk.

Authors:  Hana Lango; Colin N A Palmer; Andrew D Morris; Eleftheria Zeggini; Andrew T Hattersley; Mark I McCarthy; Timothy M Frayling; Michael N Weedon
Journal:  Diabetes       Date:  2008-06-30       Impact factor: 9.461

Review 10.  Translating genomics into improved healthcare.

Authors:  Aroon D Hingorani; Tina Shah; Meena Kumari; Reecha Sofat; Liam Smeeth
Journal:  BMJ       Date:  2010-11-05
View more
  11 in total

1.  Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer.

Authors:  Montserrat Garcia-Closas; Necdet Burak Gunsoy; Nilanjan Chatterjee
Journal:  J Natl Cancer Inst       Date:  2014-11-12       Impact factor: 13.506

Review 2.  Genetic architecture of colorectal cancer.

Authors:  Ulrike Peters; Stephanie Bien; Niha Zubair
Journal:  Gut       Date:  2015-07-17       Impact factor: 23.059

3.  Personalised medicine, disease prevention, and the inverse care law: more harm than benefit?

Authors:  Jack E James
Journal:  Eur J Epidemiol       Date:  2014-04-12       Impact factor: 8.082

4.  Epigenome-wide association studies for breast cancer risk and risk factors.

Authors:  Annelie Johansson; James M Flanagan
Journal:  Trends Cancer Res       Date:  2017

Review 5.  Do Health Professionals Need Additional Competencies for Stratified Cancer Prevention Based on Genetic Risk Profiling?

Authors:  Susmita Chowdhury; Lidewij Henneman; Tom Dent; Alison Hall; Alice Burton; Paul Pharoah; Nora Pashayan; Hilary Burton
Journal:  J Pers Med       Date:  2015-06-09

Review 6.  The Human Genome Project, and recent advances in personalized genomics.

Authors:  Brenda J Wilson; Stuart G Nicholls
Journal:  Risk Manag Healthc Policy       Date:  2015-02-16

Review 7.  Metabolomics for the masses: The future of metabolomics in a personalized world.

Authors:  Drupad K Trivedi; Katherine A Hollywood; Royston Goodacre
Journal:  New Horiz Transl Med       Date:  2017-03

8.  The economic case for precision medicine.

Authors:  Sean P Gavan; Alexander J Thompson; Katherine Payne
Journal:  Expert Rev Precis Med Drug Dev       Date:  2018-01-08

Review 9.  Implementing risk-stratified screening for common cancers: a review of potential ethical, legal and social issues.

Authors:  A E Hall; S Chowdhury; N Hallowell; N Pashayan; T Dent; P Pharoah; H Burton
Journal:  J Public Health (Oxf)       Date:  2013-08-28       Impact factor: 2.341

10.  Health care professionals' attitudes towards population-based genetic testing and risk-stratification for ovarian cancer: a cross-sectional survey.

Authors:  Katie E J Hann; Lindsay Fraser; Lucy Side; Sue Gessler; Jo Waller; Saskia C Sanderson; Madeleine Freeman; Ian Jacobs; Anne Lanceley
Journal:  BMC Womens Health       Date:  2017-12-16       Impact factor: 2.809

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.