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Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies.
Hopper, John L; Li, Shuai; MacInnis, Robert J; Dowty, James G; Nguyen, Tuong L; Bui, Minh; Dite, Gillian S; Esser, Vivienne F C; Ye, Zhoufeng; Makalic, Enes; Schmidt, Daniel F; Goudey, Benjamin; Alpen, Karen; Kapuscinski, Miroslaw; Win, Aung Ko; Dugué, Pierre-Antoine; Milne, Roger L; Jayasekara, Harindra; Brooks, Jennifer D; Malta, Sue; Calais-Ferreira, Lucas; Campbell, Alexander C; Young, Jesse T; Nguyen-Dumont, Tu; Sung, Joohon; Giles, Graham G; Buchanan, Daniel; Winship, Ingrid; Terry, Mary Beth; Southey, Melissa C; Jenkins, Mark A.
Afiliação
  • Hopper JL; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Li S; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • MacInnis RJ; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Dowty JG; Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
  • Nguyen TL; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
  • Bui M; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Dite GS; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Esser VFC; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Ye Z; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Makalic E; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Schmidt DF; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Goudey B; Genetic Technologies Ltd., Fitzroy, Victoria, Australia.
  • Alpen K; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Kapuscinski M; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Win AK; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Dugué PA; Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia.
  • Milne RL; ARC Training Centre in Cognitive Computing for Medical Technologies, University of Melbourne, Carlton, Victoria, Australia.
  • Jayasekara H; The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Brooks JD; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Malta S; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Calais-Ferreira L; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Campbell AC; University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia.
  • Young JT; Genetic Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia.
  • Nguyen-Dumont T; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Sung J; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
  • Giles GG; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Buchanan D; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Winship I; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
  • Terry MB; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Southey MC; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
  • Jenkins MA; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Genet Epidemiol ; 2024 Mar 19.
Article em En | MEDLINE | ID: mdl-38504141
ABSTRACT
Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Genet Epidemiol Assunto da revista: EPIDEMIOLOGIA / GENETICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Genet Epidemiol Assunto da revista: EPIDEMIOLOGIA / GENETICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Austrália