Literature DB >> 32071122

External Validation of Risk Prediction Models Incorporating Common Genetic Variants for Incident Colorectal Cancer Using UK Biobank.

Catherine L Saunders1, Britt Kilian1, Deborah J Thompson2, Luke J McGeoch3, Simon J Griffin1, Antonis C Antoniou2, Jon D Emery4, Fiona M Walter1, Joe Dennis2, Xin Yang2, Juliet A Usher-Smith5.   

Abstract

The aim of this study was to compare and externally validate risk scores developed to predict incident colorectal cancer that include common genetic variants (SNPs), with or without established lifestyle/environmental (questionnaire-based/classical/phenotypic) risk factors. We externally validated 23 risk models from a previous systematic review in 443,888 participants ages 37 to 73 from the UK Biobank cohort who had 6-year prospective follow-up, no prior history of colorectal cancer, and data for incidence of colorectal cancer through linkage to national cancer registries. There were 2,679 (0.6%) cases of incident colorectal cancer. We assessed model discrimination using the area under the operating characteristic curve (AUC) and relative risk calibration. The AUC of models including only SNPs increased with the number of included SNPs and was similar in men and women: the model by Huyghe with 120 SNPs had the highest AUC of 0.62 [95% confidence interval (CI), 0.59-0.64] in women and 0.64 (95% CI, 0.61-0.66) in men. Adding phenotypic risk factors without age improved discrimination in men but not in women. Adding phenotypic risk factors and age increased discrimination in all cases (P < 0.05), with the best performing models including SNPs, phenotypic risk factors, and age having AUCs between 0.64 and 0.67 in women and 0.67 and 0.71 in men. Relative risk calibration varied substantially across the models. Among middle-aged people in the UK, existing polygenic risk scores discriminate moderately well between those who do and do not develop colorectal cancer over 6 years. Consideration should be given to exploring the feasibility of incorporating genetic and lifestyle/environmental information in any future stratified colorectal cancer screening program. ©2020 American Association for Cancer Research.

Entities:  

Year:  2020        PMID: 32071122      PMCID: PMC7610623          DOI: 10.1158/1940-6207.CAPR-19-0521

Source DB:  PubMed          Journal:  Cancer Prev Res (Phila)        ISSN: 1940-6215


  36 in total

1.  Colorectal cancer predicted risk online (CRC-PRO) calculator using data from the multi-ethnic cohort study.

Authors:  Brian J Wells; Michael W Kattan; Gregory S Cooper; Leila Jackson; Siran Koroukian
Journal:  J Am Board Fam Med       Date:  2014 Jan-Feb       Impact factor: 2.657

Review 2.  Colorectal cancer screening: a global overview of existing programmes.

Authors:  Eline H Schreuders; Arlinda Ruco; Linda Rabeneck; Robert E Schoen; Joseph J Y Sung; Graeme P Young; Ernst J Kuipers
Journal:  Gut       Date:  2015-06-03       Impact factor: 23.059

3.  Incorporating non-genetic risk factors and behavioural modifications into risk prediction models for colorectal cancer.

Authors:  Jane M Yarnall; Daniel J M Crouch; Cathryn M Lewis
Journal:  Cancer Epidemiol       Date:  2013-01-30       Impact factor: 2.984

4.  A model to determine colorectal cancer risk using common genetic susceptibility loci.

Authors:  Li Hsu; Jihyoun Jeon; Hermann Brenner; Stephen B Gruber; Robert E Schoen; Sonja I Berndt; Andrew T Chan; Jenny Chang-Claude; Mengmeng Du; Jian Gong; Tabitha A Harrison; Richard B Hayes; Michael Hoffmeister; Carolyn M Hutter; Yi Lin; Reiko Nishihara; Shuji Ogino; Ross L Prentice; Fredrick R Schumacher; Daniela Seminara; Martha L Slattery; Duncan C Thomas; Mark Thornquist; Polly A Newcomb; John D Potter; Yingye Zheng; Emily White; Ulrike Peters
Journal:  Gastroenterology       Date:  2015-02-13       Impact factor: 22.682

5.  Skin Pigmentation and Risk of Hearing Loss in Women.

Authors:  Brian M Lin; Wen-Qing Li; Sharon G Curhan; Konstantina M Stankovic; Abrar A Qureshi; Gary C Curhan
Journal:  Am J Epidemiol       Date:  2017-07-01       Impact factor: 4.897

Review 6.  Selecting lung cancer screenees using risk prediction models-where do we go from here.

Authors:  Martin C Tammemägi
Journal:  Transl Lung Cancer Res       Date:  2018-06

Review 7.  Current status of screening for colorectal cancer.

Authors:  K Garborg; Ø Holme; M Løberg; M Kalager; H O Adami; M Bretthauer
Journal:  Ann Oncol       Date:  2013-04-25       Impact factor: 32.976

8.  How well does family history predict who will get colorectal cancer? Implications for cancer screening and counseling.

Authors:  David P Taylor; Gregory J Stoddard; Randall W Burt; Marc S Williams; Joyce A Mitchell; Peter J Haug; Lisa A Cannon-Albright
Journal:  Genet Med       Date:  2011-05       Impact factor: 8.822

9.  Prediction of Colorectal Cancer Risk Using a Genetic Risk Score: The Korean Cancer Prevention Study-II (KCPS-II).

Authors:  Jaeseong Jo; Chung Mo Nam; Jae Woong Sull; Ji Eun Yun; Sang Yeun Kim; Sun Ju Lee; Yoon Nam Kim; Eun Jung Park; Heejin Kimm; Sun Ha Jee
Journal:  Genomics Inform       Date:  2012-09-28

10.  A colorectal cancer prediction model using traditional and genetic risk scores in Koreans.

Authors:  Keum Ji Jung; Daeyoun Won; Christina Jeon; Soriul Kim; Tae Il Kim; Sun Ha Jee; Terri H Beaty
Journal:  BMC Genet       Date:  2015-05-09       Impact factor: 2.797

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  4 in total

Review 1.  Risk-stratified strategies in population screening for colorectal cancer.

Authors:  Iris Lansdorp-Vogelaar; Reinier Meester; Lucie de Jonge; Andrea Buron; Ulrike Haug; Carlo Senore
Journal:  Int J Cancer       Date:  2021-09-06       Impact factor: 7.316

2.  The Costs and Benefits of Risk Stratification for Colorectal Cancer Screening Based On Phenotypic and Genetic Risk: A Health Economic Analysis.

Authors:  Chloe Thomas; Olena Mandrik; Catherine L Saunders; Deborah Thompson; Sophie Whyte; Simon Griffin; Juliet A Usher-Smith
Journal:  Cancer Prev Res (Phila)       Date:  2021-05-26

3.  External validation of models for predicting risk of colorectal cancer using the China Kadoorie Biobank.

Authors:  Roxanna E Abhari; Blake Thomson; Ling Yang; Iona Millwood; Yu Guo; Xiaoming Yang; Jun Lv; Daniel Avery; Pei Pei; Peng Wen; Canqing Yu; Yiping Chen; Junshi Chen; Liming Li; Zhengming Chen; Christiana Kartsonaki
Journal:  BMC Med       Date:  2022-09-08       Impact factor: 11.150

4.  The SCRIPT trial: study protocol for a randomised controlled trial of a polygenic risk score to tailor colorectal cancer screening in primary care.

Authors:  Sibel Saya; Lucy Boyd; Patty Chondros; Mairead McNamara; Michelle King; Shakira Milton; Richard De Abreu Lourenco; Malcolm Clark; George Fishman; Julie Marker; Cheri Ostroff; Richard Allman; Fiona M Walter; Daniel Buchanan; Ingrid Winship; Jennifer McIntosh; Finlay Macrae; Mark Jenkins; Jon Emery
Journal:  Trials       Date:  2022-09-27       Impact factor: 2.728

  4 in total

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