Evidence map›Paper›PMID 32071122›Full record

ArticleCancer prevention research (Philadelphia, Pa.)2020

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

Catherine L Saunders, Britt Kilian, Deborah J Thompson, Luke J McGeoch, Simon J Griffin, Antonis C Antoniou, Jon D Emery, Fiona M Walter, Joe Dennis, Xin Yang and 1 more

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Cancer prevention research (Philadelphia, Pa.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Delphi Initiative for Early-Onset Colorectal Cancer (DIRECt) International Management Guidelines.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2023
    Guideline
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Future of Colorectal Cancer Screening: From One-Size-FITs-All to Tailor-Made.Frontiers in gastroenterology (Lausanne, Switzerland) · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 4 countries.

Catherine L SaundersThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Britt KilianThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-1493-2768
Deborah J ThompsonCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom.ORCID 0000-0003-1465-5799
Luke J McGeochSchool of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-1109-0238
Simon J GriffinThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-2157-4797
Antonis C AntoniouCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom.ORCID 0000-0001-9223-3116
Jon D EmeryDepartment of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia.ORCID 0000-0002-5274-6336
Fiona M WalterThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-7191-6476
Joe DennisCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom.ORCID 0000-0003-4591-1214
Xin YangCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, Wort's Causeway, Cambridge, United Kingdom.
Juliet A Usher-SmithThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. jau20@medschl.cam.ac.uk.
University of Cambridge · GBMRC Epidemiology Unit · GBVictorian Comprehensive Cancer Centre · AU

Funding

Cancer Research UK 20861Cancer Research UK 21464Cancer Research UK A16563Cancer Research UK A20861Cancer Research UK A21464Cancer Research UK C12292/A20861Cancer Research UK C1287/A16563Cancer Research UK C55650/A21464Medical Research Council MC_UU_00006/6Medical Research Council MC_UU_12015/4
6 · The paper itself

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 (

Indexed as

Polymorphism, Single NucleotideAdultAgedAge FactorsArea Under CurveBiological Specimen BanksColorectal NeoplasmsEthnicityFemaleHumansIncidenceMaleMiddle AgedModels, GeneticRegistriesRisk

Identifiers

PMID32071122
PMCPMC7610623
OpenAlexW3007583505

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.