Evidence map›Paper›PMID 20437058›Full record

ArticleHuman genetics2010

The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer.

Steven J Hawken, Celia M T Greenwood, Thomas J Hudson, Rafal Kustra, John McLaughlin, Quanhe Yang, Brent W Zanke, Julian Little

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Human genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Genetic variants in IL-6/JAK/STAT3 pathway and the risk of CRC.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    Pooled it
  3. Pooled it
  4. Effect of Proliferator-Activated Receptor-γ Pro12Ala Polymorphism on Colorectal Cancer Risk: A Meta-Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2015
    Pooled it
  5. Pooled it
  6. Review
  7. Article
  8. Review
  9. Article
  10. Cost-Effectiveness of Personalized Screening for Colorectal Cancer Based on Polygenic Risk and Family History.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. How can polygenic inheritance be used in population screening for common diseases?Genetics in medicine : official journal of the American College of Medical Genetics · 2013
    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

8 authors.

Steven J HawkenDepartment of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada. shawken@ohri.ca
Celia M T Greenwood
Thomas J Hudson
Rafal Kustra
John McLaughlin
Quanhe Yang
Brent W Zanke
Julian Little

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., approximately 140-160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual's CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with CRC before the question of the potential utility of germline genomic profiling can be definitively answered.

Indexed as

DNA FingerprintingEarly Detection of CancerGenetic TestingPenetranceColorectal NeoplasmsHumansPredictive Value of TestsRiskSensitivity and Specificity

Identifiers

PMID20437058
PMCPMC2885303

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.