Evidence map›Paper›PMID 31800541›Full record

Observational studyClinical and translational gastroenterology2019

Head-to-Head Comparison of Family History of Colorectal Cancer and a Genetic Risk Score for Colorectal Cancer Risk Stratification.

Korbinian Weigl, Li Hsu, Phillip Knebel, Michael Hoffmeister, Maria Timofeeva, Susan Farrington, Malcolm Dunlop, Hermann Brenner

Abstract readComparative StudyObservational Study
In one paragraph

Observational study in Clinical and translational gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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.

Korbinian WeiglDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Li HsuPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Phillip KnebelDepartment for General, Visceral and Transplantation Surgery, University Heidelberg, Germany.
Michael HoffmeisterDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Maria TimofeevaColon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and MRC Human Genetics Unit, Western General Hospital Colon Cancer Genetics Group, Edinburgh, Scotland, United Kingdom.
Susan FarringtonColon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and MRC Human Genetics Unit, Western General Hospital Colon Cancer Genetics Group, Edinburgh, Scotland, United Kingdom.
Malcolm DunlopColon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and MRC Human Genetics Unit, Western General Hospital Colon Cancer Genetics Group, Edinburgh, Scotland, United Kingdom.
Hermann BrennerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Funding

Molecular pathological epidemiology of colorectal cancerU01CA137088 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETERS, ULRIKE · 2009 to 2018
$21.8M
Genome-Wide Association Study of Nonsynonymous SNPs in Colon CancerR01CA059045 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETERS, ULRIKE · 1994 to 2011
$11.5M
Colorectal Tumor Risk Prediction in the PLCO TrialU01CA185094 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETERS, ULRIKE · 2014 to 2016
$2.0M
Statistical Methods for Genetic Epidemiology StudiesR01CA195789 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI HSU, LI · 2016 to 2019
$1.6M
Cancer Research UK 18927Cancer Research UK C348/A18927Medical Research Council MR/K018647/1NCI NIH HHS R01 CA059045NCI NIH HHS R01 CA195789NCI NIH HHS U01 CA137088NCI NIH HHS U01 CA185094Wellcome Trust
6 · The paper itself

Abstract

objectivesFamily history (FH) is associated with increased risk of colorectal cancer (CRC). We aimed to examine the potential for CRC risk stratification by known common genetic variants beyond FH in a large population-based case-control study from Germany.

methodsFour thousand four hundred forty-seven cases and 3,480 controls recruited in 2003-2016 were included for whom comprehensive interview, medical, and genomic data were available. Associations with CRC risk were estimated from multiple logistic regression models for FH and a genetic risk score (GRS) based on 90 previously identified risk variants.

resultsCRC in a first-degree relative was associated with a 1.71-fold (95% confidence interval 1.47-2.00) increase in CRC risk. A higher risk increase (odds ratio 2.06, 95% confidence interval 1.78-2.39) was estimated for the GRS when it was dichotomized at a cutoff yielding the same positivity rate as FH among controls. Furthermore, the GRS provides substantial additional risk stratification in both people with and especially without FH. Equal or even slightly higher risks were observed for participants without FH with a GRS in the upper 20% compared with participants with FH with a GRS below median. The observed patterns were confirmed in a replication study. DISCUSSION: In contrast to common perception, known genetic variants do not primarily reflect some minor share of the familial excess risk of CRC, but rather reflect a substantial share of risk independent of FH.

Indexed as

Genetic Predisposition to DiseaseMedical History TakingAgedCase-Control StudiesColorectal NeoplasmsFemaleFollow-Up StudiesGenotyping TechniquesHumansMaleMiddle AgedOdds RatioPolymorphism, Single NucleotideRisk AssessmentRisk Factors

Identifiers

PMID31800541
PMCPMC6970558

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Registered trials

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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.