Evidence map›Paper›PMID 29403313›Full record

ArticleClinical epidemiology2018

Strongly enhanced colorectal cancer risk stratification by combining family history and genetic risk score.

Korbinian Weigl, Jenny Chang-Claude, Phillip Knebel, Li Hsu, Michael Hoffmeister, Hermann Brenner

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05277116 (The Electronic Medical Records and GEnomics), which is not on this map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
9.5field-weighted citation impact, top 1% 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.

NCT05277116 naactive not recruitingnot on this mapstarted 2022, after this paper: background citation

The Electronic Medical Records and GEnomics (eMERGE) Network Genomic Risk Assessment

TypeinterventionalSponsorVanderbilt University Medical CenterRan2022 to 2030Enrolled26,877ConditionsGenetic DiseaseArmsGenome Informed Risk Assessment (GIRA) report
3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.

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  11. 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
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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

6 authors at 4 institutions in 2 countries.

Korbinian WeiglDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg.
Jenny Chang-ClaudeUnit of Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg.
Phillip KnebelDepartment for General, Visceral and Transplantation Surgery, University Heidelberg, Heidelberg, Germany.
Li HsuPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Michael HoffmeisterDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg.
Hermann BrennerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg.
German Cancer Research Center · DEHeidelberg University · DEFred Hutch Cancer Center · USUniversität Hamburg · DE

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
NCI NIH HHS R01 CA059045NCI NIH HHS R01 CA195789NCI NIH HHS U01 CA137088NCI NIH HHS U01 CA185094
6 · The paper itself

Abstract

BACKGROUND AND

aimFamily history (FH) and genetic risk scores (GRSs) are increasingly used for risk stratification for colorectal cancer (CRC) screening. However, they were mostly considered alternatively rather than jointly. The aim of this study was to assess the potential of individual and joint risk stratification for CRC by FH and GRS. PATIENTS AND

methodsA GRS was built based on the number of risk alleles in 53 previously identified single-nucleotide polymorphisms among 2,363 patients with a first diagnosis of CRC and 2,198 controls in DACHS [colorectal cancer: chances for prevention through screening], a population-based case-control study in Germany. Associations between GRS and FH with CRC risk were quantified by multiple logistic regression.

resultsA total of 316 cases (13.4%) and 214 controls (9.7%) had a first-degree relative (FDR) with CRC (adjusted odds ratio [aOR] 1.86, 95% CI 1.52-2.29). A GRS in the highest decile was associated with a 3.0-fold increased risk of CRC (aOR 3.00, 95% CI 2.24-4.02) compared with the lowest decile. This association was tentatively more pronounced in older age groups. FH and GRS were essentially unrelated, and their joint consideration provided more accurate risk stratification than risk stratification based on each of the variables individually. For example, risk was 6.1-fold increased in the presence of both FH in a FDR and a GRS in the highest decile (aOR 6.14, 95% CI 3.47-10.84) compared to persons without FH and a GRS in the lowest decile.

conclusionBoth FH and the so far identified genetic variants carry essentially independent risk information and in combination provide great potential for CRC risk stratification.

Indexed as

colorectal neoplasmscommon genetic variantsfamilial risksingle-nucleotide polymorphisms

Identifiers

PMID29403313
PMCPMC5783152
OpenAlexW2784045407

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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.