Evidence map›Paper›PMID 29890168›Full record

ArticleThe Journal of investigative dermatology2018

Assessing the Incremental Contribution of Common Genomic Variants to Melanoma Risk Prediction in Two Population-Based Studies.

Anne E Cust, Martin Drummond, Peter A Kanetsky, Australian Melanoma Family Study Investigators, Leeds Case-Control Study Investigators, Alisa M Goldstein, Jennifer H Barrett, Stuart MacGregor, Matthew H Law, Mark M Iles and 11 more

Abstract read
In one paragraph

Article in The Journal of investigative dermatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

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

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: a randomized controlled trial.Genetics in medicine : official journal of the American College of Medical Genetics · 2021
    Trial
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  8. Article
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  10. Review
  11. Review
  12. Article
  13. Association of Inherited Genetic Variants with Multiple Primary Melanoma.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
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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

21 authors.

Anne E CustCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, Australia. Electronic address: anne.cust@sydney.edu.au.
Martin DrummondCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Peter A KanetskyDepartment of Cancer Epidemiology, Moffitt Cancer Center and Research Institute, Tampa, Florida, USA.
Australian Melanoma Family Study Investigators
Leeds Case-Control Study Investigators
Alisa M GoldsteinHuman Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Jennifer H BarrettSection of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
Stuart MacGregorStatistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Matthew H LawStatistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Mark M IlesSection of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
Minh BuiCentre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Australia.
John L HopperCentre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Australia.
Myriam BrossardINSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, France; Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
Florence DemenaisINSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, France; Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
John C TaylorSection of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
Clive HoggartSection of Paediatrics, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, UK.
Kevin M BrownHuman Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Maria Teresa LandiHuman Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Julia A Newton-BishopSection of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
Graham J MannMelanoma Institute Australia, The University of Sydney, Sydney, Australia; Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia.
D Timothy BishopSection of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.

Funding

Genetic Epidermiology of MelanomaR01CA083115 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BISHOP, DAVID TIMOTHY, ELDER, DAVID ERIC · 2001 to 2017
$13.0M
Cancer Research UK 10589Cancer Research UK 19167Cancer Research UK C588/A19167Medical Research Council MR/L01629X/1NCI NIH HHS R01 CA083115
6 · The paper itself

Abstract

It is unclear to what degree genomic and traditional (phenotypic and environmental) risk factors overlap in their prediction of melanoma risk. We evaluated the incremental contribution of common genomic variants (in pigmentation, nevus, and other pathways) and their overlap with traditional risk factors, using data from two population-based case-control studies from Australia (n = 1,035) and the United Kingdom (n = 1,460) that used the same questionnaires. Polygenic risk scores were derived from 21 gene regions associated with melanoma and odds ratios from published meta-analyses. Logistic regression models were adjusted for age, sex, center, and ancestry. Adding the polygenic risk score to a model with traditional risk factors increased the area under the receiver operating characteristic curve (AUC) by 2.3% (P = 0.003) for Australia and by 2.8% (P = 0.002) for Leeds. Gene variants in the pigmentation pathway, particularly MC1R, were responsible for most of the incremental improvement. In a cross-tabulation of polygenic by traditional tertile risk scores, 59% (Australia) and 49% (Leeds) of participants were categorized in the same (concordant) tertile. Of participants with low traditional risk, 9% (Australia) and 21% (Leeds) had high polygenic risk. Testing of genomic variants can identify people who are susceptible to melanoma despite not having a traditional phenotypic risk profile.

Indexed as

Population GroupsAdolescentAdultAgedAllelesAustraliaEthnicityFemaleGenetic Predisposition to DiseaseHumansMaleMelanomaMiddle AgedPathology, MolecularPolymorphism, GeneticPrognosis

Identifiers

PMID29890168
PMCPMC6249137

What OpenQuestion holds

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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.