Evidence map›Paper›PMID 31520533›Full record

ArticleThe British journal of dermatology2020

A risk prediction model for the development of subsequent primary melanoma in a population-based cohort.

A E Cust, C Badcock, J Smith, N E Thomas, L E Haydu, B K Armstrong, M H Law, J F Thompson, P A Kanetsky, C B Begg and 9 more

Open access · greenAbstract read
In one paragraph

Article in The British journal of dermatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.

  1. A systematic review of microsimulation models for skin cancer.BMC medical informatics and decision making · 2025
    Pooled it
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  5. Survival impact of second primary cutaneous and non-cutaneous melanoma in melanoma survivors.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026
    Article
  6. Review
  7. 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
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 7 institutions in 2 countries.

A E CustCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia.ORCID 0000-0002-5331-6370
C BadcockCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia.
J SmithCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia.
N E ThomasLineberger Comprehensive Cancer Center, Chapel Hill, NC, U.S.A.
L E HayduUniversity of Texas MD Anderson Cancer Center, Houston, TX, U.S.A.
B K ArmstrongCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia.
M H LawStatistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID 0000-0002-4303-8821
J F ThompsonMelanoma Institute Australia, The University of Sydney, Sydney, Australia.
P A KanetskyDepartment of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, U.S.A.
C B BeggDepartment of Dermatology, University of North Carolina, Chapel Hill, NC, U.S.A.
Y ShiDepartment of Internal Medicine, University of New Mexico Cancer Center, University of New Mexico, Albuquerque, NM, U.S.A.
A KrickerCancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia.
I OrlowDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, U.S.A.
A SharmaDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, U.S.A.
S YooDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, U.S.A.
S F LeongDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, U.S.A.
M BerwickDepartment of Internal Medicine, University of New Mexico Cancer Center, University of New Mexico, Albuquerque, NM, U.S.A.
D W OllilaLineberger Comprehensive Cancer Center, Chapel Hill, NC, U.S.A.
S LoMelanoma Institute Australia, The University of Sydney, Sydney, Australia.ORCID 0000-0001-5092-5544
The University of Sydney · AUMemorial Sloan Kettering Cancer Center · USUniversity of North Carolina at Chapel Hill · USUniversity of New Mexico · USMoffitt Cancer Center · USQIMR Berghofer Medical Research Institute · AUThe University of Texas MD Anderson Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa A. Troester · 2001 to 2026
$36.3M
Sex Differences in Methylome Alterations and Mutational Burden in Early Stage MelanomaP01CA206980 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI BERWICK, MARIANNE, THOMAS, NANCY E. · 2017 to 2022
$10.1M
Melanoma RAS/BRAF Mutation:Heterogeneity-Risk-PrognosisR01CA112243 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI THOMAS, NANCY E. · 2005 to 2014
$5.4M
A MODEL FOR GENETIC SUSCEPTIBILITY: MELANOMAU01CA083180 · NCI · UNIVERSITY OF NEW MEXICO · PI BERWICK, MARIANNE · 1999 to 2003
$5.2M
Identification of Lethal Melanomas at the Time of DiagnosisR01CA233524 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ANTON-CULVER, HODA A, BEGG, COLIN B · 2020 to 2024
$4.5M
Solar Exposure and Melanoma SurvivalR01CA112524 · NCI · UNIVERSITY OF NEW MEXICO · PI BERWICK, MARIANNE · 2005 to 2009
$2.5M
Epidemiologic Parameters of Rare Cancer Risk FactorsR01CA098438 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI BEGG, COLIN B · 2003 to 2005
$839k
Validation of the use of whole-genome amplified DNA in a population-based studyR03CA173806 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI ORLOW, IRENE · 2013 to 2014
$170k
Mutational Analysis of Clonality in Multiple Primary MelanomaR03CA125829 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI ORLOW, IRENE · 2006 to 2007
$128k
NCI NIH HHS P01 CA206980NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA014089NCI NIH HHS P30 CA016086NCI NIH HHS R01 CA098438NCI NIH HHS R01 CA112243NCI NIH HHS R01 CA112524NCI NIH HHS R01 CA233524NCI NIH HHS R03 CA125829NCI NIH HHS R03 CA173806NCI NIH HHS U01 CA083180NIEHS NIH HHS P30 ES010126
6 · The paper itself

Abstract

backgroundGuidelines for follow-up of patients with melanoma are based on limited evidence.

objectivesTo guide skin surveillance, we developed a risk prediction model for subsequent primary melanomas, using demographic, phenotypical, histopathological, sun exposure and genomic risk factors.

methodsUsing Cox regression frailty models, we analysed data for 2613 primary melanomas from 1266 patients recruited to the population-based Genes, Environment and Melanoma study in New South Wales, Australia, with a median of 14 years' follow-up via the cancer registry. Discrimination and calibration were assessed.

resultsThe median time to diagnosis of a subsequent primary melanoma decreased with each new primary melanoma. The final model included 12 risk factors. Harrell's C-statistic was 0·73 [95% confidence interval (CI) 0·68-0·77], 0·65 (95% CI 0·62-0·68) and 0·65 (95% CI 0·61-0·69) for predicting second, third and fourth primary melanomas, respectively. The risk of a subsequent primary melanoma was 4·75 times higher (95% CI 3·87-5·82) for the highest vs. the lowest quintile of the risk score. The mean absolute risk of a subsequent primary melanoma within 5 years was 8·0 ± SD 4.1% after the first primary melanoma, and 46·8 ± 15·0% after the second, but varied substantially by risk score.

conclusionsThe risk of developing a subsequent primary melanoma varies considerably between individuals and is particularly high for those with two or more primary melanomas. The risk prediction model and its associated nomograms enable estimation of the absolute risk of subsequent primary melanoma, on the basis of on an individual's risk factors, and can be used to tailor surveillance intensity, communicate risk and provide patient education. What's already known about this topic? Current guidelines for the frequency and length of follow-up to detect new primary melanomas in patients with one or more previous primary melanomas are based on limited evidence. People with one or more primary melanomas have, on average, a higher risk of developing another primary invasive melanoma, compared with the general population, but an accurate way of estimating individual risk is needed. What does this study add? We provide a comprehensive risk prediction model for subsequent primary melanomas, using data from 1266 participants with melanoma (2613 primary melanomas), over a median 14 years' follow-up. The model includes 12 risk factors comprising demographic, phenotypical, histopathological and genomic factors, and sun exposure. It enables estimation of the absolute risk of subsequent primary melanomas, and can be used to tailor surveillance intensity, communicate individual risk and provide patient education.

Indexed as

MelanomaSkin NeoplasmsAustraliaCohort StudiesHumansNew South WalesRisk Factors

Identifiers

PMID31520533
PMCPMC7069770
OpenAlexW2972423208

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.