Evidence map›Paper›PMID 40668756›Full record

ArticleJournal of the National Cancer Institute2025

A prediction model for metachronous colorectal cancer: development and validation.

Ye Zhang, Amalia Karahalios, Aung Ko Win, Enes Makalic, Alex Boussioutas, Daniel D Buchanan, Stephanie L Schmit, N Jewel Samadder, Finlay A Macrae, Mark A Jenkins

Abstract readValidation Study
In one paragraph

Article in Journal of the National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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. Article
  2. 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

10 authors.

Ye ZhangCenter for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0003-2698-2391
Amalia KarahaliosCenter for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
Aung Ko WinCenter for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0002-2794-5261
Enes MakalicCenter for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0003-3017-0871
Alex BoussioutasDepartment of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
Daniel D BuchananUniversity of Melbourne Center for Cancer Research, Victorian Comprehensive Cancer Center, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0003-2225-6675
Stephanie L SchmitGenomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA.ORCID 0000-0001-5931-1194
N Jewel SamadderMayo Clinic Comprehensive Cancer Center, Mayo Clinic, Phoenix, AZ, USA.ORCID 0009-0003-9740-9696
Finlay A MacraeDepartment of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0003-4035-9678
Mark A JenkinsCenter for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.ORCID 0000-0002-8964-6160

Funding

Data sharing: the Colon Cancer Family Registry CohortU01CA167551 · NCI · UNIVERSITY OF MELBOURNE · PI Daniel David BUCHANAN, Steven Gallinger · 2018 to 2026
$16.8M
China Scholarship Council-University of MelbourneNational Health and Medical Research Council Investigator 1194392National Health and Medical Research Council Investigator 1194896National Health and Medical Research Council Investigator 1195099NCI NIH HHS U01 CA167551NIH HHS U01 CA167551The Colon Cancer FamilyThe Jeremy Jass Memorial Pathology Bank
6 · The paper itself

Abstract

backgroundBeing able to estimate the risk of metachronous disease in a patient with colorectal cancer (CRC) could enable risk-appropriate surveillance. The aim of this study was to develop a risk-prediction model to estimate individual 10-year risk of metachronous disease following a CRC diagnosis.

methodsA population-based cohort of patients with CRC was recruited soon after diagnosis between 1997 and 2012 from the United States, Canada, and Australia. Cox regression with the least absolute shrinkage and selection operator penalization was used to identify factors that predicted the risk of a new primary CRC diagnosed at least 1 year after the initial CRC diagnosis. Potential predictors included demography, anthropometry, lifestyle factors, comorbidities, personal and family cancer history, medication use, age at diagnosis, and pathological features of the first CRC. Internal validation through bootstrapping was used to evaluate the discrimination and calibration.

resultsWe included 6085 CRC cases; 138 (2.3%) of these cases were diagnosed with metachronous disease over a median of 12 years (IQR = 5-17 years). Metachronous CRC risk was predicted by body mass index; smoking status; level of physical activity; family history of cancer and synchronous CRC; stage, grade, histological type, and DNA mismatch repair status; and age at diagnosis of the first CRC. The model was valid with a C statistic of 0.65 (95% CI = 0.63 to 0.68) and a calibration slope of 0.873 (SD = 0.087).

conclusionsMetachronous CRC can be predicted with reasonable accuracy using a prediction model that consists of clinical variables collected as part of routine practice.

Indexed as

Colorectal NeoplasmsNeoplasms, Second PrimaryAgedAustraliaCanadaCohort StudiesFemaleHumansMaleMiddle AgedProportional Hazards ModelsRisk AssessmentRisk FactorsUnited States

Identifiers

PMID40668756
PMCPMC12505132

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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.