Evidence map›Paper›PMID 36493335›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2023

CanRisk-Prostate: A Comprehensive, Externally Validated Risk Model for the Prediction of Future Prostate Cancer.

Tommy Nyberg, Mark N Brook, Lorenzo Ficorella, Andrew Lee, Joe Dennis, Xin Yang, Naomi Wilcox, Tokhir Dadaev, Koveela Govindasami, Michael Lush and 9 more

Open access · bronzeAbstract read
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Adjuvant immunotherapy in resected non-small cell lung cancer harboring oncogenic driver alterations beyond EGFR and ALK: results from a retrospective analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  4. Polygenic risk scores in cancer.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
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  17. Protein-truncating and rare missense variants inJournal of medical genetics · 2024
    Article
  18. Screening guidelines for individuals at increased risk for prostate cancer.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2024
    Review
  19. Article
  20. 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

19 authors at 4 institutions in 1 country.

Tommy NybergCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-9436-0626
Mark N BrookOncogenetics Team, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-8969-2378
Lorenzo FicorellaCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Andrew LeeCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-0677-0252
Joe DennisCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Xin YangCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-0037-3790
Naomi WilcoxCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-7709-7029
Tokhir DadaevOncogenetics Team, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-8268-0438
Koveela GovindasamiOncogenetics Team, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Michael LushCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Goska LeslieCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-5756-6222
Artitaya LophatananonDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.
Kenneth MuirDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.
Elizabeth BancroftOncogenetics Team, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-5482-5660
Douglas F EastonCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-2444-3247
Marc TischkowitzDepartment of Medical Genetics, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-7880-0628
Zsofia Kote-JaraiOncogenetics Team, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-6329-5155
Rosalind EelesOncogenetics Team, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Antonis C AntoniouCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-9223-3116
University of Cambridge · GBInstitute of Cancer Research · GBManchester Academic Health Science Centre · GBRoyal Marsden NHS Foundation Trust · GB

Funding

Cancer Research UK 11174Cancer Research UK 20861Cancer Research UK C12292/A20861Cancer Research UK C12292/A22820Cancer Research UK C5047/A10692Cancer Research UK C5047/A15007Cancer Research UK C5047/A17528Cancer Research UK C5047/A3354Cancer Research UK C5047/A7357Medical Research Council MC_PC_17228
6 · The paper itself

Abstract

purposeProstate cancer (PCa) is highly heritable. No validated PCa risk model currently exists. We therefore sought to develop a genetic risk model that can provide personalized predicted PCa risks on the basis of known moderate- to high-risk pathogenic variants, low-risk common genetic variants, and explicit cancer family history, and to externally validate the model in an independent prospective cohort. MATERIALS AND

methodsWe developed a risk model using a kin-cohort comprising individuals from 16,633 PCa families ascertained in the United Kingdom from 1993 to 2017 from the UK Genetic Prostate Cancer Study, and complex segregation analysis adjusting for ascertainment. The model was externally validated in 170,850 unaffected men (7,624 incident PCas) recruited from 2006 to 2010 to the independent UK Biobank prospective cohort study.

resultsThe most parsimonious model included the effects of pathogenic variants in

conclusionTo our knowledge, this is the first validated risk model offering personalized PCa risks. The model will assist in counseling men concerned about their risk and can facilitate future risk-stratified population screening approaches.

Indexed as

ProstateProstatic NeoplasmsHumansMaleProspective StudiesProstate-Specific AntigenRisk FactorsProstate-Specific Antigen

Identifiers

PMID36493335
PMCPMC9928632
OpenAlexW4311022193

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.