Evidence map›Paper›PMID 26464100›Full record

SynthesisCancer prevention research (Philadelphia, Pa.)2016

Risk Prediction Models for Colorectal Cancer: A Systematic Review.

Juliet A Usher-Smith, Fiona M Walter, Jon D Emery, Aung K Win, Simon J Griffin

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Cancer prevention research (Philadelphia, Pa.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 17 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
104citing papers in PubMed, 17 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

104 citing papers in PubMed, 17 syntheses or guidelines pooled it.

  1. Guideline
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  3. Acceptability of risk stratification within population-based cancer screening from the perspective of the general public: A mixed-methods systematic review.Health expectations : an international journal of public participation in health care and health policy · 2023
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  13. Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019
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  19. Validation of a Colorectal Cancer Risk Prediction Model in US Black Women.Cancer prevention research (Philadelphia, Pa.) · 2026
    Article
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44 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Juliet A Usher-SmithThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. jau20@medschl.cam.ac.uk.
Fiona M WalterThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Department of General Practice, Melbourne Medical School Faculty of Medicine, Dentistry & Health Sciences The University of Melbourne, Carlton, Victoria, Australia.
Jon D EmeryThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Department of General Practice, Melbourne Medical School Faculty of Medicine, Dentistry & Health Sciences The University of Melbourne, Carlton, Victoria, Australia.
Aung K WinCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Level 4, The University of Melbourne, Victoria, Australia.
Simon J GriffinThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Funding

Medical Research Council MC_UU_12015/4
6 · The paper itself

Abstract

Colorectal cancer is the second leading cause of cancer-related death in Europe and the United States. Survival is strongly related to stage at diagnosis and population-based screening reduces colorectal cancer incidence and mortality. Stratifying the population by risk offers the potential to improve the efficiency of screening. In this systematic review we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict future risk of primary colorectal cancer for asymptomatic individuals. A total of 12,808 papers were identified from the literature search and nine through citation searching. Fifty-two risk models were included. Where reported (n = 37), half the models had acceptable-to-good discrimination (the area under the receiver operating characteristic curve, AUROC >0.7) in the derivation sample. Calibration was less commonly assessed (n = 21), but overall acceptable. In external validation studies, 10 models showed acceptable discrimination (AUROC 0.71-0.78). These include two with only three variables (age, gender, and BMI; age, gender, and family history of colorectal cancer). A small number of prediction models developed from case-control studies of genetic biomarkers also show some promise but require further external validation using population-based samples. Further research should focus on the feasibility and impact of incorporating such models into stratified screening programmes.

Indexed as

Models, StatisticalArea Under CurveBiomarkers, TumorBody Mass IndexColorectal NeoplasmsEarly Detection of CancerHumansIncidenceMass ScreeningReproducibility of ResultsRisk AssessmentRisk FactorsROC CurveSensitivity and SpecificityBiomarkers, Tumor

Identifiers

PMID26464100
PMCPMC7610622

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.