ArticleCommunications medicine2022
Using cancer risk algorithms to improve risk estimates and referral decisions.
Article in Communications medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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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.
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Who cites it
11 citing papers in PubMed.
- The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Trial
- Determinants of Physicians' Referrals for Suspected Cancer Given a Risk-Prediction Algorithm: Linking Signal Detection and Fuzzy Trace Theory.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers.Scientific reports · 2025Article
- Recalibrating the Genetics and Epidemiology of Colorectal Cancer Consortium Environmental Risk Score for Use in US Veterans.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024Article
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- Family physicians overestimate diagnosis probabilities regardless of the test results.Frontiers in medicine · 2023Article
- Risk prediction models for head and neck cancer: A rapid review.Laryngoscope investigative otolaryngology · 2022Review
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- Algorithm-based advice taking and clinical judgement: impact of advice distance and algorithm information.Cognitive research: principles and implications · 2022Article
- Using cancer risk algorithms to improve risk estimates and referral decisions.Communications medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Background: Cancer risk algorithms were introduced to clinical practice in the last decade, but they remain underused. We investigated whether General Practitioners (GPs) change their referral decisions in response to an unnamed algorithm, if decisions improve, and if changing decisions depends on having information about the algorithm and on whether GPs overestimated or underestimated risk. Methods: 157 UK GPs were presented with 20 vignettes describing patients with possible colorectal cancer symptoms. GPs gave their risk estimates and inclination to refer. They then saw the risk score of an unnamed algorithm and could update their responses. Half of the sample was given information about the algorithm's derivation, validation, and accuracy. At the end, we measured their algorithm disposition. We analysed the data using multilevel regressions with random intercepts by GP and vignette. Results: We find that, after receiving the algorithm's estimate, GPs' inclination to refer changes 26% of the time and their decisions switch entirely 3% of the time. Decisions become more consistent with the NICE 3% referral threshold ( Conclusions: Cancer risk algorithms have the potential to improve cancer referral decisions. Their use as learning tools to improve risk estimates is promising and should be further investigated.
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Registered trials
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.