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Record W4408907696 · doi:10.1136/bmjmed-2025-001446

Benefits, burden, and harms of computer aided polyp detection with artificial intelligence in colorectal cancer screening: microsimulation modelling study

2025· article· en· W4408907696 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsTed Rogers Centre for Heart ResearchUniversity Health Network
FundersJapan Society for the Promotion of ScienceNorges ForskningsrådEuropean Commission
KeywordsColonoscopyMedicineColorectal cancerColorectal cancer screeningPsychological interventionGuidelinePopulationGrading (engineering)Incidence (geometry)Cancer screeningInternal medicineCancerPathologyEnvironmental health

Abstract

fetched live from OpenAlex

Objective: To estimate the benefits, burden, and harms of implementing computer aided detection (CADe) of polyps in colonoscopy of population based screening programmes for colorectal cancer. Design: Microsimulation modelling study. Setting: Cost effectiveness working package in the OperA (optimising colorectal cancer prevention through personalised treatment with artificial intelligence) project. A parallel guideline committee panel (BMJ Rapid recommendation) was consulted in defining the screening interventions and selection of outcome measures. Population: Four cohorts of 100 000 European individuals aged 60-69 years. Intervention: The intervention was one screening of colonoscopy and a screening of colonoscopy after faecal immunochemical test every other year with CADe. The comparison group had the same screening every other year without CADe. Main outcome measures: Benefits (colorectal cancer incidence and death), burden (surveillance colonoscopies), and harms (colonoscopy related adverse events) over 10 years were measured. The certainty in each outcome was assessed by use of the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. Results: For 100 000 individuals participating in colonoscopy screening, 824 (0.82%) were diagnosed with colorectal cancer within 10 years without CADe versus 713 (0.71%) with CADe (risk difference -0.11% (95% CI -0.43% to 0.21%)). For faecal immunochemical test screening colonoscopy, the risk was 5.82% (n=5820) without CADe versus 5.77% (n=5770) with CADe (difference -0.05% (-0.33% to 0.15%)). The risk of surveillance colonoscopy increased from 26.45% (n=26 453) to 32.82% (n=32 819) (difference 6.37% (5.8% to 6.9%)) for colonoscopy screening and from 52.26% (n=52 263) to 53.08% (n=53 082) (difference 0.82% (0.38% to 1.26%)) for faecal immunochemical test screening colonoscopy. No significant differences were noted in adverse events related to the colonoscopy between CADe and no CADe. The model estimates were sensitive to the assumed effects of screening on colorectal cancer risk and of CADe on adenoma detection rates. All outcomes were graded as low certainty. Conclusion: With low certainty of evidence, adoption of CADe in population based screening provides small and uncertain clinical meaningful benefit, no incremental harms, and increased surveillance burden after screening.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.337
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it