Lack of Effectiveness of Computer Aided Detection for Colorectal Neoplasia: A Systematic Review and Meta-analysis of Non-Randomized Studies
Bibliographic record
Abstract
Aims Benefits of computer-aided detection (CADe) in detecting colorectal neoplasia were shown in many randomized trials where endoscopists’ behavior was strictly controlled. However, the effect of CADe on endoscopists’ performance in less-controlled setting is unclear. This systematic review and meta-analyses were aimed at clarifying benefits and harms of using CADe in real-world colonoscopy. Methods We searched MEDLINE, EMBASE, Cochrane and Google Scholar from inception to August 20, 2023. We included non-randomized studies that compared the effectiveness between CADe-assisted and standard colonoscopy. Two investigators independently extracted study data and quality. Pairwise meta-analysis was performed utilizing Risk ratio (RR) for dichotomous variables and mean difference (MD) for continuous variables with a 95% confidence interval (95% CI). Results Eight studies were included, comprising 9,782 patients (4569 with CADe and 5213 without CADe). Regarding benefits, there was neither a difference in adenoma detection rate (44% vs 38%; RR 1.11 [95% CI 0.97 – 1.28]) nor mean adenoma per colonoscopy (0.93 vs 0.79; MD 0.14 [-0.04 – 0.32]) between the CADe-assisted and standard colonoscopy, respectively. Regarding harms, there was no difference in the mean non-neoplastic lesions per colonoscopy (8 studies included for analysis, 0.52 vs 0.47; MD 0.14 [95% CI -0.07 – 0.34]) and withdrawal time (6 studies included for analysis, 14.3 vs 13.4 minutes; MD 0.8 minutes [95% CI -0.18 – 1.90]). There was a substantial heterogeneity, and all outcomes were graded with a very low certainty of evidence. Conclusions CADe in colonoscopies neither improves the detection of colorectal neoplasia nor increases burden of colonoscopy in real-world, non-randomized studies, questioning the generalizability of the results of randomized trials. Publication History Article published online: 15 April 2024 © 2024. European Society of Gastrointestinal Endoscopy. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.026 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".