S1277 No Differences in Dysplasia Detection Between Dye and Virtual Chromoendoscopy Techniques: Results From a Meta-Analysis of Randomized Clinical Trials
Bibliographic record
Abstract
Introduction: A recent meta-analysis revealed the superiority of dye chromoendoscopy (DCE) to high-definition (HD) white light endoscopy for dysplasia detection in inflammatory bowel disease (IBD) patients. This meta-analysis assesses dysplasia detection by HD scopes comparing DCE to virtual chromoendoscopy (VCE). Methods: We comprehensively searched multiple databases (PubMed, EMBASE, and Cochrane Library) through March 2024. We limited our inclusion to randomized controlled trials (RCTs) utilizing HD scopes and comparing DCE and VCE (narrow band imaging [NBI], iSCAN, auto-fluorescence imaging [AFI], or flexible spectral imaging color enhancement [FICE]). The primary outcome was dysplasia detection, defined as the number of patients with at least 1 dysplastic lesion detected (this included adenomatous lesions). A comparativeness effectiveness meta-analysis utilizing the random effects model was performed. We used odds ratios (OR) for comparison with 95% confidence intervals (CI). I2 was used to assess heterogeneity. We did a subgroup analysis excluding AFI, a VCE technique deemed inferior to DCE by a multicentric randomized control trial. Results: Eight studies met our inclusion criteria and were included in the analysis. Six studies were published as full papers. Three RCTs used NBI, 3 used iSCAN, 1 used FICE, and 1 used AFI (Table 1). Overall, the dysplasia detection was not significantly different between DCE and VCE, OR 1.2 (95% CI 0.85-1.7, P =0.2, I2 13%) (Figure 1). An analysis limited to full-text articles, including 6 studies, showed higher dysplasia detection associated with DCE, OR 1.5 (95% CI 1.03-2.22 P =0.3, I2 0%)(Figure 1). Upon excluding 1 study evaluating AFI, no difference between DCE and VCE remained, OR 1.39 (95% CI 0.087-2.21 P =0.15, I2 0%) (Figure 1). Conclusion: This updated meta-analysis of RCTs utilizing HD scopes showed no significant differences in dysplasia detection between DCE and VCE, making VCE a viable alternative to DCE when DCE is not available. Based on a subgroup analysis including AFI, significantly higher dysplasia was detected via DCE. Thus, the results of this meta-analysis do not support AFI as an alternative to DCE in dysplasia detection in IBD. Further research is needed into the long-term outcomes of various screening modalities, including cancer and cancer-related death.Figure 1.: Forest plot summarizing the odds of dysplasia detection between dye chromoendoscopy (DCE) and virtual chromoendoscopy (VCE) in A) all studies, B) full-text articles, and C) full-text articles excluding a study that used auto-fluorescence imaging technique. Table 1. - Summary of included studies Author Country Sample Size Mean Age Female (%) IBD Type Mean Disease Duration VCE DCE Publication Type Bisschops (2016) Canada 131 52.3 y 58 (44%) UC 15 y NBI 0.1% methylene blue Full Pellise (2011) Spain 60 48.3 y 27 (45%) UC/CD (42/19) 15.9 y NBI indigo carmine Full Watanabe (2016) Japan 263 51 y 127 (48%) UC 13 y NBI Indigo carmine Abstract Iacucci (2017) Canada 180 48.7 y 122 (45%) UC/CD/IC (129/136/5) 17.7 y iSCAN 0.04% methylene blue or 0.03% of indigo carmine Full González-Bernardo (2021) Spain 129 50.4 y 62 (48%) UC/CD 17.7 y iSCAN 0.03% indigo carmine Full Sinonquel (2022) European Multicentric trial 136 NS NS UC 19.8 iSCAN Methylene blue 0.1%) Abstract Gulati (2018) UK 48 44.9 y 18 (37.5%) UC/CD (45/3) 14.5 y FICE Indigo carmine Full Vleugels (2018) Netherlands & UK 210 56.2 y 88 (42%) UC 20.8 y AFI 0·1% methylene blue solution or 0·2% indigo carmine solution Full
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".