Detecting dysplasia using white light endoscopy or chromoendoscopy in ulcerative colitis patients without primary sclerosing cholangitis: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Endoscopic examinations are a vital diagnostic tool for dysplasia. Establishing the precision of different modes of examination is essential due to the disparate pick-up rates of dysplasia. OBJECTIVE: The aim of this article was to establish the pick-up rates of dysplastic or cancerous lesions using white light endoscopy (WLE) and random/targeted biopsies, or chromoendoscopy (CE), in patients with ulcerative colitis (UC) without primary sclerosing (PSC) or Crohn's disease (CD). DATA SOURCES: A systematic review to identify all studies up to November 2017, without language restriction, was conducted from PubMed, the Cochrane Controlled Trials Register (1960-2017), MEDLINE, CINAHL and EMBASE (1981-2017). MeSH and text word terms used included "ulcerative colitis", "dysplasia", "random biopsy", "targeted biopsy", "colonoscopy", "white light", and "chromoendoscopy". Further searches were performed using the bibliographies of these articles. STUDY SELECTION: All studies reporting on colonoscopy detection rates of dysplasia and cancers in UC without involvement of PSC or CD were included. There was no age restriction to include patients. DATA EXTRACTION: Outcome data were extracted by 2 authors independently using outcome measures defined a priori. Quality assessment was performed using the Newcastle-Ottawa scales. DATA SYNTHESIS: Data were extracted and analysed according to meta-analytical techniques using comprehensive meta-analysis. The pooled overall pick-up rate of dysplastic/cancerous lesions on WLE random biopsies was 5.6% [Event rate 0.06 (0.01, 0.23), df = 4, I2 = 94%]. Using a combined random and targeted approach with WLE the incidence was 5.1% [Event rate 0.05 (0.03, 0.09), df = 4, I2 = 96%]. One study reported on CE and found a 7% pick-up rate for dysplastic lesions. CONCLUSIONS: Endoscopic examination of UC patients without PSC identifies dysplastic or cancerous lesions in 5-7% of cases. WLE and random biopsies may pick-up a similar number of lesions to targeted biopsies, however the number of biopsies may need to be greater to achieve this equivalence. CE has a slightly higher pick-up rate. Further comparative studies are required to strengthen the body of evidence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".