DOP083 The association of appendectomy and colorectal cancer in ulcerative colitis patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Appendectomy is a protective factor for developing ulcerative colitis (UC), and is suggested to have a beneficial effect on the clinical course of the disease. However, recent studies showed no decreased colectomy rate with an increased risk of colorectal cancer (CRC), questioning if ongoing trials should continue. We aimed to investigate the suggested correlation in a meta-analysis, and analyse possible confounding factors. A systematic review and meta-analysis were performed using MEDLINE, EMBASE and the Cochrane library on 10 July 2017. Data from studies describing the influence of appendectomy on colectomy rate and risk of CRC and/or high-grade dysplasia (HGD) were extracted from published reports. Exclusion criteria were patients <18 years, non-UC, and animal studies. Risk of bias was assessed according to The Newcastle Ottawa Quality Assessment Scale. From 891 studies, 13 studies evaluating 73323 UC patients (appendectomy n = 2859) were included (Figure 1). Flow-diagram of study inclusion. All studies, except one, were rated as poor quality. Overall, colectomy rate in appendectomised and non-appendectomised patients was not significantly different (OR 1.21, 95% CI 0.84–1.75, I2=56%), but 4/6 studies demonstrated significantly longer disease duration, with a decreased use of steroids (73.3% and 47.5% respectively) after appendectomy. Six studies investigated the risk of CRC and/or HGD which was significantly increased after appendectomy (OR 3.68, 95% CI 1.70–7.94, I²=31%; Figure 2). Three studies looked at CRC specifically and showed the same trend, however not significant (OR 5.50, 95% CI 0.95–31.96, I2 59%). The increased incidence of malignant degeneration seemed related to longer disease duration, with an average disease duration of 102.7 months in the appendectomy group vs. 76.6 months in the non-appendectomy group. Also the cumulative percentage of PSC was higher in appendectomised patients (13.7%) vs. the non-appendectomised patients (4.4%). Forest plot of appendectomy and risk of CRC and/or HGD. This systematic review shows significantly increased risk of CRC and/or HGD after appendectomy in UC patients, which is presumably correlated to delayed colectomy. This finding shows that there is no need to stop ongoing trials, but emphasises the importance of endoscopic surveillance in a high-risk patient group.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".