Systematic review and meta‐analysis: Associations between metabolic syndrome and colorectal neoplasia outcomes
Bibliographic record
Abstract
Abstract Aim Metabolic syndrome (MetS) is a cluster of factors including obesity, hypertension, diabetes, hypercholesterolemia and hyperlipidaemia. It has been associated with an increased risk of colorectal neoplasia. This systematic review and meta‐analysis assessed the association between MetS and (i) recurrence of adenomas or occurrence of CRC in patients with prior adenomas, and (ii) survival in patients with CRC. Method MEDLINE, Embase, Scopus and Web of Science were searched up to 22 November 2019. Two authors independently conducted title and abstract screening; full text of eligible studies was evaluated. Where ≥3 studies reported effect measures for a specific outcome, meta‐analysis using random effects model was conducted. I2 was used to assess between‐study heterogeneity. Quality appraisal was undertaken with the Newcastle‐Ottawa Score. Results The search identified 1,764 articles, 55 underwent full text screening, resulting in a total of 15 eligible studies. Five studies reported on metachronous neoplasia, with differing outcomes precluded a meta‐analysis. No consistent relationship between MetS and metachronous neoplasia was found. Ten studies reported on survival outcomes. MetS was associated with poorer CRC‐specific survival (HR = 1.8, 95% CI: 1.04–3.12, I2 = 92.7%, n = 3). Progression‐free survival was also worse but this did not reach statistical significance (HR = 1.12, 95% CI: 0.89–1.42, I2 = 85.6%, n = 3). There was no association with overall survival (HR = 1.04, 95% CI: 0.94–1.15, I2 = 43.7%, n = 7). Significant heterogeneity was present but subgroup analysis did not account for this. Conclusion MetS is associated with poorer CRC‐specific survival, but evidence is inconsistent on metachronous neoplasia. Further research is warranted to better understand the impact of MetS on the adenoma‐carcinoma pathway.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.008 | 0.008 |
| 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) | 0.005 | 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".