Effect of incretin-based therapies on cancers of digestive system among 101 595 patients with type 2 diabetes mellitus: a systematic review and network meta-analysis combining 84 trials with a median duration of 30 weeks
Bibliographic record
Abstract
Objectives: To evaluate the risk of cancers of digestive system with incretin-based therapies among patients with type 2 diabetes mellitus. Research design and methods: Medline, Embase, Cochrane Library and ClinicalTrials.gov databases were searched for randomized controlled clinical trials that compared incretin-based drugs with placebo or other antidiabetic drugs. Paired reviewers independently screened citations, extracted data and assessed risk of bias of included studies. Network meta-analysis was performed, followed by subgroup analysis. The Grading of Recommendations Assessment, Development and Evaluation system was used to assess the quality of evidence. Results: A total of 84 studies (n=101 595) involving cancers of digestive system were identified (a median follow-up of 30 weeks). The risk of cancers of digestive system with incretin-based therapies was comparable with insulin (OR: 0.86, 95% CI 0.27 to 2.69), metformin (OR: 0.32, 95% CI 0.07 to 1.38), sodium-glucose co-transporter 2 (OR: 5.26, 95% CI 0.58 to 47.41), sulfonylureas (OR: 1.27, 95% CI 0.68 to 2.39), thiazolidinediones (OR: 0.42, 95% CI 0.13 to 1.42), alpha-glucosidase inhibitors (OR: 2.98, 95% CI 0.12 to 73.80), and placebo (OR: 0.87, 95% CI 0.71 to 1.05). The results of subgroup analysis based on the type of digestive system cancers indicated that incretin-based therapies did not increase the risk of gastrointestinal cancers, respectively. The results of subgroup analysis based on age, duration, mean HbA1c, trial duration, and sample size did not indicate the risk of digestive system cancers. Conclusions: Moderate to high Grading of Recommendations Assessment, Development and Evaluation evidence suggests that incretin-based therapies were not associated with an increased risk of cancer of digestive system in patients with type 2 diabetes mellitus.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.042 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".