Copper in colorectal cancer patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Several clinical studies have evaluated the relationship between copper on colorectal cancer (CRC), but the results are contradictory. This study aimed to conduct a systematic review and meta-analysis to investigate copper measured in two biological matrices (serum/plasma/blood and tissue) and dietary intake in CRC patients compared to healthy controls. We conducted a comprehensive and systematic search in PubMed, Scopus, Embase, and Web of Science. We included studies that reported copper levels in serum/plasma/blood, tissue, or from the diet, with an observational study design (cohort and case-control studies). Study quality was assessed with the Newcastle-Ottawa scale and potential causes of heterogeneity were evaluated. Standardized mean differences (SMD) with 95% confidence interval (CI) were pooled using random-effect models. Overall pooled odds ratio and 95% CI for the risk of CRC were calculated. Twenty-six studies (23 case-control and 3 cohort studies) with a total of 227 354 participants were included. Most of the studies presented low (50%) or moderate quality (42.3%). No differences in serum/plasma/blood copper levels (SMD = 0.23; 95% CI: -0.23, 0.70; I2 = 97.3%, 19 studies), tissue copper levels (SMD = -1.69; 95% CI: -3.41, 0.03; I2 = 85.6%, 2 studies), or copper/zinc ratio (SMD = 1.19; 95% CI: 0.54, 1.84; I2 = 95.3%, 6 studies) were found between CRC patients and healthy controls. Regarding dietary copper, CRC patients had a lower intake (SMD = -0.27; 95% CI: -0.51, -0.03; I2 = 0.0%, 2 studies). No differences were found in copper levels between CRC patients and healthy controls. However, evidence shows mostly low or moderate quality, and results were heterogeneous. More prospective studies with an adequate methodological approach are needed.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".