Association between smoking and colorectal cancer in Eastern Mediterranean Regional Office (EMRO): A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Smoking poses a significant risk for colorectal cancer (CRC), considered the third leading reason for cancer-related deaths worldwide. However, there has been limited research on the relationship between smoking and CRC in the Eastern Mediterranean Regional Office (EMRO). Therefore, a meta-analysis was conducted to combine available data and gain a comprehensive understanding of the relationship between smoking and CRC in EMRO. Methods: Two independent researchers searched PubMed, Scopus, and Web of Science until December 2022. The included studies were checked for risk of bias administering the Newcastle-Ottawa scale. Heterogeneity was evaluated using I2 statistics and the Cochrane test. Publication bias was determined through funnel plot analysis and Egger's regression test. Additionally, a meta-regression analysis explored the impact of a country's Human Development Index (HDI) on the relationship between smoking and CRC. Results: The final analysis included 26 studies, revealing a significant association between smoking and CRC (OR = 1.40; 95% CI: 1.11 - 1.78; P = 0.004). Moreover, smoking had a more pronounced adverse effect on CRC in countries with higher HDIs compared to those with lower HDIs (OR = 1.30; 95% CI: 0.99 - 1.71; P = 0.054). Conclusions: Our findings underscore the importance of implementing smoking cessation programs and policies in EMRO countries, as they demonstrate a positive relationship between smoking and the risk of CRC. Furthermore, the results suggest that a country's level of human development may influence the association between smoking and CRC. Further research is needed to investigate this potential connection and develop targeted public health interventions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".