Uncovering Risks Associated with Smoking Types and Intensities in Esophageal Cancer within High-Prevalence Regions in Africa: A Comprehensive Meta-analysis
Bibliographic record
Abstract
Tobacco is usually cited among the well-known risk factors of esophageal cancer; nevertheless, the extent of the contribution of the type of smoking and its intensity to the disease has not been comprehensively elucidated in Africa. We searched MEDLINE/PubMed, Excerpta Medica Database, Web of Science, Scopus, Cochrane Library, and African Journals Online studies published before September 2023. The quality of the studies was assessed using the Newcastle-Ottawa scale, and the funnel plot was used for assessing potential publication bias. Meta-analyses were conducted to estimate summary effects using random-effects models. This study included 22,319 participants from 27 studies. The results strongly indicate a significant association between tobacco use and a higher risk of esophageal cancer. The risk of esophageal cancer is notably higher among pipe smokers [OR = 4.68; 95% confidence interval (CI), 3.38-6.48], followed by hand-rolled cigarette smokers (OR = 3.79; 95% CI, 2.68-5.35), in comparison with those who smoked commercially manufactured cigarettes (OR = 2.46; 95% CI, 1.69-3.60). Our findings also showed that the risk of esophageal cancer is highest in people smoking >183 packs per year (OR = 5.47; 95% CI, 3.93-7.62), followed by those smoking 93 to 183 packs per year (OR = 3.90; 95% CI, 3.13-4.86), in comparison with those smoking ≤92 packs per year (OR = 2.90; 95% CI, 2.19-3.84). Our findings strongly show that among the different types of tobacco use in Africa, pipe and hand-roller smokers face a higher risk of esophageal cancer.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.008 | 0.007 |
| 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) | 0.003 | 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".