Coffee is protective against oral and pharyngeal cancer: A systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Coffee is one of the most popular and consumable drinks worldwide. However, there are conflicting results on the influence of this drink in oral and pharyngeal cancer risk. To clarify this, we aimed to systemically review and carry out a meta-analysis of the relevant literature on the association between coffee and oral and pharyngeal cancer. STUDY DESIGN: We carried out an electronic search of publications up to August 2016 from PubMed, National Library of Medicines Medline, Embase, Science Direct and the Cochrane Central Register. The Newcastle-Ottawa scale was used to address the quality of the studies a meta-analysis was carried out using random-effects models. RESULTS: From the 22,515 entries identified in the search, 13 case-control and 4 cohort studies were selected. With regards to quality on the Newcastle-Ottawa scale, an overall value of 6.06 was obtained. The analysis for oral and pharyngeal cancer grouped together indicated a pooled OR of .69 (95% CI of .57-.84; p<.001) for high versus low coffee consumption with a moderate heterogeneity (I2: 50.3%; p=.009). Regarding studies on oral cavity cancers we observed a pooled OR of 0.82; 95% CI =.58-1.16; p=.257) and for pharyngeal cancers a pooled OR of .72 (95% CI of 0.54-.95; p=.019). There was no significant publication bias. CONCLUSION: The results show an inverse association between high coffee consumption and the risk of oral and pharyngeal cancers, which indicates that coffee may have a protective role against these cancers. Further larger prospective observational cohort studies are needed to address any effect of other possible co-factors.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.028 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it