Meta-Analysis of the Association Between Cigarette Smoking and Incidence of Hodgkin's Lymphoma
Bibliographic record
Abstract
INTRODUCTION: Previous studies have suggested a relationship between smoking and Hodgkin's lymphoma (HL). The main objective of this study was to evaluate this potential association with a meta-analysis of observational studies. PATIENTS AND METHODS: A literature search was undertaken through December 2010 looking for observational studies evaluating the association between smoking and HL. From 714 articles, 17 were included in this study. Outcome was calculated and reported as odds ratio (OR). Heterogeneity was assessed by using the I(2) index. Publication bias was evaluated by trim-and-fill analysis. Quality assessment was performed with the Newcastle-Ottawa scale. RESULTS: Our analysis showed an OR of developing HL of 1.35 (95% CI, 1.17 to 1.56; P < .001) in current smokers. Former smokers did not have an increased risk of HL. In subset analyses of current smokers, men and older individuals had ORs of HL of 1.78 (95% CI, 1.46 to 2.17; P < .001) and 1.77 (95% CI, 1.23 to 2.54; P = .002), respectively. In addition, the OR of HL was increased in individuals who smoke more than 20 cigarettes per day, have smoked more than 20 years, or have smoked more than 15 pack-years at 1.51 (95% CI, 1.16 to 1.98; P = .002), 1.84 (95% CI, 1.47 to 2.32; P < .001), and 1.97 (1.53 to 2.54; P < .001), respectively. Meta-regression analyses showed a relative OR of HL of 1.007 (95% CI, 1.001 to 1.013; P = .025) per cigarette per day and of 1.013 (95% CI, 1.006 to 1.019; P < .001) per year of smoking. CONCLUSION: Smoking seems to increase the odds of developing HL in current smokers. The risk of HL is higher in men and older individuals and increases with higher intensity and longer duration of smoking.
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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 | 0.022 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.047 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".