Hypnotics and Risk of Cancer: A Meta-Analysis of Observational Studies
Bibliographic record
Abstract
Background and objectives: The association between hypnotic drugs and risk of cancer remains controversial. Therefore, we performed a meta-analysis to investigate this association. Materials and Methods: Pubmed and Embase were searched systematically to identify publications up to April 2020. The Newcastle-Ottawa scale for observational studies was used to assess the quality of studies. All included studies were evaluated by two reviewers independently; any discrepancies were resolved through discussion. Results: Twenty-eight studies including 22 case-control studies and 6 cohort studies with 340,614 hypnotics users and 1,828,057 non-users were included in the final analyses. Hypnotics (benzodiazepines and Z-drugs) use was significantly associated with an increased risk of cancer (odds ratio [OR] or relative risk [RR] 1.17; 95% confidence interval 1.09–1.26) in a random-effects meta-analysis of all studies. Subgroup meta-analysis by anxiolytics/sedatives effect (anxiolytics benzodiazepines vs. sedatives group (include sedatives benzodiazepines and Z-drugs)) revealed that a significant association in sedatives group (pooled OR/RR 1.26, 95% CI, 1.10–1.45), whereas no significant relationship was observed in anxiolytics benzodiazepines (pooled OR/RR 1.09, 95% CI, 0.95–1.26). Moreover, a significant dose–response relationship was observed between the use of hypnotics and the risk of cancer. Conclusions: This meta-analysis revealed association between use of hypnotics drugs and risk of cancer. However, the use of lower dose hypnotics and shorter duration exposed to hypnotics seemed to be not associated with an increased risk of cancer. Moreover, the use of anxiolytics effect benzodiazepines seemed to be lower risk than sedatives benzodiazepines. A high heterogeneity was observed among identified studies, and results were inconsistent in some subgroups. Randomized control trials are needed to confirm the findings in the future.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 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".