Antidepressant Prescription and Risk of Lung Cancer: A Nationwide Case-Control Study
Bibliographic record
Abstract
INTRODUCTION: In recent decades, concern about safety of antidepressants has been raised but the risk between antidepressants and lung cancer has not yet been established. METHODS: A case-control study was conducted by using a nationwide database in Taiwan. The case groups were new onset lung cancer diagnosis during 1999-2008 and age- and gender-matched controls were selected among those without any cancer. The cumulative exposure dose before the lung cancer diagnosis was added and risks were calculated according to the levels of defined daily dose and classes of antidepressants. RESULTS: A total of 39,001 individuals with lung cancer and 189,906 individuals without lung cancer between 1999 and 2008 were included in the analysis. Antidepressants, of any class, were not associated with elevated risks for lung cancer with the exception of bupropion at high exposure levels (odds ratio=4.81, 95% confidence interval=1.39-16.71). DISCUSSION: Antidepressant prescription was not associated with elevation of lung cancer incidence using a nationally representative sample. The elevated risk for lung cancer with bupropion at high doses may be a bias by indication and warrant longitudinal investigation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".