Antidepressant medication use and nasopharyngeal cancer risk: a nationwide population-based study
Bibliographic record
Abstract
Chiao-Fan Lin,1,2,* Hsiang-Lin Chan,1,2 Yi-Hsuan Hsieh,1,2 Hsin-Yi Liang,1,2 Wei-Che Chiu,3,4,* Yena Lee,5 Roger S McIntyre,5,6 Vincent Chin-Hung Chen2,7,81Department of Child Psychiatry, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; 2Department of Psychiatry, Chang Gung University, Taoyuan, Taiwan; 3Department of Psychiatry, Cathay General Hospital, Taipei, Taiwan; 4School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei, Taiwan; 5Mood Disorders Psychopharmacology Unit, Brain and Cognition Discovery Foundation, Toronto, Ontario, Canada; 6Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; 7Medical Research Department, Health Information and Epidemiology Laboratory, Chiayi Chang Gung Memorial Hospital, Chiayi, Taiwan; 8Department of Psychiatry, Chiayi Chang Gung Memorial Hospital, Chiayi, Taiwan*These authors contributed equally to this work Background: The association between antidepressant exposure and nasopharyngeal cancer (NPC) has not been previously explored. The purpose of this study was to investigate the association between antidepressant prescription, including novel antidepressants, and the risk of NPC in a population-based study.Materials and methods: Data for the analysis were derived from National Health Insurance Research Database. We identified 16,957 cases with a diagnosis of NPC and 83,231 matched controls by using a nested case–control design. A conditional logistic regression model was used, with adjustments for potentially confounding variables (eg, comorbid physical diseases, comorbid psychiatric diseases, and other medications).Results: We report no association between NPC incidence and antidepressant prescription. For all classes of antidepressants, antidepressant exposure, regardless of cumulative dose, had no significant effect on NPC incidence (adjusted odds ratio of cumulative selective serotonin reuptake inhibitor exposure ≥336 defined daily dose was 1.18 [95% CI: 0.90–1.53]; tricyclic antidepressant exposure ≥336 defined daily dose was 1.18 [95% CI: 0.80–1.74]).Conclusion: There was no association between antidepressant prescription and incident NPC.Keywords: nasopharyngeal cancer, antidepressants, Taiwan national insurance
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".