Printed in U.S.A. DOI: 10.1093/aje/kwh234 Antidepressant Medication Use and Non-Hodgkin’s Lymphoma Risk: No Association
Bibliographic record
Abstract
Animal and human studies have suggested that antidepressant medications may be associated with several cancers. The authors evaluated the association between antidepressant medication use and the risk of non-Hodgkin’s lymphoma using a Canadian population-based case-control study, the National Enhanced Cancer Surveillance Study. Non-Hodgkin’s lymphoma cases (n = 638) diagnosed in 1995–1996 were identified using the Ontario Cancer Registry, and controls (n = 1,930) were identified from the Ontario Ministry of Finance Property Assessment Database. Antidepressant medication use was ascertained using a self-administered questionnaire. Multivariate logistic regression was used to estimate odds ratios. “Ever ” use of antidepressant medications was not associated with non-Hodgkin’s lymphoma risk. The odds ratio for non-Hodgkin’s lymphoma with 25 or more months of tricyclic antidepressant medication use was 1.6; however, this was nonsignificant. Duration or history of use or individual types of antidepressant medications were not associated with non-Hodgkin’s lymphoma risk. These findings do not support an increased risk of non-Hodgkin’s lymphoma with antidepressant medication use. antidepressive agents; case-control studies; lymphoma, non-Hodgkin; neoplasms Abbreviations: ASOR, age- and sex-adjusted odds ratio; CI, confidence interval; SSRI, selective serotonin reuptake inhibitor. With the dramatic increase in incidence and mortality rates of non-Hodgkin’s lymphoma over the past 30 years,
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.881 | 0.771 |
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".