Antidepressants and the Risk of Breast Cancer
Bibliographic record
Abstract
BACKGROUND: A recent national newspaper article highlighted 2 published research papers that suggest an association between antidepressants and an increased risk of breast cancer. The authors of the 2 papers recommend switching or avoiding the antidepressants implicated in their studies. METHOD: We critically review these papers and, based on our review, consider what clinical practices, if any, should be modified as a result of their findings. RESULTS: Both articles are based upon case-control studies. In the first paper, the authors examine the relation between tricyclic antidepressants (TCAs) and an increased risk of breast cancer. The study upon which the paper is based has several design strengths, and the paper presents findings that have biological plausibility. However, the conclusions are weakened by the lack of accounting for potential confounding factors and multiple statistical comparisons. In the second paper, the authors combined survey and administrative data to examine the association between antidepressant use and breast cancer risk. The press article notwithstanding, the second paper does not find a significant association between specific antidepressants and an increased risk of breast cancer, after adjusting for potential confounders. There are significant methodological limitations to the research upon which the paper is based. CONCLUSIONS: The finding of an association between TCA use and increased risk of breast cancer merits further testing using stronger research designs. However, because of the methodological concerns described, the 2 papers we review provide insufficient evidence to guide practitioners to change clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".