Antipsychotic use is inversely associated with gastric cancer risk: A nationwide population‐based nested case‐control study
Bibliographic record
Abstract
OBJECTIVE: The association between antipsychotic use and gastric cancer risk remains unclear. Therefore, this study aimed to determine the association between antipsychotic exposure and the incidence of gastric cancer. METHODS: Using a nested case-control design, a total of 34 470 gastric cancer patients and 163 430 nongastric cancer controls were identified from Taiwan's National Health Insurance Research Database between 1 January 1997 and 31 December 2013. We analyzed the data using a conditional logistic regression model to adjust for possible confounding variables. RESULTS: Antipsychotic use was independently inversely associated with gastric cancer risk after controlling for potential confounding factors including income, urbanization, medications, physical and medical illness, aspirin use, nonsteroidal anti-inflammatory drug use and triple therapy. In addition, dose-dependent trends against gastric cancer risk were also shown with individual antipsychotic compounds including thioridazine, haloperidol, sulpiride, clozapine, olanzapine, quetiapine, amisulpride, and risperidone. A sensitivity analysis showed that second-generation antipsychotics had significant dose-dependent effects in reducing the risk of gastric cancer risk in patients with and without peptic ulcer disease. CONCLUSIONS: Antipsychotic use was inversely associated with gastric cancer risk, and dose-dependent effects against gastric cancer were also seen with several individual antipsychotic compounds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".