The Association between Selective Serotonin Reuptake Inhibitors (SSRIs) Use and the Risk of Bladder Cancer: A Nationwide Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: Past studies suggest mixed associations between selective serotonin reuptake inhibitor (SSRI) prescription and carcinogenic risk. There is no epidemiological study reporting on the association between SSRI use and the incidence of bladder cancer. The aim of this study is to determine whether SSRI use influences the risk of bladder cancer. METHODS: We conducted a nationwide retrospective cohort study by Taiwan's National Health Insurance Research Database from January 1, 1997 to December 31, 2013. 192,392 SSRI prescribed individuals were randomly matched 1 to 1 with 191,786 individuals who had never received any SSRIs by propensity scores match. The Cox Proportional Hazard models were conducted to examine the risk of bladder cancer between individuals prescribed SSRIs and individuals not prescribed SSRIs. RESULTS: SSRIs were associated with significant reduced risk of bladder cancer with 0.5, 1, and 2 year induction periods (adjusted hazard ratio (aHR) = 0.86, 95% CI (confidence interval) = 0.76-0.98, aHR = 0.85, 95% CI = 0.75-0.97, and aHR = 0.77, 95% CI = 0.66-0.89). When examining the effect of specific SSRI, there was significantly lower risk of bladder cancer in individuals prescribed fluoxetine (6 month induction period: aHR = 0.78, 95% CI = 0.65-0.93; 1 year induction period: aHR = 0.78, 95% CI = 0.65-0.94; 2 year induction period: aHR = 0.73, 95% CI = 0.60-0.89), paroxetine (6 month induction period: aHR = 0.78, 95% CI = 0.61-0.99; 1 year induction period: aHR = 0.79, 95% CI = 0.61-1.01; 2 year induction period: aHR = 0.72, 95% CI = 0.54-0.95), and citalopram (6 month induction period: aHR = 0.74, 95% CI = 0.53-1.03; 1 year induction period: aHR = 0.70, 95% CI = 0.50-0.99; 2 year induction period: aHR = 0.60, 95% CI = 0.41-0.88). CONCLUSIONS: Individuals prescribed fluoxetine, paroxetine, or citalopram had a reduced risk of bladder cancer in this large, cross-national database.
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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 | 0.001 |
| 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".