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Record W3021085450 · doi:10.3390/cancers12051184

The Association between Selective Serotonin Reuptake Inhibitors (SSRIs) Use and the Risk of Bladder Cancer: A Nationwide Population-Based Cohort Study

2020· article· en· W3021085450 on OpenAlexaff
Yichun Liu, Vincent Chin‐Hung Chen, Mong-Liang Lu, Min‐Jing Lee, Roger S. McIntyre, Amna Majeed, Yena Lee, Yi‐Lung Chen

Bibliographic record

VenueCancers · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsUniversity Health NetworkUniversity of Toronto
FundersChiayi Chang Gung Memorial HospitalChang Gung Medical FoundationNational Health Research InstitutesChang Gung Memorial Hospital
KeywordsMedicineBladder cancerCohortOncologyCohort studyPopulationInternal medicineCancerBioinformaticsEnvironmental healthBiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.263
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2020
Admission routes1
Has abstractyes

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