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No evidence that polymorphisms in CYP2C8, CYP2C9, UGT1A6, PPARδ and PPARγ act as modifiers of the protective effect of regular NSAID use on the risk of colorectal carcinoma

2005· article· en· W1979374480 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePharmacogenetics and Genomics · 2005
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsBishop's University
Fundersnot available
KeywordsOdds ratioColorectal cancerPeroxisome proliferator-activated receptorCYP2C9Cytochrome P450Internal medicineConfidence intervalCase-control studyMedicineCYP2C8PharmacologyGastroenterologyOncologyEndocrinologyReceptorCancerMetabolism

Abstract

fetched live from OpenAlex

OBJECTIVES: Regular continuous non-steroidal anti-inflammatory drug (NSAID) use has been associated with a reduction in risk of colorectal cancer. Our objective was to investigate whether or not a number of the polymorphic genes involved in the metabolism of NSAIDs, including cytochrome P450 s (CYPs), act as modifiers of this protective effect. METHODS: As part of a multi-centre case-control study, 478 colorectal cancer patients and 733 controls (433 matched case-control pairs) answered questions on NSAID use. These individuals were then genotyped for common polymorphisms in P450 CYP2C8, P450 CYP2C9, UDP-glucuronosyl transferase (UGT)1A6 and peroxisome proliferator-activated receptor isoforms delta and gamma (PPARdelta and PPARgamma). RESULTS AND CONCLUSION: Our study confirmed the reduction in risk of colorectal cancer with regular NSAID use (odds ratio (OR) = 0.73, 95% confidence interval (CI) (0.56, 0.95)) but showed that none of the polymorphic genes studied appeared to modify the protective effect of regular NSAID use.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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