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Record W2159187753 · doi:10.1056/nejmoa1207756

Aspirin Use, Tumor<i>PIK3CA</i>Mutation, and Colorectal-Cancer Survival

2012· article· en· W2159187753 on OpenAlexfundno aff
Xiaoyun Liao, Paul Lochhead, Reiko Nishihara, Teppei Morikawa, Aya Kuchiba, Mai Yamauchi, Yu Imamura, Zhi Rong Qian, Yoshifumi Baba, Kaori Shima, Ruifang Sun, Katsuhiko Nosho, Jeffrey A. Meyerhardt, Edward L. Giovannucci, Charles S. Fuchs, Andrew T. Chan, Shuji Ogino

Bibliographic record

VenueNew England Journal of Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesDamon Runyon Cancer Research FoundationGary Bennett Family FundNational Cancer InstituteNational Institutes of HealthHarvard UniversityNational Institute of Diabetes and Digestive and Kidney DiseasesEntertainment Industry Foundation
KeywordsAspirinHazard ratioMedicineColorectal cancerKRASInternal medicineOncologyProportional hazards modelSulindacCancerMicrosatellite instabilityCancer researchConfidence intervalBiologyGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Regular use of aspirin after a diagnosis of colon cancer has been associated with a superior clinical outcome. Experimental evidence suggests that inhibition of prostaglandin-endoperoxide synthase 2 (PTGS2) (also known as cyclooxygenase-2) by aspirin down-regulates phosphatidylinositol 3-kinase (PI3K) signaling activity. We hypothesized that the effect of aspirin on survival and prognosis in patients with cancers characterized by mutated PIK3CA (the phosphatidylinositol-4,5-bisphosphonate 3-kinase, catalytic subunit alpha polypeptide gene) might differ from the effect among those with wild-type PIK3CA cancers. METHODS: We obtained data on 964 patients with rectal or colon cancer from the Nurses' Health Study and the Health Professionals Follow-up Study, including data on aspirin use after diagnosis and the presence or absence of PIK3CA mutation. We used a Cox proportional-hazards model to compute the multivariate hazard ratio for death. We examined tumor markers, including PTGS2, phosphorylated AKT, KRAS, BRAF, microsatellite instability, CpG island methylator phenotype, and methylation of long interspersed nucleotide element 1. RESULTS: Among patients with mutated-PIK3CA colorectal cancers, regular use of aspirin after diagnosis was associated with superior colorectal cancer-specific survival (multivariate hazard ratio for cancer-related death, 0.18; 95% confidence interval [CI], 0.06 to 0.61; P<0.001 by the log-rank test) and overall survival (multivariate hazard ratio for death from any cause, 0.54; 95% CI, 0.31 to 0.94; P=0.01 by the log-rank test). In contrast, among patients with wild-type PIK3CA, regular use of aspirin after diagnosis was not associated with colorectal cancer-specific survival (multivariate hazard ratio, 0.96; 95% CI, 0.69 to 1.32; P=0.76 by the log-rank test; P=0.009 for interaction between aspirin and PIK3CA variables) or overall survival (multivariate hazard ratio, 0.94; 95% CI, 0.75 to 1.17; P=0.96 by the log-rank test; P=0.07 for interaction). CONCLUSIONS: Regular use of aspirin after diagnosis was associated with longer survival among patients with mutated-PIK3CA colorectal cancer, but not among patients with wild-type PIK3CA cancer. The findings from this molecular pathological epidemiology study suggest that the PIK3CA mutation in colorectal cancer may serve as a predictive molecular biomarker for adjuvant aspirin therapy. (Funded by The National Institutes of Health and others.).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations838
Published2012
Admission routes1
Has abstractyes

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