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Record W3023660975 · doi:10.6004/jnccn.2019.7382

Outcomes of Patients With Advanced Gastrointestinal Cancer in Relationship to Opioid Use: Findings From Eight Clinical Trials

2020· article· en· W3023660975 on OpenAlex
Omar Abdel‐Rahman, Hatim Karachiwala, Jacob C. Easaw

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

VenueJournal of the National Comprehensive Cancer Network · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineInternal medicineLogistic regressionOdds ratioProportional hazards modelClinical trialHazard ratioOpioidColorectal cancerOncologyConfidence intervalCancerSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: This study assessed the patterns of opioid use among patients with advanced gastrointestinal cancers who were included in 8 clinical trials and evaluated the impact of opioid use on survival outcomes of included patients. METHODS: Deidentified datasets from 8 clinical trials evaluating first-line systemic treatment of advanced gastrointestinal cancers were accessed from the Project Data Sphere platform (ClinicalTrial.gov identifiers: NCT01124786, NCT00844649, NCT00290966, NCT00678535, NCT00699374, NCT00272051, NCT00305188, and NCT00384176). These trials evaluated patients with pancreatic carcinoma, gastric carcinoma, hepatocellular carcinoma (HCC), and colorectal carcinoma. Multivariable logistic regression analysis was used to evaluate factors predicting the use of opioids. Kaplan-Meier survival estimates were used to compare survival outcomes in each disease entity among patients who did or did not receive opioid treatment. Multivariable Cox regression analysis was then used to further assess the impact of opioid use on survival outcomes in each disease entity. RESULTS: A total of 3,441 participants were included in the current analysis. The following factors predicted a higher probability of opioid use within logistic regression analysis: younger age at diagnosis (odds ratio [OR], 0.990; 95% CI, 0.984-0.997; P=.004), nonwhite race (OR for white vs nonwhite, 0.749; 95% CI, 0.600-0.933; P=.010), higher ECOG score (OR for 1 vs 0, 1.751; 95% CI, 1.490-2.058; P<.001), and pancreatic primary site (OR for colorectal vs pancreatic, 0.241; 95% CI, 0.198-0.295; P<.001). Use of opioids was consistently associated with worse overall survival (OS) in Kaplan-Meier survival estimates of each disease entity (P=.008 for pancreatic cancer; P<.001 for gastric cancer, HCC, and colorectal cancer). In multivariable Cox regression analysis, opioid use was associated with worse OS among patients with pancreatic cancer (hazard ratio [HR], 1.245; 95% CI, 1.063-1.459; P=.007), gastric cancer (HR, 1.725; 95% CI, 1.403-2.122; P<.001), HCC (HR, 1.841; 95% CI, 1.480-2.290; P<.001), and colorectal cancer (HR, 1.651; 95% CI, 1.380-1.975; P<.001). CONCLUSIONS: Study findings suggest that opioid use is consistently associated with worse OS among patients with different gastrointestinal cancers. Further studies are needed to understand the underlying mechanisms of this observation and its potential implications.

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)0.004
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 score0.039
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.132
GPT teacher head0.400
Teacher spread0.269 · 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