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The impact of routine ESAS use on overall survival: Results of a population-based retrospective matched cohort analysis.

2019· article· en· W2947022664 on OpenAlexaffabout
Lisa Barbera, Rinku Sutradhar, Craig C. Earle, Nicole Mittmann, Hsien Seow, Doris Howell, Qing Li, Deva Thiruchelvam

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreMcMaster UniversityOntario Institute for Cancer ResearchInstitute for Clinical Evaluative SciencesBaker Hughes (Canada)
Fundersnot available
KeywordsMedicineRetrospective cohort studyPropensity score matchingProportional hazards modelCancerCohortInternal medicineComorbidityCohort studyPopulationSurvival analysis

Abstract

fetched live from OpenAlex

6509 Background: The study objective was to examine the impact of routine Edmonton Symptom Assessment System (ESAS) use on overall survival among adult cancer patients. We hypothesized that patients exposed to ESAS would have better overall survival rates than those who didn’t have ESAS. Methods: The effect of ESAS screening on survival was evaluated in a retrospective matched cohort study. The cohort included all Ontario patients aged 18 or older who were diagnosed with cancer between 2007 and 2015. Patients completing at least one ESAS assessment during the study were considered exposed. The index date was the day of their first ESAS assessment. Follow up time for each patient was segmented into one of three phases: initial, continuing, or palliative care. Exposed and unexposed patients were matched 1:1 using hard (birth year ± 2 years, cancer diagnosis date ± 1 year, cancer type and sex) and propensity-score matching (14 measures including cancer stage, treatments received, and comorbidity). Matched patients were followed until death or the end of study at Dec 31, 2015. Kaplan-Meier curves and multivariable Cox regression were used to evaluate the impact of ESAS on survival. Results: There were 128,893 pairs well matched on all baseline characteristics (standardized difference < 0.1). The probability of survival within the first 5 years was higher among those exposed to ESAS compared to those who were not (73.8% vs. 72.0%, P-value < 0.0001). In the multivariable Cox regression model, ESAS assessment was significantly associated with a decreased mortality risk (HR: 0.49, 95% CI: 0.48-0.49) and this protective effect was seen across all phases. Conclusions: ESAS exposure is associated with improved survival in cancer patients, in all phases of care. To the extent possible, extensive matching methods have mitigated biases inherent to observational data. This provides real world evidence of the impact of routine symptom assessment in cancer care.

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)0.002
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.087
GPT teacher head0.462
Teacher spread0.375 · 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".

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Citations12
Published2019
Admission routes2
Has abstractyes

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