The impact of routine ESAS use on overall survival: Results of a population-based retrospective matched cohort analysis.
Why this work is in the frame
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it