Integrating patient-reported-outcomes into prognostication in gastroesophageal cancer: Results of a population-based retrospective cohort analysis.
Bibliographic record
Abstract
320 Background: Patient reported outcomes (PRO) measures are accurate self-reflections of an individual’s physical functioning and emotional well-being. The prognostic value is unknown in gastroesophageal (GE) cancer patients (pts). The Edmonton Symptom Assessment Scale (ESAS) is a simple and validated 10-item PRO tool which uses a 0 to 10 rating of ten common symptoms (total rating 0-100). In this study, we examined the association between the ESAS score and overall survival (OS) in pts with localized and metastatic GE adenocarcinoma (GEA). Methods: This study is based on the retrospective cohort database of pts with localized (stage I-III) and metastatic GEA. We included pts who were diagnosed with GEA between 2011 and 2021 and completed at least 1 baseline ESAS prior to the treatment. Pts were grouped into 3 cohorts based as follows: High symptom burden (SB) ESAS score ≥ 26, Moderate SB (11-25) or low SB (0-10). OS was defined as time from the first visit date to death. OS was assessed using the Kaplan-Meier method and significance was set at 2-sided P < 0.05. Univariate statistical analyses were used to examine the relationships between OS and multiple variables in the presentation. Results: 233 pts met the inclusion criteria: median age was 60.8y [51.4, 69.4]; 58% of pts were ECOG PS 1; 81% were non-Asian and 18.9% Asian; 67.4% of pts were male and 32.6% female. In terms of tumor location, gastric represented 47.2% of pts, GEJ 40.8% and esophageal 12.0% primaries; 43.7% pts were stage I-III, while 56.3% were de-novo metastatic pts. Median OS in Low, Mod, High SB pts cohorts were 22.7m, 17.6mm, & 14.6m, respectively (p < 0.036). Although worse OS and worse ESAS levels were not statistically significant in the localized pts (p, 505) and metastatic subgroup (p 0,092), there was a numerical tendency, especially in the metastatic pts. In the univariate analysis, there was a significant association between OS and high-symptom burden (Hazard ratio [HR] = 1.64 (95% CI, 1.12-2.38; p = 0.0104), ECOG ≥2 (HR= 2.79 (95% CI, 1.62-4.79; p = 0.0002) and metastatic pts (HR= 3.50 (95% CI, 2.51-4.86, p<0.0001). Conclusions: Higher SB based on ESAS was associated with poorer OS among GEA pts. ESAS is a reliable tool that carries a prognostic significance that could be used in practice.[Table: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".