Are real-world patient-reported outcomes associated with survival in patients with advanced pancreatic cancer?
Bibliographic record
Abstract
205 Background: Advanced pancreatic cancer (APC) patients often have a substantial symptom burden. In Ontario, patients visiting cancer clinics routinely complete the Edmonton Symptom Assessment Scale (ESAS), which screens for 9 symptoms (scale: 0-10). Using ESAS, we explored the association between baseline patient-reported outcomes and overall survival (OS). Methods: APC Patients with ESAS records prior to receiving publicly-funded drugs from November 2008 to March 2016 were identified from Cancer Care Ontario’s New Drug Funding Program and Symptom Management databases. We examined 3 baseline composite ESAS scores: Total Symptom Distress Score (TSDS: all 9 symptoms), Physical Symptom Score (PHS: 6/9 symptoms), and Psychological Symptom Score (PSS: 2/9 symptoms); Composite scores greater than a threshold (defined as number of symptoms in composite score multiplied by clinically relevant score (≥4)) were categorized as High Symptom Burden (TSDS ≥ 36, PHS ≥ 24, PSS ≥ 8). The primary endpoint, OS, was assessed using Kaplan-Meier. Multivariable Cox models were used to adjust for age, gender, income, prior therapies (surgery, adjuvant gemcitabine, radiation), and Charlson's comorbidity. Analysis was repeated in a sub-cohort with identifiable ECOG status and stage. Results: We identified 2,199 APC patients (mean age 64 years, 55% male) with ESAS records prior to receiving gemcitabine (54%), FOLFIRINOX (40%) or gemcitabine/nab-paclitaxel (6%). Crude median survival was 4.5 and 7.3 months for patients with high and low TSDS burden, respectively (HR = 1.50, 95% CI: 1.36, 1.66). After adjustment with multivariable Cox model, high TSDS burden was associated with lower OS (HR = 1.47, 95% CI: 1.33, 1.63). Similar trends were observed for PHS and PSS. When adjusting for both PHS and PSS in a Cox model, only the effect of PHS remained significant. In the sub-cohort (n = 393), high TSDS burden (HR = 1.34, 95% CI: 1.04, 1.73) was associated with lower OS, after adjusting for ECOG and stage. Conclusions: Among APC patients, a higher burden of patient-reported symptoms, via ESAS, at baseline was associated with reduced OS. The effect was prominent for physical symptoms, even after adjusting for treatment, stage and ECOG.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".