Symptom Burden of Patients with Advanced Pancreas Cancer (APC): A Provincial Cancer Institute Observational Study
Bibliographic record
Abstract
Patients with advanced pancreatic cancer (APC) experience many disease-related symptoms. ESAS-r measures the severity of 9 symptom domains and has been validated for use in the ambulatory oncology setting. We aimed to describe symptom burden at baseline for patients with APC treated with modern chemotherapy (CT), and to determine whether symptom burden at baseline is prognostic. Patients diagnosed with APC between 2012-2016, treated with ≥1 cycle of CT, who completed ≥1 ESAS-r were identified. Descriptive statistics were used to report symptom burden and common moderate-to-severe symptoms. A joint model was used to describe the trajectory of ESAS-r during follow-up while controlling for death. Multivariable Cox regression was used to identify independent predictors of death. Of 123 patients identified, the median age was 65 and 61% had metastatic disease. The median baseline ESAS-r total symptom distress score (TSDS) was 24. A total of 86% of patients had at least one symptom score of ≥4 at baseline, with the most common being: fatigue, nausea, anxiety, and shortness of breath. Median overall survival was 10.2 months. Baseline TSDS was not predictive for worse survival in the era of modern CT. Patients with APC have a high burden of cancer-associated symptoms and a high prevalence of moderate-to-severe symptoms. Early intervention has the potential to improve quality of life in this group of patients and should be investigated.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".