Symptom burden of patients with advanced pancreas cancer (APC): A provincial cancer institute observational study.
Bibliographic record
Abstract
384 Background: Patients (pts) with advanced pancreatic cancer (APC) experience many disease-related symptoms. The Edmonton Symptom Assessment System (ESAS) measures the severity of 9 separate domains, and is completed by pts at each visit at our provincial cancer institute. The aim of this study was to describe symptom burden at baseline and over time for chemotherapy (CT) treated pts with APC, using ESAS. Methods: Pts diagnosed with APC between 2012-2016 and treated with at least 1 cycle of CT were identified. ESAS scores were extracted from the electronic medical record. Descriptive statistics were used to report the most common symptoms of pts with APC. A joint model was used to describe the trajectory of ESAS during follow-up while controlling for death. Multivariable Cox regression was used to identify independent predictors of death. Results: Of 123 pts identified, 61% had metastatic disease, 82.1% had a baseline ECOG of 0-1, with an average age of 64.8. 1608 clinic visits had an ESAS score documented and 87% of pts completed ≥ 2 ESAS assessments. Median overall survival was 10.2 months. Median progression free survival was 6.7 months. At baseline, the 10th percentile, median and 90th percentile for total symptom distress (TSD) score were 6.2, 24 and 53 respectively. 86% of pts had at least one ESAS score of ≥ 4 at baseline, with the most common being: fatigue, nausea, anxiety, and shortness of breath. Using a joint model, average TSD scores for the cohort improved for the first 4 to 5 months after starting CT and started to rise after 6 months. Average TSD scores at 15 to 18 months were similar to scores at baseline. Controlling for metastatic disease and CT type, for every increase of 10 in baseline TSD score, there was a 5% increased risk of death. Conclusions: The ESAS tool reflects the heavy burden of cancer-associated symptoms in APC. Symptoms improve months after starting CT and eventually worsen. The impact of early intervention to address symptom management is an important area of investigation in APC.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".