Quality of life and symptom intensity over time in people with cancer receiving palliative care: Results from the international European Palliative Care Cancer Symptom study
Bibliographic record
Abstract
BACKGROUND: People with advanced cancer experience multiple symptoms during their illness trajectory, which can fluctuate in intensity. AIM: To describe the course of self-reported quality of life, emotional functioning, physical functioning and symptom intensity over time in cancer patients receiving palliative care. DESIGN: Longitudinal study with monthly assessments, using the EORTC QLQ-C15-PAL. Data were analysed (1) prospectively, from baseline to ≥8-month follow-up; and (2) retrospectively, by taking death as index date and comparing results from three cross-sectional subsamples at different stages of illness (time to death ≥6, 5-3 and 2-0 months). Linear mixed models were calculated. SETTING/PARTICIPANTS: A total of 1739 patients (mean age 66, 50% male) from 30 palliative care centers in 12 countries were included. RESULTS: In prospective analyses, quality of life, functioning and symptoms-except nausea/vomiting-remained generally stable over time. In retrospective analyses, patients 2-0 months before death reported significantly lower quality of life and physical functioning scores than those 5-3 months before death, who in turn scored lower than those ≥6 months before death, suggesting progressive decline. Emotional functioning remained initially unchanged, but decreased in the last months. Pain, fatigue and appetite loss showed a stable increase in intensity towards death. Dyspnea, insomnia and constipation increased from 5-3 to 2-0 months before death. Nausea/vomiting only increased when comparing those ≥6 months before death with those 2-0 months before death. CONCLUSION: While the prospective approach showed predominantly stable patterns for quality of life, functioning and symptom severity throughout study duration, retrospective analyses indicated that deterioration was already apparent before the terminal phase and accelerated close to death. Our findings support the importance of early symptom identification and treatment in this population, and highlight the need for further studies to explore what characterizes those with either lower or higher symptom burden at different time points towards death.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".