Stable longitudinal symptom intensity in cancer patients during end-of-life palliative care at home: prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: This study aimed to investigate the trajectory of symptom burden and quality of life in palliative cancer patients receiving home-based care in Sweden. The focus was on identifying key symptoms and their changes over time to evaluate the impact of palliative care teams. METHODS: A cohort of 240 cancer patients enrolled in palliative home-care teams across three Swedish municipalities participated in this study. Symptoms were assessed using the Edmonton Symptom Assessment System at enrolment and at 1 month, 3 months and 6 months thereafter. Demographic data, symptom ratings and place of death were recorded. Statistical analyses included descriptive statistics, correlation assessments and Wilcoxon tests to identify symptom changes over time. RESULTS: The most reported symptoms with moderate or severe intensity were lack of energy, reduced quality of life and lack of appetite. Symptom levels remained stable over time, with pain and lack of security showing temporary increases at 1 month and 3 months before returning to baseline at 6 months. Significant gender and living arrangement differences were observed: men reported higher energy deficits, while patients living alone experienced more insecurity. Correlation analysis revealed strong interconnections between symptoms, particularly well-being and quality of life. CONCLUSION: This study underscores the effectiveness of palliative home-care teams in maintaining symptom stability despite the progressive nature of cancer. While overall symptom burden did not worsen, specific areas, such as pain management and providing emotional security, may require targeted interventions. The findings highlight the importance of structured, patient-centred palliative care in improving end-of-life outcomes for cancer patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".