Quality of life assessment in advanced cancer patients treated at home, an inpatient unit, and a day care center
Bibliographic record
Abstract
AIM OF THE STUDY: To assess quality of life (QoL) in cancer patients treated at home, at an in-patient palliative care unit (PCU), and at a day care center (DCC). PATIENTS AND METHODS: QoL was assessed in advanced cancer patients at baseline and after 7 days of symptomatic treatment using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 15-Palliative Care (EORTC QLQ-C15-PAL), the Edmonton Symptom Assessment System (ESAS), and the Karnofsky Performance Status (KPS) scale. RESULTS: A total of 129 patients completed the study, with 51 patients treated at home, 51 patients treated at the PCU, and 27 patients at DCC. In the EORTC QLQ-C15-PAL, improvement in functional and symptom scales was observed except in physical functioning and fatigue levels; patients at DCC had a better physical functioning, global QoL, appetite, and fatigue levels. In the ESAS, improvement in all items was found except for drowsiness levels, which was stable in patients treated at DCC and deteriorated in home and PCU patients. Higher activity, better appetite and well-being, and less drowsiness were observed in patients treated at DCC. KPS was better in DCC patients compared to those treated at home and at the PCU; the latter group deteriorated. CONCLUSIONS: QoL improved in all patient groups, with better results in DCC patients and similar scores in those staying at home and at the PCU. Along with clinical assessment, baseline age, KPS, physical and emotional functioning may be considered when assigning patients to care at a DCC, PCU, or at home.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".