Impact of Palliative Care in Evaluating and Relieving Symptoms in Patients with Advanced Cancer. Results from the DEMETRA Study
Bibliographic record
Abstract
Background: Cancer patients experience multiple symptoms throughout the course of the disease. We aimed to provide a comprehensive analysis of the symptom burden in patients with advanced cancer at admission to specialist palliative care (PC) services and seven days later to estimate the immediate impact of PC intervention. Patient and methods: The analysis was based on an observational, prospective, multicenter study (named DEMETRA) conducted in Italy on new patients accessing network specialist PC centers during the period May 2017–November 2017. The prevalence and intensity of symptoms were assessed at baseline and after seven days using three tools including the Edmonton Symptom Assessment System (ESAS). Results: Five PC centers recruited 865 cancer patients. Thirty-three different symptoms were observed at the baseline, the most frequent being asthenia (84.9%) and poor well-being (71%). The intensity of the most frequent symptoms according to ESAS ranged from 5.5 for asthenia to 3.9 for nausea. The presence and intensity of physical symptoms increased with increasing levels of anxiety and depression. After seven days, prevalence of nausea and breathlessness as well as intensity of almost all symptoms significantly decreased. Conclusions: The study confirmed the considerable symptom burden of patients with advanced cancer. PC intervention has significantly reduced the severity of symptoms, despite the patients’ advanced disease and short survival.
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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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".