Early versus delayed palliative/supportive care in advanced cancer: an observational study
Bibliographic record
Abstract
OBJECTIVE: The positive impact of early palliative care interventions in advanced cancer patients has so far been largely evaluated in randomised controlled trials. This study aimed at providing information on the value of early palliative/supportive care, integrated with standard oncologic care, in a real-life setting. METHODS: This was a retrospective observational study of 292 advanced cancer patients consecutively admitted at Carpi Hospital in Modena, Italy, between 2014 and 2017. For the purpose of this analysis, patients were classified into two groups (early and delayed palliative/supportive care patients), and analysed for different clinical indicators. Early and delayed palliative/supportive care were classified according to the time elapsed from advanced cancer diagnosis until palliative/supportive care start. RESULTS: A total of 200 patients (68%), with at least three visits, were included in the analyses. The frequency of chemotherapy use in the last 60 days of life was 3.4% and 24.6% in the early and delayed groups, respectively (adjusted OR=0.1; 95% CI 0.0 to 0.4; p=0.002). The estimated survival probability at 1 year was 74.5% (95% CI 65.0% to 85.4%) and 45.5% (95% CI 37.6% to 55.0%), in the early and delayed groups, respectively. Performance status, pain and all the Edmonton Symptom Assessment Scale items, assessed at baseline and at 1 to 12 weeks after the intervention, showed significant improvement over time. However, no between-group differences were found with regard to symptom outcomes. CONCLUSIONS: An earlier palliative/supportive care intervention was associated with reduced aggressiveness of therapy, in patients receiving community oncology care. Symptom burden was improved by early palliative/supportive care, independently of the timing of patient referral.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".