Systematic referral to palliative care in patients attending dedicated emergency units from French comprehensive anticancer centres: the prospective multicentre randomised comparative clinical trial PALLU
Bibliographic record
Abstract
INTRODUCTION: International medical oncology societies recommended early integration of palliative care to alleviate symptoms, improve quality of life and significantly reduce aggressiveness of care near the end of life, defined as the use of chemotherapy, high rate of hospitalisation/visits to emergency or intensive care unit in the last month of life or death in acute care unit. However, the most appropriate schedule for patient referral is still to be determined. Scores and criteria are debated, with uncontrolled symptoms (pain, dyspnoea, distress, etc) being one of the main indicators. These symptoms are also the leading causes for patients with cancer to seek care in emergency units. Several studies in North America suggested that referral to palliative care from emergency units is feasible and efficient.The aim of this study is to determine if systematic early referral to palliative care in a context of emergency reduces aggressiveness of care near the end of life compared with referral on medical team request. METHODS AND ANALYSIS: This multicentric randomised study plans to enrol patients with a PALLIA-10 score >3 attending unscheduled on-site visits in French comprehensive cancer centres, and allocate them to randomisation (1:1) to receive palliative care systematically (experimental group) or on medical oncology team request (standard group). The primary objective is to compare the proportion of patients meeting at least one criterion of clinical care aggressiveness near the end of life, in each group. Secondary objectives include a description of clinical care aggressiveness components, palliative care requirement (psychologist, social worker, nutritional counselling, etc), patient-reported outcomes (FACT-G7, Hospital Anxiety and Depression Scale, Edmonton Symptoms Assessment System), the place of death and overall survival. Health economics and human and social sciences substudies will be presented.The study needs to include 192 patients (96 patients per arm) to reach a 20% decrease in care aggressiveness in the last month of life from 65% to 45%, with a statistical power of 80%, and a 2-sided type I error rate of 5%, using systematic referral. Considering a 20% rate of dropout or patients still alive at the time of analysis, 240 patients will need to be allocated to randomisation. ETHICS AND DISSEMINATION: This clinical study received approval from the Ethics committee CPP Est III on 25 October 2023, and complies with the MR001 Commission Nationale de l'Informatique et des Libertés (#1994173, 27 September 2016). The first consent was signed on 12 September 2024.Results will be presented and published in international academic journals. PROTOCOL IDENTIFIER: V.2.1 dated 10 July 2024. TRIAL REGISTRATION NUMBER: NCT06150027.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".