The systematic early integration of palliative care into multidisciplinary oncology care in the hospital setting (IPAC), a randomized controlled trial: the study protocol
Bibliographic record
Abstract
BACKGROUND: Previous studies in the US and Canada, have shown the positive impact of early palliative care programs for advanced cancer patients on quality of life (QoL) and even survival time. There has been a lack of similar research in Europe. In order to generalize the findings from the US and Canada research on a larger scale, similar studies are needed in different countries with different care settings. The aim of this paper is to describe the research protocol of a randomized controlled trial, situated in Flanders, Belgium, evaluating the effect of systematic early integration of palliative care in standard oncology care. METHODS/DESIGN: A randomized controlled trial will be conducted as follows: 182 patients with advanced cancer will be recruited from the departments of Medical Oncology, Digestive Oncology and Thoracic Oncology of the Ghent University Hospital. The trial will randomize patients to either systematic early integration of palliative care in standard oncology care or standard oncology care alone. Patients and informal caregivers will be asked to fill out questionnaires on QoL, mood, illness understanding and satisfaction with care at baseline, 12 weeks and every six weeks thereafter. Other outcome measures are end-of-life care decisions and overall survival time. DISCUSSION: This trial will be the first randomized controlled trial in the Belgian health care setting to evaluate the effect of systematic early integration of palliative care for advanced cancer patients. The results will enable us to evaluate whether systematic early integration of palliative care has positive effects on QoL, mood and patient illness-understanding and which components of the intervention contribute to these effects. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT01865396 , registered 24(th) of May, 2013.
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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 | 0.031 | 0.033 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.032 | 0.006 |
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".