The Adjunctive Effect of Acupuncture for Advanced Cancer Patients in a Collaborative Model of Palliative Care: Study Protocol for a 3-Arm Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Cancer is the second leading cause of death before the age of 70. Improved cancer survival has put increasing demands on cancer care. Palliative care is the specialized multi-disciplinary care providing relief from the pain, symptoms, and stress of serious illness. The study aims to evaluate the adjunctive effect of acupuncture for advanced cancer patients in a collaborative model of palliative care. METHODS/DESIGN: This is a single-blinded, randomized, sham-controlled trial. One hundred twenty advanced cancer patients undergoing palliative care will be randomized in a ratio of 2:1:1 to manual acupuncture plus standard care group (ASC), sham acupuncture plus standard care group (SSC), and standard care group (SC). Patients in ASC and SSC will receive 9 sessions of acupuncture or sham acupuncture for 3 weeks, and will be followed up for 2 months. The primary measure is the change from baseline score of the Edmonton Symptom Assessment System at 3 weeks. The secondary measures include the Brief Fatigue Inventory, Hospital Anxiety and Depression Scale, Insomnia Severity Index, Numeric Rating Scale, and European Organization for Research and Treatment of Cancer Quality of Life 15 items Questionnaire for Palliative Care. DISCUSSION: The finding of this trial will provide high-quality evidence on the adjunctive effect of acupuncture to standard care on advanced cancer patients undergoing palliative care. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04398875 (https://www.clinicaltrials.gov/ct2/show/NCT04398875), Registered on 21 May 2020.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".