Tibetan Herbal Pain-Relieving Plaster for Chronic Musculoskeletal Pain Among Cancer Survivors: Study Protocol of a Randomized, Double-Blind, Placebo-Controlled Trial
Bibliographic record
Abstract
Chronic pain is common and debilitating in cancer survivors. Tibetan herbal pain-relieving plaster is used as an external analgesic to treat musculoskeletal pain in China; however, its safety and efficacy have not been evaluated via clinical trials in cancer survivors. We designed this Phase II randomized, double-blind, placebo-controlled trial (ClinicalTrials.gov Identifier: NCT04916249) to assess the efficacy and safety of the pain-relieving plaster for temporary pain relief among cancer survivors with chronic musculoskeletal pain. Under ethical approval from the Institutional Review Board at the Memorial Sloan Kettering Cancer Center, we will enroll eligible cancer survivors who have a clinical diagnosis of moderate to severe chronic musculoskeletal pain in this study. We use a central randomization system to allocate the eligible participants to either the treatment or the control group in a 1:1 ratio, with stratification by baseline opioid use. We will instruct the participants to apply the herbal patch (Tibetree Pain-Relieving Plaster, Tibet Cheezheng Tibetan Medicine Co. Ltd., Tibet, China) or placebo patch daily at the focal area with worst pain for 14 consecutive days. Study physician, participant, outcome assessor, and biostatistician are blinded to the group allocation. The primary outcome is pain severity measured by the Brief Pain Inventory on Days 2-7. Secondary outcomes include changes in insomnia, anxiety, depression, fatigue, pressure pain threshold, pain medication use, and global impression of change. We will also monitor the adverse events throughout the study period. Statistical analysis will follow the intention-to-treat principle and linear mixed modeling will be used. With rigorous design and implementation, this randomized, placebo-controlled trial will provide the initial evidence on the efficacy and safety of the pain-relieving plaster for pain relief among cancer survivors with chronic musculoskeletal pain.
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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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.067 | 0.013 |
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".