Evaluation of TiaoShenZhiAi (TSZA) Regimen for Ovarian Cancer Patients with Psychoneurological Symptom Cluster: Protocol for a Multicenter, Double-Blind, Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
Abstract Background Psychoneurological symptom clusters (PNSCs) are common in patients with ovarian cancer and are associated with reduced quality of life, treatment interruption, and poor prognosis. However, effective interventions for PNSCs remain limited. Traditional Chinese medicine may provide comprehensive benefits for symptom management. Objective This study aims to evaluate the efficacy and safety of the TiaoShenZhiAi (TSZA) regimen in alleviating PNSCs in patients with ovarian cancer and to assess its effects on quality of life and survival outcomes. Methods A total of 316 patients with ovarian cancer aged 18 to 70 years with PNSCs will be included and randomly divided into 2 parallel groups. Both groups will receive standard treatment for ovarian cancer as the basic treatment. The intervention group will receive the TSZA regimen, that is, Compound Ciwujia Granules (containing Acanthopanax senticosus and Schisandra chinensis ) combined with psychological intervention. The control group will receive a low-dose active control (simulated Compound Ciwujia Granules) combined with psychological intervention. The primary outcome is the remission rate of PNSCs at 3 months. The secondary outcome measures include the Pittsburgh Sleep Quality Index, the Patient Health Questionnaire-9, the Generalized Anxiety Disorder-7 scale, the revised Piper Fatigue Scale, the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire - Core 30 Quality of Life Scale, the traditional Chinese medicine syndrome scale, sleep quality, sleep diary, and the 1-year survival analysis. In addition, this study also includes a series of exploratory indicators (including functional magnetic resonance imaging, biomarkers of peripheral blood and tumor tissue, proportion of immune cells, cytokine levels, hypothalamic-pituitary-adrenal axis function, and immune gene expression analysis) and safety indicators (including vital signs, liver and kidney function, and electrocardiogram). The study outcomes will be evaluated based on different indicators during the treatment period (baseline and the 1st, 2nd, and 3rd mo of enrollment) and the follow-up period (the 6th, 9th, and 12th mo of enrollment). Data analysis will be conducted using R (version 4.5.3) software. A one-sided P value of <.03 will be considered statistically significant. Results This study is designed to enroll a total of 316 participants. Participant enrollment is set to commence in October 2025, with no recruitment having occurred as of April 2026. The recruitment period will extend until September 2028 or until the target enrollment is met. Data analysis is scheduled for November 2028, with submission of the trial results to a peer-reviewed journal anticipated by May 2029. Conclusions This study will evaluate the efficacy of the TSZA regimen in managing PNSCs in patients with ovarian cancer and generate clinical evidence for a new therapeutic option that improves quality of life and alleviates the symptom burden.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.005 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".