A novel infusible botanically-derived drug, PG2, for cancer-related fatigue: A phase II double-blind, randomized placebo-controlled study
Bibliographic record
Abstract
PURPOSE: This study investigated the efficacy of the botanical-derived drug, PG2, a partially purified extract of Astragalus membranaceus, as a complementary and palliative medicine for managing cancer-related fatigue (CRF). METHODS: Patients with advanced cancer and moderate to severe CRF were randomized to receive either PG2 or a placebo (normal saline, NS) in the first treatment cycle (four weeks) in a double-blind manner; thereafter, on the next cycle (four weeks), all patients received open-label treatment with PG2. RESULTS: PG2 significantly improved CRF in the NS-primed group. In the first four week cycle, PG2 administration resulted in a greater fatigue-improvement response rate than seen with NS alone. In addition, approximately 82% of patients who reported an improvement of fatigue symptoms following the first cycle of PG2 experienced sustained benefits after administration of the second treatment cycle. Among patients treated with PG2 who did not report an improvement in symptoms throughout the first treatment cycle, approximately 71% showed significant improvement after the second treatment cycle. No major or irreversible toxicities were observed with PG2 treatment. CONCLUSION: PG2 might be an effective and safe treatment for relieving CRF among advanced cancer patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".