Using Quality of Life Measures in a Phase I Clinical Trial of Noni in Patients With Advanced Cancer to Select a Phase II Dose
Bibliographic record
Abstract
ABSTRACT. The purpose of this study was to determine a maximum tolerated dose of noni in cancer patients and whether an optimal quality of life-sustaining dose could be identified as an alternative way to select a dose for subsequent Phase II efficacy trials. Dose levels started at two capsules twice daily (2 g), the suggested dose for the marketed product, and were escalated by 2 g daily in cohorts of at least five patients until a maximum tolerated dose was found. Patients completed subscales of the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 quality of life (physical functioning, pain, and fatigue) the brief fatigue inventory (BFI), questionnaires at baseline and at approximately 4-week intervals. Blood and urine were collected at baseline and at approximately 4-week intervals for measurement of scopoletin. Fifty-one patients were enrolled at seven dose levels. The maximum tolerated dose was six capsules four times daily (12 g). Although no dose-limiting toxicity was found, seven of eight patients at the next level (14 g), withdrew due to the challenges of ingesting so many capsules. There were dose-related differences in self-reported physical functioning and pain and fatigue control. Overall, patients taking three or four capsules four times daily experienced better outcomes than patients taking lower or higher doses. Blood and urinary scopoletin concentrations related to noni dose. We concluded that it is feasible to use quality of life measures to select a Phase II dose. Three or four capsules four times daily (6-8 g) is recommended when controlling fatigue, pain, and maintaining physical function are the efficacies of interest. Scopoletin, a bioactive component of noni fruit extract, is measurable in blood and urine following noni ingestion and can be used to study the pharmacokinetics of noni in 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 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".