An N-of-1 Feasibility Study of Homeopathic Treatment for Fatigue in Patients Receiving Chemotherapy
Bibliographic record
Abstract
BACKGROUND: Cancer-related fatigue has been described as a subjective feeling of physical, emotional, and/or cognitive tiredness. Homeopathy has been widely used to treat side effects of chemotherapy. The n-of-1 design is a single-patient trial method to study a clinical condition that is either short lived and reversible or is chronic and stable. The n-of-1 design requires a washout/reset period. The feasibility of performing an n-of-1 study in homeopathy has not previously been tested. METHODS: A feasibility n-of-1 trial of individualized homeopathic treatment for fatigue in a single adult undergoing chemotherapy administered periodically was performed. For each matched pair of treatments, the participant was randomly allocated either placebo or verum for the period between treatments. For the subsequent treatment period, the opposite allocation was given. Participant and practitioner were blinded to the allocation. Ongoing conventional treatments were permitted. The ability to recruit and retain was monitored and changes in fatigue and quality of life were measured using two validated outcome measures. RESULTS: Sixty-eight patients were assessed between February 2014 and February 2015. Four patients were eligible for the study and one consented to participate. The participant enrolled in the study for six cycles of chemotherapy and completed all treatment and outcome measures. There was no improvement under homeopathic treatment compared to placebo. There were multiple confounding events such as conventional medication changes and an adverse event unrelated to therapy. CONCLUSION: Adequate recruitment was not feasible in this setting. The n-of-1 study design is feasible in this population from the perspective of the ability to complete the trial. No conclusion on the efficacy of homeopathy for this individual can be made. It is unclear as to whether multiple treatments of chemotherapy would be an appropriate clinical situation in which to apply the n-of-1 trial methodology. Future studies should pilot adaptations to this study design.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".