Case Report: A castration-resistant terminal prostate cancer patient’s survival prolonged after practicing Falun Gong
Bibliographic record
Abstract
Background: Most metastatic prostate cancer patients receive combined androgen blockade (CAB) as the mainstay of treatment. Unfortunately, patients ultimately progress to castration resistance. Clinical finding and diagnosis: We describe a man in his eighties who developed stage IV, M1b prostate cancer, multiple (≥5) bone metastases, and required the aid of a walker to ambulate. Without treatment, his treating physician predicted he would survive 6 months. Interventions and outcomes: The patient initially responded well to treatment with CAB, but during the 68-80th week of treatment he developed castration resistance. Bicalutamide was then discontinued. He subsequently began practicing Falun Gong (FLG) as an alternative form of care. Within one year of constant practice, he became able to walk independently, his bone metastases disappeared, and he also enjoyed better psychosocial functioning. His treating physician assessed that his prostate malignancy was “clinically, under control” and “his overall functional status is excellent.” The patient survived a total of 263 weeks (61.4 months) post diagnosis, including 174 weeks (40.6 months) after developing castration resistance. Conclusion: This castration-resistant terminal prostate cancer patient gained significant clinical benefits after practicing Falun Gong.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".