Capsaicin may slow PSA doubling time: case report and literature review
Bibliographic record
Abstract
Capsaicin is the main pungent component of chili peppers. This is the first case, to our knowledge, that describes prostate-specific antigen (PSA) stabilization in a patient with prostate cancer, who had biochemical failure after radiation therapy. A 66-year-old male underwent radiotherapy treatment for a T2b, Gleason 7 (3+4) adenocarcinoma of the prostate, with a PSA level of 13.3 ng/mL in April 2001. He had 3-dimensional conformal radiotherapy of 46 Gy in 23 fractions to the prostate and pelvis, and a prostate boost of 30 Gy in 15 fractions. Radiotherapy was completed in May 2001 and PSA nadired in January 2002 (0.57). Due to the continued PSA rise, the patient was started on bicalutamide (50 mg orally, daily) and leuprolide acetate (1 dose of 22.5 mg intramuscularly) in July 2005 when PSA was 38.5 ng/mL. Due to poor tolerance of androgen ablation therapy, the patient discontinued treatment and started taking 2.5 mL of habaneros chili sauce, containing capsaicin, 1 to 2 times a week in April 2006. Prostate-specific antigen doubling time (PSAdt) increased from 4 weeks before capsaicin to 7.3 months by October 2006. From October 2006 until November 2007, the patient remained on capsaicin (2.5 to 15 mL daily) and his PSA was stable (between 11 to 14 ng/mL). By January 2008, his PSA rose to 22.3 and he has maintained a PSAdt between 4 and 5 months, where it presently remains. Due to the patient's continued PSA rise, he was restarted on bicalutamide (12.5 mg daily). Apart from PSA relapse, the patient remains free of signs or symptoms of recurrence.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".