Regression of Follicular Lymphoma With Devil’s Claw: Coincidence or Causation?
Bibliographic record
Abstract
BACKGROUND: Cancer patients frequently use alternative therapies. Two follicular lymphoma patients who had objective tumour regression after taking Devil's Claw without cytotoxic therapy are reported here. METHODS AND RESULTS: Patient 1 presented with coexistent immunoglobulin G plasma cell dyscrasia and stage iiia lymphoma (nodes 5 cm in diameter). Computed tomography scan 10 months later showed partial regression. On enquiry, it was learned that the patient was taking Devil's Claw and Essiac (Essiac Products Services, Pompano Beach, FL, U.S.A.). This patient later developed overt myeloma, at which time he stopped the herbal supplements and underwent high-dose chemotherapy and stem cell transplantation, since which no lymphoma progression has occurred. Patient 2 presented with stage IIIA lymphoma (nodes 2.5 cm in diameter). He learned of patient 1 through our lymphoma patient support group and started Devil's Claw. Computed tomography scan 11 months later showed decreased adenopathy and splenomegaly, which has been sustained for 4 years. DISCUSSION AND CONCLUSIONS: Devil's Claw tuberous root has anti-inflammatory properties, probably through suppression of cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase expression. There are no prior reports of anticancer activity. Inhibition of COX-2 has a role in colon cancer prevention, has been implicated in lymphomagenesis, and is associated both with lymphoma stage and with response to treatment. However, spontaneous regression in lymphoma has been reported in 16% of patients in one series, of whom none were on herbal medications or COX-2 inhibitors. The key issue in both these patients is whether disease regression was "spontaneous" or causally related to therapy with Devil's Claw. The timing of the response suggests a positive effect. Further investigation is warranted, preferably with a COX-2 inhibitor of known purity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".