Naturopathic Oncology for Advanced Cancers: Survival Outcomes from the Canadian/US Integrative Oncology Study
Bibliographic record
Abstract
Background: Several traditional, complementary, and integrative therapies have been studied for their effect on cancer outcomes; however, few studies have evaluated naturopathic oncology in a real-world setting. We conducted an observational cohort study to evaluate whether consulting with a naturopathic doctor (ND) improves survival in people with advanced cancers. Methods: Participants with metastatic breast, metastatic colorectal, advanced ovarian, or advanced pancreatic cancer were recruited from 12 North American naturopathic clinics. The primary outcome was 5-year overall survival compared with a matched cohort from the Surveillance Epidemiology and End Results (SEER) registry. We additionally evaluated survival based on the number of ND visits and intravenous vitamin C (IVC), intravenous mistletoe, and hyperthermia treatments. Results: 400 participants were enrolled: 165 had breast cancer, 116 had colorectal cancer, 72 had ovarian cancer, and 47 had pancreatic cancer. A bootstrapped analysis showed no significant differences in 5-year survival compared with SEER (breast: median hazard ratio [HR] 1.10, 95% confidence interval [CI] 0.80–1.54; colorectal: median HR 0.95, 95% CI 0.68–1.31; ovarian: median HR 1.08, 95% CI 0.64–1.86; pancreatic: median HR 0.76, 95% CI 0.51–1.13). Higher survival odds were seen with increasing IVC treatments in breast cancer, and with increasing ND visits in all cancer types except ovarian. Conclusion: No survival benefits were seen in patients with advanced cancers who saw an ND compared with registry data. After controlling for survivorship bias, in general, the number of ND visits positively correlated with improved survival; however, the number of select naturopathic treatments did not. Findings should be interpreted with caution given study limitations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".