Case – Causation vs. correlation: Naturopathic medicine vs. natural history of a disease
Bibliographic record
Abstract
Urothelial carcinoma (UC) is the fourth most common type of cancer and arises from the urogenital epithelial. Between 5% and 10% of primary UC originate from renal pelvis and ureters and are collectively called upper tract urothelial carcinoma (UTUC). The estimated annual incidence of UTUC in Canada is 1–2/100 000.1 It most commonly affects patients in the sixth and seventh decade of life with a male predominance. In developed countries, tobacco smoking is the greatest risk factor. UTUC is often multifocal, as the entire urothelial surface is affected by the same carcinogen. 2 The gold standard treatment of localized UTUC is a radical nephroureterectomy due to the frequent occurrence of synchronous or metachronous tumours. For patients with high-risk disease (i.e., T3–T4 and/or patients with positive lymph nodes), adjuvant chemotherapy is also suggested.2 Postoperative recurrences are common. In general, bladder recurrence occurs in 22–47%, while extravesical recurrences occur in 0–12% of patients with UTUC.1 Naturopathic treatments have frequently been mentioned in the context of “curing” cancer. However, there are limited studies that follow up on these numerous treatment options and the studies that are available often are unreliable or invalid.3 Therefore, many of these rare cases are generally attributed to the spontaneous regression of cancer. We present a case of a patient with UTUC who had a local recurrence following definitive therapy and experienced resolution of cancer following a naturopathic treatment option.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".