Naturopathic Oncology Care For Thoracic Cancers : a Practice Survey
Bibliographic record
Abstract
Dugald Seely (1,2), Julie K Ennis (1,2), Ellen McDonell (1,2), Linlu Zhao (1,2)(1) Ottawa Integrative Cancer Centre, Ottawa, Ontario, Canada; (2) Canadian College of Naturopathic Medicine, Toronto, Ontario, CanadaBackground: There is a lack of clear information regarding the types and goals of treatments recommended by Naturopathic Doctors (NDs) for thoracic cancer care (lung, gastric and esophageal cancers). Objectives: NDs were surveyed to: (i) identify the most common therapeutic recommendations for thoracic cancer care; (ii) identify the most common interventions used to support key treatment goals; and (iii) identify contraindications between integrative and conventional therapies.Methods: Oncology Association of Naturopathic Physicians (OncANP) members (n=351) were invited to complete an electronic survey. Respondents provided information on recommendations considered for thoracic cancer care pre- and post-operatively across 4 domains (natural health products (NHPs), physical, mental/emotional, nutritional), treatment goals and contraindications. This survey was part of the development of the Thoracic Perioperative Integrative Surgical Evaluation (POISE) trial. Results: Forty-four NDs completed the survey (12.5% response rate), all of whom were trained in North America and the majority of whom were Fellows of the American Board of Naturopathic Oncology (FABNO; 56.8%). NDs selected significantly more interventions in the post-op compared to pre-op setting. The most frequently selected interventions included modified citrus pectin, arnica, omega-3 fatty acids, vitamin D, probiotics, exercise, acupuncture, meditation, stress reduction, low glycemic index diet and Mediterranean diet. For each of 10 pre-defined therapeutic goals, between 4 and 22 interventions were selected by at least 20% of respondents. Nine interventions were identified as meeting u22655 therapeutic goals (omega-3 fatty acids, exercise, anti-inflammatory diet, meditation, acupuncture, probiotics, arnica, visualization and turmeric. The consistency of reporting of contraindications around conventional treatment (surgery, chemotherapy and radiotherapy) differed across NHPs. Conclusion: These findings highlight naturopathic interventions with a high level of practical usage in thoracic cancer care, describe and characterize therapeutic goals, the most common interventions used to achieve these goals and provide insight on how practice changes relative to conventional cancer treatment phase.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".