Use of complementary medicine (CAM) among women receiving chemotherapy for ovarian cancer: A comparison of attitudes between two patient populations
Bibliographic record
Abstract
e20545 Background: CAM use in cancer patients (pts) is common. The aim of this study was to compare patterns of CAM use and attitudes to CAM among ovarian cancer (EOC) pts in Canada and Scotland. Methods: Patients receiving chemotherapy for EOC in Princess Margaret Hospital (PMH), Toronto and the Edinburgh Cancer Centre (ECC), Scotland, completed a survey on CAM taken within the previous month as well as a questionnaire assessing patient attitudes and perceptions of CAM. A comparison between the 2 patient populations and between CAM users and non-users was made. Results: 194 pts (100 ECC: 94 PMH) were enrolled on study. The use of CAM in PMH was significantly higher than in ECC (52% vs. 36%, p=0.02). Whilst both populations thought it important for their oncologist to be aware of CAM usage (86% PMH: 93% ECC), pts from PMH were less likely to inform their compared to pts from ECC (50% vs 81%, p=0.02). Patterns of CAM use differed between the 2 populations: Multivitamins were the most common CAM in both populations (31% PMH:13% ECC). They were not considered CAM for the purpose of analysis. Most commonly used CAM in PMH were Soy products (12%), vitamin C (10%) and Green Tea (9%); in ECC pts used Omega 3 and fish oil (9%), Evening Primrose (7%) and vitamin C (6%). Although the majority of CAM users in both populations found CAM to be helpful (57% PMH: 61% ECC) only a minority thought they would cure their cancer (18% PMH: 6% ECC), prevent its spread (31% PMH: 14% ECC) or prevent a recurrence (20% PMH: 11% ECC). Users more often felt CAM relieved symptoms (45% PMH: 42% ECC), boosted the immune system (55% PMH: 56% ECC) or improved their quality of life (43% PMH: 53% ECC). ECC CAM users were more likely than PMH users to concede that CAMs have side effects (39% vs 29%) or could impact the efficacy of conventional treatment (17% vs 6%). CAM users were more likely than non-users to agree with positive statements and to disagree with negative statements about CAM. Conclusions: CAM use is common among pts receiving chemotherapy for EOC. CAM use was more prevalent among North American pts than Scottish pts. Attitudes and patterns of CAM usage differ and are culturally sensitive. Oncologists need to be aware of this when initiating discussion about CAM with their patients during cancer treatment. No significant financial relationships to disclose.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".