Complementary and Alternative Medicine Use and Breast Cancer Prognosis: A Pooled Analysis of Four Population-Based Studies of Breast Cancer Survivors
Bibliographic record
Abstract
BACKGROUND: Complementary and alternative medicine (CAM) use is common among breast cancer survivors, but little is known about its impact on survival. METHODS: We pooled data from four studies conducted in Hawaii in 1994-2003 and linked to the Hawaii Tumor Registry to obtain long-term follow-up information. The effect of CAM use on the risk of breast cancer-specific death was evaluated using Cox regression. RESULTS: The analysis included 1443 women with a median follow-up of 11.8 years who had a primary diagnosis of in situ and invasive breast cancer. The majority were Japanese American (36.4%), followed by white (26.9%), Native Hawaiian (15.9%), other (10.6%), and Filipino (10.3%). CAM use was highest in Native Hawaiians (60.7%) and lowest in Japanese American (47.8%) women. Overall, any use of CAM was not associated with the risk of breast cancer-specific death (hazard ratio [HR] 1.47, confidence interval [CI] 0.91-2.36) or all-cause death (HR 0.82, 95% CI 0.63-1.06). However, energy medicine was associated with an increased risk of breast cancer-specific death (HR 3.19, 95% CI 1.06-8.52). When evaluating CAM use within ethnic subgroups, Filipino women who used CAM were at increased risk of breast cancer death (HR 6.84, 95% CI 1.23-38.19). CONCLUSIONS: Our findings suggest that, overall, CAM is not associated with breast cancer-specific death but that the effects of specific CAM modalities and possible differences by ethnicity should be considered in future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".