Randomized Exercise Trial of Aromatase Inhibitor–Induced Arthralgia in Breast Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Arthralgia occurs in up to 50% of breast cancer survivors treated with aromatase inhibitors (AIs) and is the most common reason for poor AI adherence. We conducted, in 121 breast cancer survivors receiving an AI and reporting arthralgia, a yearlong randomized trial of the impact of exercise versus usual care on arthralgia severity. PATIENTS AND METHODS: Eligibility criteria included receiving an AI for at least 6 months, reporting ≥ 3 of 10 for worst joint pain on the Brief Pain Inventory (BPI), and reporting < 90 minutes per week of aerobic exercise and no strength training. Participants were randomly assigned to exercise (150 minutes per week of aerobic exercise and supervised strength training twice per week) or usual care. The BPI, Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index, and Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire were completed at baseline and at 3, 6, 9, and 12 months. Intervention effects were evaluated using mixed-model repeated measures analysis, with change at 12 months as the primary end point. RESULTS: Over 12 months, women randomly assigned to exercise (n = 61) attended 70% (± standard deviation [SD], 28%) of resistance training sessions and increased their exercise by 159 (± SD, 136) minutes per week. Worst joint pain scores decreased by 1.6 points (29%) at 12 months among women randomly assigned to exercise versus a 0.2-point increase (3%) among those receiving usual care (n = 60; P < .001). Pain severity and interference, as well as DASH and WOMAC pain scores, also decreased significantly at 12 months in women randomly assigned to exercise, compared with increases for those receiving usual care (all P < .001). CONCLUSION: Exercise led to improvement in AI-induced arthralgia in previously inactive breast cancer survivors.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".