Identification of Tools to Measure Changes in Musculoskeletal Symptoms and Physical Functioning in Women With Breast Cancer Receiving Aromatase Inhibitors
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To estimate and compare responsiveness of standardized self-reported measures of musculoskeletal symptoms (MSSs) and physical functioning (PF) during treatment with aromatase inhibitors (AIs). DESIGN: Prospective, longitudinal study. SETTING: Park Nicollet Institute and North Memorial Cancer Center, both in Minneapolis, MN. SAMPLE: 122 postmenopausal women with hormone receptor-positive breast cancer. METHODS: MSSs and PF were assessed before starting AIs and at one, three, and six months using six self-reported MSSs measures and two PF tests. MAIN RESEARCH VARIABLES: MSSs and PF changes from baseline to six months. FINDINGS: Using the Breast Cancer Prevention Trial-Musculoskeletal Symptom (BCPT-MS) subscale, 54% of participants reported MSSs by six months. Scores from the BCPT-MS subscale and the physical function subscales of the Australian/Canadian Osteoarthritis Hand Index (AUSCAN) and Western Ontario and McMaster Osteoarthritis Index (WOMAC) were most responsive to changes over six months. CONCLUSIONS: BCPT-MS, AUSCAN, and WOMAC were the most responsive instruments for measuring AI-associated MSSs. IMPLICATIONS FOR NURSING: Assessment and management of MSSs are important aspects of oncology care because MSSs can affect functional ability and AI adherence. KNOWLEDGE TRANSLATION: The three measures with the greatest sensitivity were the BCPT-MS, AUSCAN, and WOMAC questionnaires. These measures will be useful when conducting research on change in MSSs associated with AI treatment in women with breast cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".