Feasibility Trial to Evaluate Tendon Stiffness Obtained from Shear Wave Elastography Imaging as a Biomarker of Aromatase Inhibitor-Induced Arthralgias
Bibliographic record
Abstract
Aromatase inhibitor-induced arthralgia (AIA) comprises significant, activity-limiting musculoskeletal symptoms, including joint pain, myalgia, and joint stiffness. We conducted a prospective feasibility study in postmenopausal women diagnosed with early-stage (0–3) hormone receptor positive (HR+) breast cancer who were candidates for treatment with adjuvant AI therapy (n = 16). Tendons of the hands and wrists and the median nerve were imaged using gray-scale and power Doppler ultrasound (US) and US SWE. Arthralgia symptoms were evaluated using the Breast Cancer Prevention Trial (BCPT) Symptom Checklist musculoskeletal subscale (MS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and stiffness subscales. At baseline, there were significant differences in the SW velocities of tendons between dominant and nondominant hands. Increased velocity in 2 of 6 tendons and the median nerve was associated with greater pain at baseline, whereas slower velocity of the extensor digitorum tendon (suggesting decreased stiffness) was associated with a higher WOMAC stiffness score. Increased SW velocity (suggestive of increased stiffness) at baseline in the abductor pollicis longus tendon was associated with a worsening of all three pain and stiffness measures by 6 months. Future studies should evaluate SWE scores related to AIA outcomes in a larger sample size.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".