Predictors of Pain Reduction in Trials of Interventions for Aromatase Inhibitor–Associated Musculoskeletal Symptoms
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Bibliographic record
Abstract
Abstract Background Almost one-half of aromatase inhibitor (AI)–treated breast cancer patients experience AI-associated musculoskeletal symptoms (AIMSS); 20%-30% discontinue treatment because of severe symptoms. We hypothesized that we could identify predictors of pain reduction in AIMSS intervention trials by combining data from previously conducted trials. Methods We pooled patient-level data from 3 randomized trials testing interventions (omega-3 fatty acids, acupuncture, and duloxetine) for AIMSS that had similar eligibility criteria and the same patient-reported outcome measures. Only patients with a baseline Brief Pain Inventory average pain score of at least 4 of 10 were included. The primary outcome examined was 2-point reduction in average pain from baseline to week 12. Variable cut-point selection and logistic regression were used. Risk models were built by summing the number of factors statistically significantly associated with pain reduction. Analyses were stratified by study and adjusted for treatment arm. Results For the 583 analyzed patients, the 4 factors statistically significantly associated with pain reduction were Functional Assessment of Cancer Therapy Functional Well-Being greater than 24 and Physical Well-Being greater than 14 (higher scores reflect better function), and Western Ontario and McMaster Universities Osteoarthritis Index less than 50 and Modified Score for the Assessment and Quantification of Chronic Rheumatoid Affections of the Hands less than 33 (lower scores reflect less pain). Patients with all 4 factors were greater than 6 times more likely to experience at least a 2-point pain reduction (odds ratio = 6.37, 95% confidence interval = 2.31 to 17.53, 2-sided P < .001); similar results were found for secondary 30% and 50% pain reduction endpoints. Conclusions Patients with AIMSS who have lower symptom and functional distress at study entry on AIMSS intervention trials are more likely to experience meaningful pain reduction. Baseline symptom and functional status should be considered as stratification factors in future interventional trials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it