A Survey of Potentially Modifiable Patient-Level Factors Associated with Self-Report and Objectively Measured Adherence to Adjuvant Endocrine Therapies After Breast Cancer
Bibliographic record
Abstract
PURPOSE: Despite the efficacy of adjuvant endocrine therapy (AET) in reducing breast cancer recurrence and mortality, suboptimal AET adherence is common and hence an important clinical issue among breast cancer survivors. Delineating potentially modifiable patient-level factors associated with AET adherence may support the development of successful adherence-enhancing interventions. PATIENTS AND METHODS: The present study included 133 breast cancer survivors prescribed AET recruited from a cancer pharmacy. Women completed a baseline questionnaire examining psychosocial factors and self-reported adherence and consented to their prescription records being monitored for the proceeding 12 months to ascertain proportion of days covered (PDC), an objective measure of adherence. Regression analyses were used to identify the factors most strongly associated with both self-reported and objective adherence. Exploratory moderation analyses examined whether factors were differentially associated with adherence based on AET type (aromatase inhibitors or tamoxifen). RESULTS: Adherence was high in this sample (PDC over 12 months was 95%). Side effect severity was most strongly associated with self-reported adherence, followed by self-efficacy, and medication/healthcare system-related barriers. Medication/healthcare system-related barriers was the only factor that uniquely predicted objective adherence. Within medication/healthcare system-related barriers, fear of side effects was most strongly associated with both measures of adherence. There were no significant interactions between AET type and potentially modifiable factors in predicting self-reported or objective adherence. CONCLUSION: Side effects, reactions to side effects, and self-efficacy may represent modifiable targets through which AET adherence can be improved. Associations between potentially modifiable factors and adherence did not vary by AET type, despite distinct side-effect profiles.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".