Impact Of Treatment On Patient-Reported Pain In Early Breast Cancer Patients Receiving Adjuvant Radiotherapy
Bibliographic record
Abstract
Background: Patients who receive radiation treatment (RT) for breast cancer often report pain, which contributes negatively to quality of life (QoL). This study aimed to identify demographic, treatment, and disease characteristics associated with pain using the Edmonton Symptom Assessment Scale (ESAS). Methods: We identified all patients diagnosed with non-metastatic breast cancer from 2011 Jan-2017 June at the Odette Cancer Centre with at least one ESAS completed pre- and post-RT. Data on systemic treatment, radiation, patient demographics, and disease stage were extracted. To identify factors associated with pain before and after RT and changes in pain, univariate and multivariate general linear regression analysis was conducted. p<0.05 was considered statistically significant. Results: This study included 1222 female patients with a mean age of 59 years old. ESAS was completed on average 28 and 142 days before RT (baseline) and after RT respectively. In multivariable analysis, higher baseline pain scores were associated with recently completing adjuvant chemotherapy and eventual receipt of locoregional or chest wall radiation. Two factors, adjuvant chemotherapy and chest wall radiation were associated with significant reduction in pain score after radiotherapy. Conclusions: No patient, treatment, or disease characteristics were associated with sustained increase in pain after radiation. Pre-existing pain in patients receiving chest wall radiation or adjuvant chemotherapy tended to reduce following RT completion, while pre-existing pain associated with locoregional RT tended to persist. Therefore, patients who receive locoregional RT should be screened for pain and provided pain management interventions and support when necessary.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.032 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.011 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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; both teacher heads agree on what is shown here.
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".