Chronic Arm Morbidity After Curative Breast Cancer Treatment: Prevalence and Impact on Quality of Life
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To determine the prevalence of and contributing factors for chronic arm morbidity including lymphedema in breast cancer patients after treatment and to assess the impact of arm morbidity on quality of life (QOL). PATIENTS AND METHODS: A four-question screening questionnaire was developed and mailed to a random sample of 744 breast cancer patients treated curatively in two cancer centers from 1993 to 1997. Patients were without recurrence and at least 2 years from diagnosis. Respondents were classified as with or without arm-related symptoms on the basis of the survey. Stratified random samples from each group were then invited for a detailed assessment of their symptoms and signs, including the presence of lymphedema. Their QOL was assessed by the European Organization for Research and Treatment of Cancer QOL Questionnaire C-30 and by a detailed arm problem questionnaire that assessed various aspects of daily arm functioning. RESULTS: Approximately half of all screened patients were symptomatic and 12.5% of all assessed patients had lymphedema. Axillary dissection (AD) and axillary radiotherapy (RT) after dissection were statistically significantly related to the occurrence of arm symptoms (odds ratio for AD = 3.3, P <.001; odds ratio for RT = 3.1, P <.001). Symptomatic patients and patients with lymphedema both had impaired QOL compared with asymptomatic patients. CONCLUSION: Treatment for breast cancer is associated with considerable arm morbidity, which has a negative impact on QOL. Arm morbidity should be carefully monitored in future studies involving local treatment modalities for breast cancer.
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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) | 0.002 | 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