Pain and quality of life in breast cancer patients
Bibliographic record
Abstract
OBJECTIVE: To evaluate the influence of pain on quality of life in breast cancer patients. METHODS: A cross-sectional study of 400 patients, including 118 without metastasis, 160 with loco-regional metastasis and 122 with distant metastasis. The instruments used were the European Organization for Research and Treatment for Cancer Quality of Life Questionnaire-Core 30 and the Breast Cancer-specific 23 and short McGill Pain Questionnaire. RESULTS: In total, 71.7% of patients reported pain. The most frequent sensory descriptor used by patients was 'jumping.' In the evaluative dimension, the main descriptor chosen was troublesome. The Global Health self-assessment showed pain to be inversely correlated with quality of life: the group without metastasis had a mean score of 55.3 (SD=24.8) for those in pain, which rose to 69.7 (SD=19.2) for those without pain (p=0.001). Subjects with loco-regional metastasis had score of 59.1 (SD=21.3) when in pain, and those without pain had a significantly higher score of 72.4 (SD=18.6) (p<0.001). Patients from the distant metastasis group showed similar results with a mean score of 48.6 (SD=23.1) for those in pain and 67.6 (SD=20.4) for those without pain (p=0.002). Regarding the association of pain intensity and quality of life, patients with distant metastasis and intense pain had the worst scores for quality of life with a functional scale mean of 49.9 (SD=17.3) (p<0.009), a Symptom Scale score of 50.0 (SD=20.1) (p<0.001) and a Global Health Scale score of 39.7 (SD=24.7) (p<0.006). CONCLUSIONS: Pain compromises the quality of life of patients with breast cancer, particularly those with advanced stages of the disease.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".