Symptom Assessment for Patients with Non-small Cell Lung Cancer Scheduled for Chemotherapy.
Bibliographic record
Abstract
AIM: This study assessed the symptoms and health-related quality of life (HRQOL) of patients with advanced non-small cell lung cancer (NSCLC) and examined the symptom-associated characteristics. PATIENTS AND METHODS: The symptoms of 122 patients with NSCLC scheduled for chemotherapy before starting treatment were surveyed using the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire and Edmonton Symptom Assessment Scale (ESAS). RESULTS: The most prevalent symptoms were coughing (EORTC score 41.7), dyspnea (33.9), fatigue (31.9), insomnia (30.3) and pain (21.8). The mean EORTC score for global QoL was 56.9 (SD=23.5). Physical, cognitive and emotional functioning, insomnia, diarrhea, and dyspnea had a significant influence on the HRQOL (p<0.05). ESAS assessment correlated with these results and thus was an easy-to-use tool for symptom assessment (correlation coefficient range=0.546-0.865, p<0.0001 for all symptoms). CONCLUSION: Patients with advanced NSCLC suffer from multiple symptoms influencing HRQOL. ESAS provides a symptom assessment tool that is as reliable as but simpler to use than the EORTC questionnaire.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".