Quality of Life of Cancer Patients Treated with Chemotherapy
Bibliographic record
Abstract
Background: Life-quality tests are the basis for assessing the condition of oncological patients. They allow for obtaining valuable information from the patients regarding not only the symptoms of disease and adverse effects of the treatment but also assessment of the psychological, social and spiritual aspects. Taking into account assessment of the quality of life made by the patient in the course of disease has a positive effect on the well-being of patients, their families and their caregivers as well as on satisfaction with the interdisciplinary and holistic oncological care. Methods: A population-based, multi-area cross-sectional study was conducted among patients with cancer in the study in order to assess their life quality. The method used in the study was a clinical interview. Quality of life was measured using the EQ-5D-5L Quality of Life Questionnaire, the Karnofsky Performance Status, our own symptom checklist, Edmonton Symptom Assessment and Visual Analogue Scale. Results: In the subjective assessment of fitness, after using the Karnofsky fitness index, it was shown that 28% (95% CI (confidence interval): 27–30) of patients declared the ability to perform normal physical activity. In the assessment the profile, quality of life and psychometric properties of EQ-5D-5L, it was shown that patients had the most severe problems in terms of self-care (81%, 95% CI: 76–89) and feeling anxious and depressed (63%, 95% CI: 60–68). Conclusions: Cancer undoubtedly has a negative impact on the quality of life of patients, which is related to the disease process itself, the treatment used and the duration of the disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".