Clinical practice recommendations for quality of life assessment in patients with gynecological cancer
Bibliographic record
Abstract
Quality of life (QoL) is a multidimensional concept regarding self-assessment of patients' situation. Quality of life has not been clearly defined up to date, although it is clear that it is a subjective self-assessment that to a significant extent is determined by individual needs, beliefs, values, attitudes, which are changing with time. Health-related QoL comprises basic dimensions such as patients' performance status, physical, emotional, and social functioning, symptoms of the disease and adverse effects of treatment, spiritual (God and existential) and other dimensions. In women, the ovary, cervical, corpus uterus, vagina and vulva cancers deteriorate QoL by disease progression and consequences of treatment, also in cancer survivors. Common symptoms include the genito-urinary system, the lower gastrointestinal tract and peripheral neuropathies induced by chemotherapy. In young women, QoL is impaired by infertility, sexual problems and menopause symptoms. An overview of QoL questionnaires used in oncology with special regard to patients with gynecological tumors was conducted. A screening tool for psychological state assessment of oncology patients (distress thermometer), the Edmonton Symptom Assessment System (ESAS) and modular approach of QoL assessment recommended by the EORTC (European Organization for the Research and Treatment of Cancer) were presented. Practical guidelines were proposed to assess appropriately QoL in patients with gynecological cancers who stay at in-patient gynecology units and those treated at home and in an ambulatory care setting.
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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 | 0.020 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".