Health-Related Quality of Life and Treatment Satisfaction of Patients with Malignant IDH Wild-Type Gliomas and Their Caregivers
Bibliographic record
Abstract
(1) Background: Clinical aspects like sex, age, Karnofsky Performance Scale (KPS) and psychosocial distress can affect the health-related quality of life (HR-QoL) and treatment satisfaction of patients with malignant isocitrate dehydrogenase wild-type (IDHwt) gliomas and caregivers. (2) Methods: We prospectively investigated the HR-QoL and patient/caregiver treatment satisfaction in a cross-sectional study with univariable and multiple regression analyses. Questionnaires were applied to investigate the HR-QoL (EORTC QLQ-C30, QLQ-BN20) and treatment satisfaction (EORTC PATSAT-C33). (3) Results: A cohort of 61 patients was investigated. A higher KPS was significantly associated with a better HR-QoL regarding the functional scales of the EORTC QLQ-C30 (p < 0.004) and a lower symptom burden regarding the EORTC QLQ-BN20 (p < 0.001). The patient treatment satisfaction was significantly poorer in the patients older than 60 years in the domain of family involvement (p = 0.010). None of the investigated aspects showed a significant impact on the treatment satisfaction of caregivers. (4) Conclusions: We demonstrated that in patients with IDHwt gliomas, the KPS was the most important predictor for a better HR-QoL in functional domains. Data on the HR-QoL and treatment satisfaction in patients with IDHwt gliomas and their caregivers are rare; therefore, further efforts should be made to improve supportive care in this highly distressed cohort.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".