The Influence of Chemotherapy-Induced Neurotoxicity on Psychological Distress and Sleep Sisturbance in Cancer Patients
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Bibliographic record
Abstract
PURPOSE: In the present study, we aimed to investigate the effects of chemotherapy-induced peripheral neurotoxicity (cipn) on psychological distress and sleep quality in cancer patients. METHODS: A total of 706 cancer patients were interviewed for the study. In the 4th week of treatment, patient cipn was measured using the Patient Neurotoxicity Questionnaire (pnq). The sleep quality and psychological distress of patients were measured using the Pittsburgh Sleep Quality Index (psqi), the Distress Thermometer (dt), and the Hospital Anxiety and Depression Scale (hads). Multiple logistic regression was applied to determine the independent effects of cipn on psychological distress and sleep disturbance in the patients. RESULTS: THESE CORRELATION COEFFICIENTS WERE OBTAINED: 0.387 (p < 0.0001) between the pnq total score and the dt score, 0.386 (p < 0.0001) between the pnq total score and the hads Depression score, 0.379 (p < 0.0001) between the pnq total score and the hads Anxiety score, and 0.399 (p < 0.0001) between the pnq total score and the psqi global score. The prevalence rates of distress, depression, anxiety, and poor sleep quality in the five pnq grades were statistically significantly different (p < 0.0001). After controlling for age, sex, education level, social supports, fatigue, disease stage, and tumour site, the pnq grades were found to be associated with depression (p < 0.0001), anxiety (p < 0.0001), and poor sleep quality (p < 0.0001). CONCLUSIONS: Chemotherapy-induced peripheral neurotoxicity negatively affects psychological distress and sleep quality in cancer patients treated with chemotherapy. High pnq grades were significantly associated with poor psychological status and sleep quality. Our results emphasize the importance of assessing peripheral neuropathies during chemotherapy and of adjusting treatment plans based on assessment results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it